Journal articles on the topic 'Channel state information'

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1

Shimray, Somipam Ronra, and Chennupati K. Ramaiah. "Information Channel Preference in Seeking Cultural Heritage Information A Study." DESIDOC Journal of Library & Information Technology 42, no. 2 (February 28, 2022): 98–104. http://dx.doi.org/10.14429/djlit.42.2.17605.

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Information is accessed through a variety of routes, one of which is an information channel. The formal channel follows a structured path, whereas the informal channel takes a more unstructured path. This study primarily looks into the channel(s) used for seeking cultural heritage information among the Tangkhul tribe from Manipur state, India and also checked the significant change between studied variables and demographic variables. This study employed a stratified random sampling method to draw the sample. The study used a survey method and a structured questionnaire tool for data collection. The questionnaire comprises respondents’ demographic profiles and 13 items on channels preferred for seeking cultural heritage information. Analysis present that the most prevalent strategy for accessing cultural heritage knowledge was determined to be “elderly people in the community” with a mean score of 3.85. Furthermore, factor analysis identifies two types of channels: informal and formal. And current residency (p-value=0.044) