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Narottama, Bhaskara, Denny Kusuma Hendraningrat, and Soo Young Shin. "Quantum-inspired evolutionary algorithms for NOMA user pairing." ICT Express 8, no. 1 (March 2022): 11–17. http://dx.doi.org/10.1016/j.icte.2022.01.014.
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El-ghorab, Mahmoud Ahmed, Mohamed Rihan El-meligy, Mohamed Mostafa Ibrahim, and Fatma Newagy. "Energy-Efficient User Pairing for Downlink NOMA in Massive MIMO Networks." Applied Sciences 12, no. 11 (May 27, 2022): 5421. http://dx.doi.org/10.3390/app12115421.
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The motivations for deploying energy and spectral-efficient network architectures are the high energy consumption and the need for more spectral resources in modern cellular networks. The key method to solve the energy efficiency EE maximization problem of the downlink non-orthogonal multiple access (NOMA)-based massive MIMO system is to decouple it into user pairing and efficient power allocation problems. This work studies the performance of three main pairing methods in NOMA-based networks: Hungarian, Gale–Shapley, and correlation-based approaches. Firstly, we provide a mathematical analysis for EE of downlink NOMA in a massive MIMO system for the non-line of sight (NLoS) channel model with perfect successive interference cancellation (SIC). Finally, the sequential convex programming (SCP) approach is used to tackle the power allocation problem. Simulation results show that the Hungarian algorithm for pairing plus SCP for power allocation (Hungarian algorithm-SCP) achieves the highest energy efficiency among all the three pairing algorithms with an identical performance to joint user and resource block association with power allocation (joint user-RB PA) algorithm but with much lower computational complexity and outperforms the NOMA SCP greedy algorithm (NOMA-SCP-GA).
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Ibrahim, Hesham S., Mohamed Abaza, Ali Mansour, and Ayman Alfalou. "Performance Analysis of Power Allocation and User-Pairing Techniques for MIMO-NOMA in VLC Systems." Photonics 11, no. 3 (February 25, 2024): 206. http://dx.doi.org/10.3390/photonics11030206.
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In this paper, we evaluate the performance of multiple-input multiple-output (MIMO) communication systems applied with a non-orthogonal multiple access (NOMA)-based indoor visible light communication (VLC). We present two efficient user-pairing algorithms for NOMA in VLC, aiming to enhance achievable data rates effectively. Our investigation involves the application of three low-complexity power allocation techniques. Comparative analysis reveals performance enhancements when employing the proposed schemes, especially when contrasted with NOMA without user pairing and orthogonal frequency division multiple access (OFDMA). Additionally, we explore the performance of both algorithms in scenarios with both even and odd numbers of users. Simulation results demonstrate the superiority of NOMA in comparison to OFDMA.
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Wu, Jiang, Leyang Sun, and Yubo Jia. "User Pairing and Power Allocation for NOMA-CoMP Based on Rate Prediction." Information 13, no. 4 (April 15, 2022): 200. http://dx.doi.org/10.3390/info13040200.
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In this paper, we consider a non-orthogonal multiple access (NOMA) system with coordinated multi-point (CoMP), which is used in 5G cellular networks to guarantee the rate requirements from the different edge users. Based on the China Family Panel Studies (CFPS) dataset, we use several learning algorithms to predict users’ rate requirements according to their profiles. We propose a many-to-many two-side subchannel–user matching strategy, which can classify users into cell-center users, high-rate requirement edge users, and low-rate requirement edge users based on their status and learning prediction results, and pair users with different subchannels to form joint transmission CoMP (JT-CoMP) subchannels and dynamic point selection CoMP (DPS-CoMP) subchannels. Furthermore, a discrete power allocation algorithm based on group search is proposed. Simulation results show that our proposed algorithm outperforms the traditional NOMA-CoMP algorithm and maximum throughput (MT) NOMA-CoMP algorithm. It maximizes the rate of high-rate requirement edge users while guaranteeing user fairness.
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Ma, Lizhi, Guangyu Liu, and Shuo Liu. "Design of Pairing Mechanisms for the Device-to-Device Communication System." Journal of Physics: Conference Series 2537, no. 1 (June 1, 2023): 012017. http://dx.doi.org/10.1088/1742-6596/2537/1/012017.
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Abstract The potential of device-to-device (D2D) communication lies in improving system performance and user experience. Thus, D2D communication is widely concerned. For the D2D communication system, this work investigates the D2D pairing problem to maximize the sum rate of all D2D pairs. To comprehensively compare the performance of different algorithms, three pairing mechanisms are proposed based on the graph theory and the matching theory. The simulation results show the impact of the network scale on the optimized results. And for small and large network scales, the Hungary algorithm and the minimum distance matching algorithm are selected as the D2D pairing mechanism, respectively.
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Annadurai, Soorya, and Bhargav J. Bhatkalkar. "Secure Multiparty Device Pairing Using Random Peephole Generations." Journal of Computational and Theoretical Nanoscience 17, no. 1 (January 1, 2020): 216–21. http://dx.doi.org/10.1166/jctn.2020.8653.
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A secure device pairing mechanism is used to establish a trusted communication channel between unassociated wireless devices. The broadcast nature of wireless communication opens the door for man-in-the-middle (MITM) attacks, and even other subtle forms of masquerader and misfeasor attacks. This paper introduces a simple device pairing approach to tackle such attacks seamlessly. The algorithm is compatible with a multitude of devices, whereas a majority of existing algorithms are based on two devices exclusively. This approach utilizes a human visual channel as an Out-Of-Band (OOB) channel to authenticate the public keys exchanged between the devices. The interactive nature of this approach forces user attention, hence improving the reliability and consistency of the device pairing process. To do so, we introduce the concept of ‘peepholes,’ and mathematically define it before demonstrating the algorithm’s methodology. Subsequent sections also demonstrate its robustness against attacks via misfeasors, masqueraders, and men-in-the-middle.
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Wang, Xinshui, Ke Meng, Xu Wang, Zhibin Liu, and Yuefeng Ma. "Dynamic User Resource Allocation for Downlink Multicarrier NOMA with an Actor–Critic Method." Energies 16, no. 7 (March 24, 2023): 2984. http://dx.doi.org/10.3390/en16072984.
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Future wireless communication systems require higher performance requirements. Based on this, we study the combinatorial optimization problem of power allocation and dynamic user pairing in a downlink multicarrier non-orthogonal multiple-access (NOMA) system scenario, aiming at maximizing the user sum rate of the overall system. Due to the complex coupling of variables, it is difficult and time-consuming to obtain an optimal solution, making engineering impractical. To circumvent the difficulties and obtain a sub-optimal solution, we decompose this optimization problem into two sub-problems. First, a closed-form expression for the optimal power allocation scheme is obtained for a given subchannel allocation. Then, we provide the optimal user-pairing scheme using the actor–critic (AC) algorithm. As a promising approach to solving the exhaustive problem, deep-reinforcement learning (DRL) possesses higher learning ability and better self-adaptive capability than traditional optimization methods. Simulation results have demonstrated that our method has significant advantages over traditional methods and other deep-learning algorithms, and effectively improves the communication performance of NOMA transmission to some extent.
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Chandrasekaran, Balaji, and Ramadoss Balakrishnan. "An Efficient Tate Pairing Algorithm for a Decentralized Key-Policy Attribute Based Encryption Scheme in Cloud Environments." Cryptography 2, no. 3 (July 15, 2018): 14. http://dx.doi.org/10.3390/cryptography2030014.
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Attribute-based encryption (ABE) is used for achieving data confidentiality and access control in cloud environments. Most often ABE schemes are constructed using bilinear pairing which has a higher computational complexity, making algorithms inefficient to some extent. The motivation of this paper is on achieving user privacy during the interaction with attribute authorities by improving the efficiency of ABE schemes in terms of computational complexity. As a result the aim of this paper is two-fold; firstly, to propose an efficient Tate pairing algorithm based on multi-base number representation system using point halving (TP-MBNR-PH) with bases 1/2, 3, and 5 to reduce the cost of bilinear pairing operations and, secondly, the TP-MBNR-PH algorithm is applied in decentralized KP-ABE to compare its computational costs for encryption and decryption with existing schemes.
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Zhao, Zhixin, Dong Wang, Hongwei Zhang, and Haitao Sang. "Joint User Pairing and Power Allocation Scheme Based on Transmission Mode Switching between NOMA-Based Maximum Ratio Transmission and MMSE Beamforming in Downlink MISO Systems." Mobile Information Systems 2021 (March 9, 2021): 1–21. http://dx.doi.org/10.1155/2021/6671371.
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This paper investigates the design of the joint user pairing and power allocation scheme with transmission mode switching (TMS) in downlink multiple-input-single-output (MISO) systems. Firstly, the closed-form expressions of the boundary of achievable rate region of two candidate transmission modes, i.e., non-orthogonal multiple access based maximum ratio transmission (NOMA-MRT) and minimum mean square error beamforming (MMSE-BF), are obtained. By obtaining the outer boundary of the union of the achievable rate regions of the two transmission modes, an adaptive switching method is developed to achieve a larger rate region. Secondly, based on the idea that the solution to the problem of weighted sum rate (WSR) optimization must be on the boundary of the achievable rate region, the optimal solutions to the problem of WSR optimization for NOMA-MRT and MMSE-BF are obtained for the two-user case, respectively. Subsequently, by exploiting the aforementioned optimal solutions for two transmission modes and the high efficiency of TMS, a suboptimal user pairing and power allocation algorithm (JUPA) is proposed to further improve the sum rate performance for the multiuser case. Compared with the exhaustive search-based user pairing and power allocation algorithm (ES-PPA), the proposed JUPA can enjoy a much lower computational complexity and only suffers a slight sum rate performance loss, and it outperforms other traditional schemes. Finally, numerical results are provided to validate the analyses and the proposed algorithms.
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Yu, Zhihao, and Jia Hou. "Research on Interference Coordination Optimization Strategy for User Fairness in NOMA Heterogeneous Networks." Electronics 11, no. 11 (May 26, 2022): 1700. http://dx.doi.org/10.3390/electronics11111700.
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In order to comprehensively improve the performance of edge users in heterogeneous cellular networks and the fairness of network users, a downlink interference coordination optimization strategy in heterogeneous cellular networks with non-orthogonal multiple access (NOMA) based on the cell range expansion (CRE) and the almost blank subframe (ABS) technology is proposed. Different from the traditional interference coordination strategy, a NOMA user pairing scheme combined with ABS technology and a dynamic NOMA power allocation scheme are designed to maximize the network fairness based on the optimized throughput of the edge users. The simulation results show that the proposed optimization strategy can balance the performance of network users more effectively to improve the throughput of edge users and network fairness than other NOMA user pairing and power allocation algorithms without the complexity being increased.
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Shen, Yanyan, Shuqiang Wang, and Zhiming Wei. "Joint Subchannel Pairing and Power Control for Cognitive Radio Networks with Amplify-and-Forward Relaying." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/380106.
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Dynamic spectrum sharing has drawn intensive attention in cognitive radio networks. The secondary users are allowed to use the available spectrum to transmit data if the interference to the primary users is maintained at a low level. Cooperative transmission for secondary users can reduce the transmission power and thus improve the performance further. We study the joint subchannel pairing and power allocation problem in relay-based cognitive radio networks. The objective is to maximize the sum rate of the secondary user that is helped by an amplify-and-forward relay. The individual power constraints at the source and the relay, the subchannel pairing constraints, and the interference power constraints are considered. The problem under consideration is formulated as a mixed integer programming problem. By the dual decomposition method, a joint optimal subchannel pairing and power allocation algorithm is proposed. To reduce the computational complexity, two suboptimal algorithms are developed. Simulations have been conducted to verify the performance of the proposed algorithms in terms of sum rate and average running time under different conditions.
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Rehman, Bilal Ur, Mohammad Inayatullah Babar, Arbab Waheed Ahmad, Hesham Alhumyani, Gamil Abdel Azim, Rashid A. Saeed, and Sayed Abdel Khalek. "Joint power control and user grouping for uplink power domain non-orthogonal multiple access." International Journal of Distributed Sensor Networks 17, no. 12 (December 2021): 155014772110574. http://dx.doi.org/10.1177/15501477211057443.
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Orthogonal multiple access schemes based on assignment of communication resource blocks among multiple contenders, although widely available, still necessitate an upper limit on the number of concurrent users for minimization of multiple-user interference. The feature thwarts efforts to cater for pressing connectivity demands posed by modern-day cellular communication networks. Non-orthogonal multiple access, regarded as a key advancement towards realization of high-speed 5G wireless communication networks, enables multiple users to access the same set of resource blocks non-orthogonally in terms of power with controllable interference, thereby allowing for overall performance enhancement. Owing to the combinatorial nature of the underlying optimization problem involving user pairing/grouping scheme, power control and decoding order, the computational complexity in determining optimal and sub-optimal solutions remains considerably high. This work proposes three novel alternative approaches (Randomly, 2-Opt and Hybrid) for arriving at a near-optimal solution for the problem of user pairing/grouping. The algorithms not only offer reduced computational complexity but also outperform orthogonal multiple access and existing schemes reported in the literature for uplink non-orthogonal multiple access systems.
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Hibbing, Paul R., Samuel R. LaMunion, Haileab Hilafu, and Scott E. Crouter. "Evaluating the Performance of Sensor-Based Bout Detection Algorithms: The Transition Pairing Method." Journal for the Measurement of Physical Behaviour 3, no. 3 (September 1, 2020): 219–27. http://dx.doi.org/10.1123/jmpb.2019-0039.
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Background: Bout detection algorithms are used to segment data from wearable sensors, but it is challenging to assess segmentation correctness. The purpose of this study was to present and demonstrate the Transition Pairing Method (TPM), a new method for evaluating the performance of bout detection algorithms. Methods: The TPM compares predicted transitions to a criterion measure in terms of number and timing. A true positive is defined as a predicted transition that corresponds with one criterion transition in a mutually exclusive pair. The pairs are established using an extended Gale-Shapley algorithm, and the user specifies a maximum allowable within-pair time lag, above which pairs cannot be formed. Unpaired predictions and criteria are false positives and false negatives, respectively. The demonstration used raw acceleration data from 88 youth who wore ActiGraph GT9X monitors (right hip and non-dominant wrist) during simulated free-living. Youth Sojourn bout detection algorithms were applied (one for each attachment site), and the TPM was used to compare predicted bout transitions to the criterion measure (direct observation). Performance metrics were calculated for each participant, and hip-versus-wrist means were compared using paired t-tests (α = 0.05). Results: When the maximum allowable lag was 1-s, both algorithms had recall <20% (2.4% difference from one another, p < .01) and precision <10% (1.4% difference from one another, p < .001). That is, >80% of criterion transitions were undetected, and >90% of predicted transitions were false positives. Conclusion: The TPM improves on conventional analyses by providing specific information about bout detection in a standardized way that applies to any bout detection algorithm.
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Nguyen, Kha-Hung, Hieu V. Nguyen, Mai T. P. Le, Tuan X. Cao, and Oh-Soon Shin. "Rate Fairness and Power Consumption Optimization for NOMA-Assisted Downlink Networks." Energies 14, no. 1 (December 24, 2020): 58. http://dx.doi.org/10.3390/en14010058.
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This paper considers a non-orthogonal multiple access (NOMA) downlink network, where a hybrid of NOMA and beamforming designs is developed to enhance the channel capacity. We aim to improve the system performance in terms of rate fairness and power consumption. Hence, a multi-objective problem with a joint optimization of user equipment pairing, power control, and quality-of-service requirements is addressed. To efficiently solve the problem, we propose two low-complexity algorithms based on the inner-approximation method, with the first algorithm using the relaxation method and the second one using graph theory. Numerical results are provided to demonstrate the effectiveness of the two proposed algorithms in comparison with the exhaustive search and existing methods.
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Mancharla, Ravi, and Yaka Bulo. "A Comparative Analysis of the various Power Allocation Algorithm in NOMA-MIMO Network Using DNN and DLS Algorithm." ICST Transactions on Mobile Communications and Applications 7, no. 2 (August 31, 2022): e3. http://dx.doi.org/10.4108/eetmca.v7i2.2651.
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The high data rate, huge spectrum efficiency, successive interference cancellation (SIC), and ultra-reliable low latency (URLL) are of the demand for next-generation technologies. Non-orthogonal multiple access (NOMA) scheme provides multi-user scaling (multiplexing), optimum spectral efficiency (SE), excellent user-pairing improvement, and a single resource block sharing by multiple users because of which it is a more preferable scheme over orthogonal multiple access (OMA) for the next generation technologies. This article investigates comparative analysis of various power allocation algorithms in multiple-input multiple-output-NOMA (MIMO-NOMA) technology and to come up with the best power allocation algorithm which suited best for MIMO-NOMA technology. Firstly, comparison analysis will be carried out considering direct methodologies followed by power allocation algorithm using Deep Neural Network (DNN) along with the Depth limited search (DLS) algorithm. These techniques are tested on two users initially then followed by multi-user communication. Allocating optimal power to the poor signal strength user terminal (user not receiving appropriate signal power) is a difficult task in actual scenario, and moreover, SIC also creates complexity in the proper allocation of Base station (BS) source power. The above problems can be solved with the assistance of the DNN along with the DLS algorithm, where the weaker user receives maximum power and the stronger user receives minimum power. The DNN-MIMO-NOMA technology, which is based on the DLS algorithm, helps user terminals to get their signals free from noise (inter_user_interference) and with greater precision. The DLS process (algorithm) offers higher potential in MIMO-NOMA with DNN technology for successfully applying SIC. Here, MIMO helps to improve the channel gain. A DLS provides an optimum power allocation (OPA) based on the position of user equipment. The simulation results show that the power allocation method using DNN along with DLS algorithm achieves better performance than the traditional multi-user.
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Dadwal, Jyoti, and Bhubneshwar Sharma. "Bluetooth SIG oversees development of the specification and prediction of program that protects Bluetooth pin." International Journal of Advances in Scientific Research 2, no. 2 (February 28, 2016): 59. http://dx.doi.org/10.7439/ijasr.v2i2.2753.
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Bluetooth implementsconfidentiality,authenticationandkeyderivation with custom algorithms based on theSAFER+block cipher. Bluetooth key generation is generally based on a Bluetooth PIN, which must be entered into both devices. This procedure might be modified if one of the devices has a fixed PIN (e.g., for headsets or similar devices with a restricted user interface). During pairing, an initialization key or master key is generated, using the E22 algorithm.TheE0 stream cipher is used for encrypting packets, granting confidentiality, and is based on a shared cryptographic secret, namely a previously generated link key or master key. Those keys, used for subsequent encryption of data sent via the air interface, rely on the Bluetooth PIN, which has been entered into one or both devices.
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Zhou, Yuetian, Bowen Cai, and Xue Ding. "Joint Power Control and Resource Allocation for Optimizing the D2D User Performance of Full-Duplex D2D Underlying Cellular Networks." Sensors 23, no. 23 (December 1, 2023): 9549. http://dx.doi.org/10.3390/s23239549.
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D2D communication is a promising technology for enhancing spectral efficiency (SE) in cellular networks, and full-duplex (FD) has the potential to double SE. Due to D2D’s short-distance communication and low transmittance power, it is natural to integrate FD into D2D, creating FD-D2D to underlay a cellular network to further improve SE. However, the residual self-interference (RSI) resulting from FD-D2D and interference arising from spectrum sharing between D2D users (DUs) and cellular users (CUs) can restrict D2D link performance. Therefore, we propose an FD-D2D underlying cellular system in which DUs jointly share uplink and downlink spectral resources with CUs. Moreover, we present two algorithms to enhance the performance experience of DUs while improving the system’s SE. For the first algorithm, we tackle an optimization problem aimed at maximizing the sum rate of FD-DUs in the system while adhering to transmittance power constraints. This problem is formulated as a mixed-integer nonlinear programming problem (MINLP), known for its mathematical complexity and NP-hard nature. In order to address this MINLP, our first algorithm decomposes it into two subproblems: power control and spectral resource allocation. The power control aspect is treated as a nonlinear problem, which we solve through one-dimensional searching. Meanwhile, spectral resource allocation is achieved using the Kuhn–Munkres algorithm, determining the pairing of CUs and DUs sharing the same spectrum. As for the second algorithm, our objective is to enhance the individual performance of FD-DUs by maximizing the minimum rate among them, ensuring more uniform rate performance across all FD-DUs. In order to solve this optimization problem, we propose a novel spectral resource allocation algorithm based on bisection searching and the Kuhn–Munkres algorithm, whereas the power control aspect remains the same as in the first algorithm. The numerical results demonstrate that our proposed algorithm effectively enhances the performance of DUs in an FD-D2D underlying cellular network when compared to the sum rate maximization design.
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Wan, Changsheng, Juan Zhang, and Daoli Huang. "SCPR: Secure Crowdsourcing-Based Parking Reservation System." Security and Communication Networks 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/1076419.
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The crowdsourcing-based parking reservation system is a new computing paradigm, where private owners can rent their parking spots out. Security is the main concern for parking reservation systems. However, current schemes cannot provide user privacy protection for drivers and have no key agreement functions, resulting in a lot of security problems. Moreover, current schemes are typically based on the time-consuming bilinear pairing and not suitable for real-time applications. To solve these security and efficiency problems, we present a novel security protocol with user privacy called SCPR. Similar to protocols of this field, SCPR can authenticate drivers involved in the parking reservation system. However, different from other well-known approaches, SCPR uses pseudonyms instead of real identities for providing user privacy protection for drivers and designs a novel pseudonym-based key agreement protocol. Finally, to reduce the time cost, SCPR designs several novel cryptographic algorithms based on the algebraic signature technique. By doing so, SCPR can satisfy a number of security requirements and enjoy high efficiency. Experimental results show SCPR is feasible for real world applications.
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Jemihin, Zulianie Binti, Soo Fun Tan, and Gwo-Chin Chung. "Attribute-Based Encryption in Securing Big Data from Post-Quantum Perspective: A Survey." Cryptography 6, no. 3 (August 5, 2022): 40. http://dx.doi.org/10.3390/cryptography6030040.
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Attribute-based encryption (ABE) cryptography is widely known for its potential to solve the scalability issue of recent public key infrastructure (PKI). It provides a fine-grained access control system with high flexibility and efficiency by labeling the secret key and ciphertext with distinctive attributes. Due to its fine-grained features, the ABE scheme is a protection layer in securing users’ data and privacy in big data processing and analytics. However, quantum computing, new technology on the horizon that will transform the security and privacy environment, has begun to appear. Like the conventional ABE schemes, present cryptography is not excluded from the impacts of quantum technology as they are not made to be quantum-resistant. While most recent surveys generally touched on the generic features of attribute-based encryption schemes such as user revocation, scalability, flexibility, data confidentiality, and scope in pairing-based ABE schemes, this survey investigated quantum-resistant ABE schemes in securing big data. This survey reviews the challenges faced by the recent ABE cryptography in the post-quantum era and highlights its differences from the conventional pairing-based ABE schemes. Subsequently, we defined the criteria of an ideal quantum-resistant ABE scheme. Additionally, existing works on quantum-resistant ABE schemes are reviewed based on their algorithms design, security and functionalities. Lastly, we summarized quantum-resistant ABE schemes’ ongoing challenges and future works.
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Hao, Wanming, Shouyi Yang, and Wanliang Hao. "Relay Selection and Subcarrier-Pair Based Energy-Efficient Resource Allocation for Multirelay Cooperative OFDMA Networks." International Journal of Antennas and Propagation 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/461713.
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Energy-efficient resource allocation is investigated for a relay-based multiuser cooperation orthogonal frequency division multiple access (OFDMA) uplink system with amplify-and-forward (AF) protocol for all relays. The objective is to maximize the total energy efficiency (EE) of the uplink system with consideration of some practical limitations, such as the individual power constraint for the users and relays and the quality of service (QoS) for every user. We formulate an energy-efficient resource allocation problem that seeks joint optimization of subcarrier pairing, relay selection, subcarrier assignment, and power allocation. Unlike previous optimization throughput models, we transform the considered EE problem in fractional form into an equivalent optimal problem in subtractive form, which is solved by using dual decomposition and subgradient methods. To reduce computation costs, we propose two low-complexity suboptimal schemes. Numerical studies are conducted to evaluate the EE of the proposed algorithms.
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Jerath, Ravinder, Mohammad Syam, and Shajia Ahmed. "The Future of Stress Management: Integration of Smartwatches and HRV Technology." Sensors 23, no. 17 (August 22, 2023): 7314. http://dx.doi.org/10.3390/s23177314.
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In the modern world, stress has become a pervasive concern that affects individuals’ physical and mental well-being. To address this issue, many wearable devices have emerged as potential tools for stress detection and management by measuring heart rate, heart rate variability (HRV), and various metrics related to it. This literature review aims to provide a comprehensive analysis of existing research on HRV tracking and biofeedback using smartwatches pairing with reliable 3rd party mobile apps like Elite HRV, Welltory, and HRV4Training specifically designed for stress detection and management. We apply various algorithms and methodologies employed for HRV analysis and stress detection including time-domain, frequency-domain, and non-linear analysis techniques. Prominent smartwatches, such as Apple Watch, Garmin, Fitbit, Polar, and Samsung Galaxy Watch, are evaluated based on their HRV measurement accuracy, data quality, sensor technology, and integration with stress management features. We describe the efficacy of smartwatches in providing real-time stress feedback, personalized stress management interventions, and promoting overall well-being. To assist researchers, doctors, and developers with using smartwatch technology to address stress and promote holistic well-being, we discuss the data’s advantages and limitations, future developments, and the significance of user-centered design and personalized interventions.
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Lam, Michelle S., Ayush Pandit, Colin H. Kalicki, Rachit Gupta, Poonam Sahoo, and Danaë Metaxa. "Sociotechnical Audits: Broadening the Algorithm Auditing Lens to Investigate Targeted Advertising." Proceedings of the ACM on Human-Computer Interaction 7, CSCW2 (September 28, 2023): 1–37. http://dx.doi.org/10.1145/3610209.
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Algorithm audits are powerful tools for studying black-box systems without direct knowledge of their inner workings. While very effective in examining technical components, the method stops short of a sociotechnical frame, which would also consider users themselves as an integral and dynamic part of the system. Addressing this limitation, we propose the concept of sociotechnical auditing: auditing methods that evaluate algorithmic systems at the sociotechnical level, focusing on the interplay between algorithms and users as each impacts the other. Just as algorithm audits probe an algorithm with varied inputs and observe outputs, a sociotechnical audit (STA) additionally probes users, exposing them to different algorithmic behavior and measuring their resulting attitudes and behaviors. As an example of this method, we develop Intervenr, a platform for conducting browser-based, longitudinal sociotechnical audits with consenting, compensated participants. Intervenr investigates the algorithmic content users encounter online, and also coordinates systematic client-side interventions to understand how users change in response. As a case study, we deploy Intervenr in a two-week sociotechnical audit of online advertising (N = 244) to investigate the central premise that personalized ad targeting is more effective on users. In the first week, we observe and collect all browser ads delivered to users, and in the second, we deploy an ablation-style intervention that disrupts normal targeting by randomly pairing participants and swapping all their ads. We collect user-oriented metrics (self-reported ad interest and feeling of representation) and advertiser-oriented metrics (ad views, clicks, and recognition) throughout, along with a total of over 500,000 ads. Our STA finds that targeted ads indeed perform better with users, but also that users begin to acclimate to different ads in only a week, casting doubt on the primacy of personalized ad targeting given the impact of repeated exposure. In comparison with other evaluation methods that only study technical components, or only experiment on users, sociotechnical audits evaluate sociotechnical systems through the interplay of their technical and human components.
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Veerabhadram, Vadlamani, and Gregory Arul Dalton. "Optimal and Efficient Searchable Encryption with Single Trapdoor for Multi-Owner Data Sharing in Federated Cloud Computing." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 6s (June 14, 2023): 528–42. http://dx.doi.org/10.17762/ijritcc.v11i6s.6964.
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Cloud computing, an Internet based computing model, has changed the way of data owners store and manage data. In such environment, data sharing is very important with more efficient data access control. Issuing an aggregate key to users on data enables and authorizes them to search for data of select encrypted files using trapdoor or encrypted keyword. The existing schemes defined for this purpose do have certain limitations. For instance, Cui et al. scheme is elegant but lacks in flexibility in access control in presence of multiple data owners sharing data to users. Its single trapdoor approach needs transformation into individual trapdoors to access data of specific data owner. Moreover, the existing schemes including that of Cui et al. does not support federated cloud. In this paper we proposed an efficient key aggregate searchable encryption scheme which enables multiple featuressuch as support for truly single aggregate key to access data of many data owners, federated cloud support,query privacy, controlled search process and security against cross-pairing attack. It has algorithms for setup, keygen, encrypt, extract, aggregate, trapdoor, test and federator. In multi-user setting it is designed to serve data owners and users with secure data sharing through key aggregate searchable encryption The proposed scheme supports federated cloud. Experimental results revealed that the proposed scheme is provably secure withrelatively less computational overhead and time complexity when compared with the state of the art.
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Choi, Hyun-Ho, and Wonjong Noh. "Outage Analysis of User Pairing Algorithm for Full-Duplex Cellular Networks." Wireless Communications and Mobile Computing 2019 (January 2, 2019): 1–12. http://dx.doi.org/10.1155/2019/4909450.
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In a full-duplex (FD) cellular network, a base station transmits data to the downlink (DL) user and receives data from uplink (UL) users at the same time; thereby the interference from UL users to DL users occurs. One of the possible solutions to reduce this interuser interference in the FD cellular network is user pairing, which pairs a DL user with a UL user so that they use the same radio resource at the same time. In this paper, we consider a user pairing problem to minimize outage probability and formulate it as a nonconvex optimization problem. As a solution, we design a low-complexity user pairing algorithm, which first controls the UL transmit power to minimize the interuser interference and then allows the DL user having a worse signal quality to choose first its UL user giving less interference to minimize the outage probability. Then, we perform theoretical outage analysis of the FD cellular network on the basis of stochastic geometry and analyze the performance of the user pairing algorithm. Results show that the proposed user pairing significantly decreases the interuser interference and thus improves the DL outage performance while satisfying the requirement of UL signal-to-interference-plus-noise ratio, compared to the conventional HD mode and a random pairing. We also reveal that there is a fundamental tradeoff between the DL outage and UL outage according to the user pairing strategy (e.g., throughput maximization or outage minimization) in the FD cellular network.
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Noh, Wonjong, Wonjae Shin, and Hyun-Ho Choi. "Performance Analysis of User Pairing Algorithm in Full-Duplex Cellular Networks." Mobile Information Systems 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/8182150.
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In a full duplexing (FD) wireless cellular network, a base station operates in FD mode, while the downlink (DL) and uplink (UL) users operate in half duplexing (HD) mode. Thus, the downlink and uplink transmissions occur simultaneously so that interuser interference from a UL to a DL user occurs. In an FD network, the main challenge to minimize the interuser interference is user pairing, which determines a pair of DL and UL users who use the same radio resource simultaneously. We formulate a nonconvex optimization problem for user pairing to maximize the cell throughput. Then, we propose a heuristic user pairing algorithm with low complexity. This algorithm is designed such that the DL user having a better signal quality has higher priority to choose its paired UL user for throughput maximization. Thereafter, we conduct theoretical performance analysis of the FD cellular system based on stochastic geometry and analyze the impact of the user paring algorithm on the performance of the FD cellular system. Results show that the FD system that uses the proposed user pairing algorithm effectively reduces the interuser interference and approaches optimal performance. It also considerably outperforms the FD system using a random user pairing and almost doubles the conventional HD system in terms of cell throughput.
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Wu, Guowei, Guifen Chen, and Tong Zhu. "Resource allocation algorithm in Heterogeneous Network Based on Non-orthogonal Multiple Access." Journal of Physics: Conference Series 2637, no. 1 (November 1, 2023): 012046. http://dx.doi.org/10.1088/1742-6596/2637/1/012046.
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Abstract The proposed resource allocation algorithm with joint power control and user pairing addresses the problem of degraded uplink user fairness due to cross-cell interference in NOMA uplink and improves user fairness. In the power control section, by decoupling power control from user pairing, the WOA algorithm is proposed in the statistical channel state scenario to solve the nonconvex optimization problem of intra-user pair fairness; in the user pairing section, the PTS algorithm is proposed to introduce randomness into the algorithm to improve the algorithm’s global search performance, solve the local optimum problem of integer programming, and improve inter-user pair fairness. Simulation results show that relative to the α-fairness comparison algorithm, the algorithm in this paper can improve fairness by about 5% under different interfering user densities, cell coverage radius, and tiny area transmit power.
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Barollet, Théo, Claude Brisson, and Quentin Rendu. "Pairgoth: A Modern and Flexible Software for Efficient Go Tournament Organization." Journal of Go Studies 18, no. 2 (December 2024): 51–70. https://doi.org/10.62578/094422.
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Pairing players during a Go tournament is a complex task. One must register the players, pair them using a pairing system, gather the results and display the information to the players. Several standalone programs offer these functionalities, however they are often game-specific and maintained and developed by a single person. The pairing itself is non-trivial, because of different pairing systems and of many parameters influencing them. This creates challenges for an intuitive user interface which can be used by non-experts tournament organizers. In this article, Pairgoth is presented, a new pairing software inspired from Opengotha, a mainstream Go pairing software heavily used in Europe. Several improvements have been added to the pairing algorithm, which has also been made more generic. New pairing systems can easily be implemented in Pairgoth. Although initially designed for Go, it can easily be used for other games such as Chess, Shogi or Scrabble. Pairgoth consists of a pairing engine coupled with a web-based user interface. This allows management of the tournament from several machines, including smartphones. It already supports Swiss and MacMahon pairing systems, while more options are currently under development (Round-Robin, accelerated Swiss, Amalfi, …). Pairgoth was tested in real conditions at the international Grenoble tournament (TIGGRE 2024, 5 rounds Mac-Mahon tournament with top group and super top-group, 158 players from 29k to 7d) and at international Paris tournament (51st TIP, 6 rounds Mac-Mahon tournament with top-group, 160 players from 30k to 8d). Pairgoth was also successfully used during the 2024 European Go Congress in Toulouse, where nearly a thousand players participated. It was used for the prestigious main tournament as well as the majority of the side tournaments. It was recently used in the 2024 KPMC edition, making Pairgoth used in several countries. On top of presenting Pairgoth, this article also tackles challenges encountered in pairing engines such as deterministic randomness, non-uniqueness of pairings, and the computation of fair standing criteria.
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Wang, Jie, Chen Xu, and XiaoHu You. "Research on user pairing algorithm for LTE femtocell uplink." Science China Information Sciences 57, no. 8 (June 11, 2014): 1–9. http://dx.doi.org/10.1007/s11432-014-5120-x.
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Sasibhushan Rao Chanthati. "A segmented approach to encouragement of entrepreneurship using data science." World Journal of Advanced Engineering Technology and Sciences 12, no. 2 (July 30, 2024): 584–605. http://dx.doi.org/10.30574/wjaets.2024.12.2.0330.
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In the dynamic landscape of entrepreneurship, where opportunities abound and innovation thrives, Entrepreneurship: Navigating the Future with Data Science and AI" presents a groundbreaking approach to cultivating and empowering the next generation of business leaders. Authored with a comprehensive understanding of the intersection between technology and entrepreneurial endeavors, this paper offers a segmented approach that delves into the realms of data science, artificial intelligence, audience nurturing, and emerging trends. In employed and self-employed worlds, emphasizing a paradigm shift towards discussing opportunities rather than individuals. The core premise revolves around leveraging artificial intelligence, data-driven marketing, and audience nurturing as pivotal tools for fostering entrepreneurship. The paper introduces a novel segmented model, markets, societies, and political landscapes by strategically promoting entrepreneurship. Drawing on the computational power of data science, statistical methods, and computer science algorithms, the book advocates for the analysis of diverse and unstructured datasets to encourage risk-taking and entrepreneurial activities, particularly among students. The segmented model identifies and supports small risk-takers, utilizing specific data points sourced with consent from interested students, government schemes, private initiatives, and entrepreneurial supporting businesses. As the narrative unfolds, readers are guided through the intricacies of implementing this segmented approach, involving industry experts, instructors, and mentors. The paper proposes few concepts on 'entrepreneurship,' any one can build a user-friendly ecosystem designed to connect entrepreneurs, investors, and trainers seamlessly. Key features include user segmentation, a resource hub, networking platforms, business counseling integration, and events and webinars calendar, among others. The significance of artificial intelligence technologies is thoroughly explored, with a focus on resource acquisition, opportunity recognition, product development, organization creation, growth, and commercialization. Practical applications of AI in online communication, prototyping, and mentorship further underscore the transformative role of technology in the entrepreneurial journey. The latter part of the paper introduces a proposed algorithm for connecting startups with potential investors, emphasizing the importance of factors like industry alignment, business stage, investment preferences, and expertise. The algorithm is presented in Python, providing a tangible and implementable solution for fostering successful collaborations. A noteworthy addition to the narrative is the integration of machine learning in the matchmaking process. In this paper we will discuss the machine learning model to predict compatibility scores, showcasing a more dynamic and data-driven approach to pairing startups with investors. The step-by-step guide includes the generation of synthetic data, training the ML model, and using predictions to match startups with investors. Entrepreneurship serves as a comprehensive guide for aspiring entrepreneurs, seasoned business leaders, and anyone intrigued by the transformative power of data science and artificial intelligence in shaping the future of entrepreneurship. It invites readers to embrace innovation, leverage technology, and navigate the complexities of the business landscape with strategic insight, ultimately contributing to the growth and success of ventures in the evolving entrepreneurial ecosystem.
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LIU, Wei, Wu-yang JIANG, Hanwen LUO, and Ming DING. "A Novel User Pairing Algorithm for Uplink Virtual MIMO Systems." IEICE Transactions on Communications E95.B, no. 7 (2012): 2485–88. http://dx.doi.org/10.1587/transcom.e95.b.2485.
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Riad, Mai A., Osama El-Ghandour, and Ahmed Abd El-Haleem. "Joint User-Slice Pairing and Association Framework Based on H-NOMA in RAN Slicing." Sensors 22, no. 19 (September 27, 2022): 7343. http://dx.doi.org/10.3390/s22197343.
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Multiservice cellular in Radio Access Network (RAN) Slicing has recently attained huge interest in enhancing isolation and flexibility. However, RAN slicing in heterogeneous networks (HetNet) architecture is not adequately explored. This study proposes a pairing-network slicing (NS) approach for Multiservice RAN that cares about quality of service (QoS), baseband resources, capacities of wireless fronthaul and backhaul links, and isolation. This intriguing approach helps address the increased need for mobile network traffic produced by a range of devices with various QoS requirements, including improved dependability, ultra-reliability low-latency communications (uRLLC), and enhanced broadband Mobile Services (eMBB). Our study displays a unique RAN slicing framework for user equipment (UE) for joint user-association. Multicell non-orthogonal multiple access (NOMA)-based resource allocation across 5G HetNet under successive interference cancelation (SIC) is seen to achieve the best performance. Joint user-slice pairing and association are optimization problems to maximize eMBB UE data rates while fulfilling uRLLC latency and reliability criteria. This is accomplished by guaranteeing the inter- and intra-isolation property of slicing to eliminate interferences between eMBB and uRLLC slices. We presented the UE-slice association (U-S. A) algorithm as a one-to-many matching game to create a stable connection between UE and one of the base stations (BSs). Next, we use the UE-slice pairing (U-S. P) algorithm to find stable uRLLC-eMBB pairs that coexist on the same spectrum. Numerical findings and performance analyses of the submitted association and pairing technique show they can all be RAN slicing criteria. We prove that the proposed algorithm optimizes system throughput while decreasing uRLLC latency by associating and pairing every uRLLC user in mini slots.
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Puppala, Narendra, and Sandip Sen. "Evolving Cooperative Groups Using Shared Memory." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 6 (December 20, 1999): 457–61. http://dx.doi.org/10.20965/jaciii.1999.p0457.
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We present a coevolutionary approach to generating behavioral strategies for cooperating agent groups. We coevolve agent behavior with genetic algorithms (GAs), where one GA population is evolved per individual in the cooperative group. Groups are evaluated by pairing strategies from each population and the best strategy pairs are stored together in shared memory. To evaluate a strategy from one population, it is paired sequentially with strategies from the other population stored in shared memory. The maximum evaluation from all such pairings is used to evaluate the strategy. A pair is stored in shared memory if we encounter at least one pair previously stored there with a lower fitness value. We evaluate our approach using an asymmetric room painting domain with two agents - a whitewasher and a painter. Shared memory proved superior to random pairing in consistently generating optimal behavior patterns.
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Sugiyama, Masaki, Aohan Li, Zengchao Duan, Makoto Naruse, and Mikio Hasegawa. "BER Minimization by User Pairing in Downlink NOMA Using Laser Chaos Decision-Maker." Electronics 11, no. 9 (April 30, 2022): 1452. http://dx.doi.org/10.3390/electronics11091452.
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In next-generation wireless communication systems, non-orthogonal multiple access (NOMA) has been recognized as essential technology for improving the spectrum efficiency. NOMA allows multiple users transmit data using the same resource block simultaneously with proper user pairing. Most of the pairing schemes, however, require prior information, such as location information of the users, leading to difficulties in realizing prompt user pairing. To realize real-time operations without prior information in NOMA, a bandit algorithm using chaotically oscillating time series, which we refer to as the laser chaos decision-maker, was demonstrated. However, this scheme did not consider the detailed communication processes, e.g., modulation, error correction code, etc. In this study, in order to adapt the laser chaos decision-maker to real communication systems, we propose a user pairing scheme based on acknowledgment (ACK) and negative acknowledgment (NACK) information considering detailed communication channels. Furthermore, based on the insights gained by the analysis of parameter dependencies, we introduce an adaptive pairing method to minimize the bit error rate of the NOMA system under study. The numerical results show that the proposed method achieves superior performances than the traditional using pairing schemes, i.e., Conventional-NOMA pairing scheme (C-NOMA) and Unified Channel Gain Difference pairing scheme (UCGD-NOMA), and ϵ-greedy-based user pairing scheme. As the cell radius of the NOMA system gets smaller, the superior on the BER of our proposed scheme gets bigger. Specifically, our proposed scheme can decrease the BER from 10−1 to 10−5 compared to the conventional schemes when the cell radius is 400 m.
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Singh, Manpreet, and Preeti Gulati. "Implementation of User-Pairing Algorithm by using Heuristic Technique for OFDMA." IARJSET 2, no. 12 (December 20, 2015): 140–42. http://dx.doi.org/10.17148/iarjset.2015.21226.
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Xia Chen, Honglin Hu, Haifeng Wang, Hsiao-hwa Chen, and M. Guizani. "Double proportional fair user pairing algorithm for uplink virtual MIMO systems." IEEE Transactions on Wireless Communications 7, no. 7 (July 2008): 2425–29. http://dx.doi.org/10.1109/twc.2008.061091.
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Savima, K., and M. V. Srinath. "Developing an Encryption Method with a Comparative Algorithmic Approach of Lightweight Block Ciphers for Improved Security Performance in IoT Devices: PRESOPT." Indian Journal Of Science And Technology 17, no. 47 (December 28, 2024): 4999–5009. https://doi.org/10.17485/ijst/v17i47.3774.
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Background: This study compares encryption-decryption algorithms, and a new framework called PRESOPT, which is improved upon the Present algorithm, a lightweight block cipher. This article examines the security and performance of DES, ROT-13, and the current framework for the PRESOPT implementation outcome. Objectives: PRESOPT is developed to enhance and surpass the safety operation of prevailing algorithms with complementary capabilities to make IoT devices more resilient to cyberattacks. The PRESOPT algorithm is designed to optimize both time and security. Method: The algorithm uses DES with a 64-bit block size, a key length of 56 bits, and 16 operation rounds. On the other hand, the existing method uses a set of procedures utilizing Near Feel Communication (NFC) based pairing that works with Internet of Things devices, whereas ROT-13 is an improvement on the Ceaser cipher. Python is used to implement the simulations for the suggested study, and the outcomes are successfully procured. Findings : The output shows Elapsed Time 0.00281709 seconds that it handles block ciphers efficiently. Novelty: The proposed PRESOPT algorithm improves the present algorithm's security performance and gives an add-on capability to secure the Internet of Things from cyberattacks. Keywords: IoT (Internet of Things), ROT-13 (Rotation-13), Cipher, Encryption, Decryption
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Maraqa, Omar, Umair F. Siddiqi, Saad Al-Ahmadi, and Sadiq M. Sait. "On the Achievable Max-Min User Rates in Multi-Carrier Centralized NOMA-VLC Networks." Sensors 21, no. 11 (May 26, 2021): 3705. http://dx.doi.org/10.3390/s21113705.
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Visible light communications (VLC) is gaining interest as one of the enablers of short-distance, high-data-rate applications, in future beyond 5G networks. Moreover, non-orthogonal multiple-access (NOMA)-enabled schemes have recently emerged as a promising multiple-access scheme for these networks that would allow realization of the target spectral efficiency and user fairness requirements. The integration of NOMA in the widely adopted orthogonal frequency-division multiplexing (OFDM)-based VLC networks would require an optimal resource allocation for the pair or the cluster of users sharing the same subcarrier(s). In this paper, the max-min rate of a multi-cell indoor centralized VLC network is maximized through optimizing user pairing, subcarrier allocation, and power allocation. The joint complex optimization problem is tackled using a low-complexity solution. At first, the user pairing is assumed to follow the divide-and-next-largest-difference user-pairing algorithm (D-NLUPA) that can ensure fairness among the different clusters. Then, subcarrier allocation and power allocation are solved iteratively through both the Simulated Annealing (SA) meta-heuristic algorithm and the bisection method. The obtained results quantify the achievable max-min user rates for the different relevant variants of NOMA-enabled schemes and shed new light on both the performance and design of multi-user multi-carrier NOMA-enabled centralized VLC networks.
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Liang, Wei, Zhiguo Ding, Yonghui Li, and Lingyang Song. "User Pairing for Downlink Non-Orthogonal Multiple Access Networks Using Matching Algorithm." IEEE Transactions on Communications 65, no. 12 (December 2017): 5319–32. http://dx.doi.org/10.1109/tcomm.2017.2744640.
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Karthik, A., and Neelesh B. Mehta. "An Opportunistic, Fast, and Distributed Subchannel and User-Pairing Algorithm for OFDMA." IEEE Transactions on Communications 60, no. 3 (March 2012): 767–78. http://dx.doi.org/10.1109/tcomm.2012.12.110204.
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Stinner, Florian, David Gorgis, Alexander Kümpel, and Dirk Müller. "Automatic detection of control loops in existing buildings." Journal of Physics: Conference Series 2600, no. 8 (November 1, 2023): 082013. http://dx.doi.org/10.1088/1742-6596/2600/8/082013.
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Abstract Improving control loops in buildings is cost-intensive due to the need of expert time. With well structured data, the development of data-driven algorithms is promising to minimize the required time. But data stream names across buildings do not follow a uniform naming schema. We developed a method to identify temperature control loops (sensors and set points) based on data stream names. The methodology starts with narrowing down to three potential sensors per set point using string distances and their combination, before estimating the probability that the first sensor is the correct paired sensor to the set point. We used data from three buildings: A large data set composed of over 12,000 translated data streams for the development and adjustment of the methodology and two smaller data sets for the verification of the transferability of the developed method. The results are strongly dependent on data stream name structure. The results indicate that within the test data set, the pairing sensor to a set point can be automatically limited to three or five sensor candidates, and the algorithm can identify a high number of control loops. For the transfer to the two validation sets, the limitation of sensor candidates is still possible, but identifying pairings and control loops is difficult.
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Wang, Zhenyu, Honglin Hu, Boqi Jia, and Tianheng Xu. "A windowing-based joint user pairing and resource allocation algorithm for V-MIMO systems." Computer Communications 144 (August 2019): 1–7. http://dx.doi.org/10.1016/j.comcom.2019.05.004.
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Zhang, Qianfeng, Kang An, Xiaojuan Yan, Hongxia Xi, and Yuli Wang. "User Pairing for Delay-Limited NOMA-Based Satellite Networks with Deep Reinforcement Learning." Sensors 23, no. 16 (August 9, 2023): 7062. http://dx.doi.org/10.3390/s23167062.
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In this paper, we investigate a user pairing problem in power domain non-orthogonal multiple access (NOMA) scheme-aided satellite networks. In the considered scenario, different satellite applications are assumed with various delay quality-of-service (QoS) requirements, and the concept of effective capacity is employed to characterize the effect of delay QoS limitations on achieved performance. Based on this, our objective was to select users to form a NOMA user pair and utilize resource efficiently. To this end, a power allocation coefficient was firstly obtained by ensuring that the achieved capacity of users with sensitive delay QoS requirements was not less than that achieved with an orthogonal multiple access (OMA) scheme. Then, considering that user selection in a delay-limited NOMA-based satellite network is intractable and non-convex, a deep reinforcement learning (DRL) algorithm was employed for dynamic user selection. Specifically, channel conditions and delay QoS requirements of users were carefully selected as state, and a DRL algorithm was used to search for the optimal user who could achieve the maximum performance with the power allocation factor, to pair with the delay QoS-sensitive user to form a NOMA user pair for each state. Simulation results are provided to demonstrate that the proposed DRL-based user selection scheme can output the optimal action in each time slot and, thus, provide superior performance than that achieved with a random selection strategy and OMA scheme.
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Greenwell, Raymond N., and Daniel E. Seabold. "The Stable Pairing Problem." Mathematics Teacher 107, no. 6 (February 2014): 446–50. http://dx.doi.org/10.5951/mathteacher.107.6.0446.
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Bellés-Muñoz, Marta, Barry Whitehat, Jordi Baylina, Vanesa Daza, and Jose Luis Muñoz-Tapia. "Twisted Edwards Elliptic Curves for Zero-Knowledge Circuits." Mathematics 9, no. 23 (November 25, 2021): 3022. http://dx.doi.org/10.3390/math9233022.
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Circuit-based zero-knowledge proofs have arose as a solution to the implementation of privacy in blockchain applications, and to current scalability problems that blockchains suffer from. The most efficient circuit-based zero-knowledge proofs use a pairing-friendly elliptic curve to generate and validate proofs. In particular, the circuits are built connecting wires that carry elements from a large prime field, whose order is determined by the number of elements of the pairing-friendly elliptic curve. In this context, it is important to generate an inner curve using this field, because it allows to create circuits that can verify public-key cryptography primitives, such as digital signatures and encryption schemes. To this purpose, in this article, we present a deterministic algorithm for generating twisted Edwards elliptic curves defined over a given prime field. We also provide an algorithm for checking the resilience of this type of curve against most common security attacks. Additionally, we use our algorithms to generate Baby Jubjub, a curve that can be used to implement elliptic-curve cryptography in circuits that can be validated in the Ethereum blockchain.
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Wan, Liang-Tian, Lu-Tao Liu, Wei-Jian Si, and Zuo-Xi Tian. "Joint Estimation of 2D-DOA and Frequency Based on Space-Time Matrix and Conformal Array." Scientific World Journal 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/463828.
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Each element in the conformal array has a different pattern, which leads to the performance deterioration of the conventional high resolution direction-of-arrival (DOA) algorithms. In this paper, a joint frequency and two-dimension DOA (2D-DOA) estimation algorithm for conformal array are proposed. The delay correlation function is used to suppress noise. Both spatial and time sampling are utilized to construct the spatial-time matrix. The frequency and 2D-DOA estimation are accomplished based on parallel factor (PARAFAC) analysis without spectral peak searching and parameter pairing. The proposed algorithm needs only four guiding elements with precise positions to estimate frequency and 2D-DOA. Other instrumental elements can be arranged flexibly on the surface of the carrier. Simulation results demonstrate the effectiveness of the proposed algorithm.
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Chen, Liang, Lin Ma, and Yubin Xu. "Proportional Fairness-Based User Pairing and Power Allocation Algorithm for Non-Orthogonal Multiple Access System." IEEE Access 7 (2019): 19602–15. http://dx.doi.org/10.1109/access.2019.2896181.
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N. F., Mohamed, Mohamed N. A., Mohamed N. H., and Subani N. "Comparison of two hybrid algorithms on incorporated aircraft routing and crew pairing problems." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 3 (June 1, 2020): 1665. http://dx.doi.org/10.11591/ijeecs.v18.i3.pp1665-1672.
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<span>In airline operations planning, a sequential method is traditionally used in airline system. In airline systems, minimizing the costs is important as they want to get the highest profits. The aircraft routing problem is solved first, and then pursued by crew pairing problem. The solutions are suboptimal in some cases, so we incorporate aircraft routing and crew pairing problems into one mathematical model to get an exact solution. Before we solve the integrated aircraft routing and crew pairing problem, we need to get the aircraft routes (AR) and crew pairs (CP). In this study, we suggested using genetic algorithm (GA) to develop a set of AR and CP. By using the generated AR and CP, we tackle the integrated aircraft and crew pairing problems using two suggested techniques, Integer Linear Programming (ILP) and Particle Swarm Optimization (PSO). Computational results show that GA's executed of AR and CP and then solved by ILP obtained the greatest results among all the methods suggested.</span>
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Emiliani, Ramon D., Gabriel Chartrand, Edward Son, Sophie A. Pawlowski, Selvan Rajakesari, Alexandre Cengarle-Samak, Jeremi Lavoie, Simon Ducharme, and David Roberge. "NIRL-08 AUTOMATED LONGITUDINAL TRACKING OF BRAIN METASTASES INTEGRATED IN A USER-ORIENTED SOFTWARE." Neuro-Oncology Advances 6, Supplement_1 (August 2024): i21. http://dx.doi.org/10.1093/noajnl/vdae090.069.
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Abstract The burden of detection and segmentation of brain metastases (BM) for treatment planning and response assessment has been found to be alleviated by machine learning methods. However, tracking individual lesions over time remains tedious and would benefit from automated assistance for complex cases. We developed a software solution combining an AI-based BM segmentation method with an automated pairing algorithm allowing to track BM across longitudinal scans. The proposed tracking method comprises two steps: identifying lesions in each scan and pairing identified findings across scans. Identification and segmentation of BM is done with our previously published neural network based algorithm. Tracking of BM is achieved by progressively assigning a lesion ID to individual findings. For each series, individual findings are co-registered using image registration to a reference series which defines the initial set of lesions. A matching function then computes a score for each possible finding-lesion pair based on diameter similarity and inter-centroid distance. Findings from highest scoring pairs are sequentially assigned their matched lesion ID, while pairs scoring under a given threshold are assigned a new lesion ID. Series are processed as such until all findings are dispatched. Assignment accuracy was assessed using adjusted rand index (ARI) on a synthetic noisy dataset simulating registration error and misdetections. Findings from 10 to 20 lesions on 5 series of dimension 100 mm per side were randomly generated for 100 synthetic patients each. With a simulated registration error range of 0-2 deg and 0-5mm, the average per patient ARI was 0.94 +/- 0.05, while an error range of 0-4 deg and 0-10mm lowered ARI to 0.87 +/-0.08. Results support the validity of our software solution for automated detection and longitudinal tracking of BM, which can alleviate the burden of follow-ups in the context of stereotactic radiosurgery.
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He, J., and Z. Tang. "Low‐complexity user pairing and power allocation algorithm for 5G cellular network non‐orthogonal multiple access." Electronics Letters 53, no. 9 (April 2017): 626–27. http://dx.doi.org/10.1049/el.2016.4190.
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Rui, Y., H. Hu, H. Yi, and H. H. Chen. "Robust user pairing algorithm under channel estimation errors for uplink virtual multiple-input multiple-output systems." IET Communications 6, no. 3 (2012): 318. http://dx.doi.org/10.1049/iet-com.2010.0972.
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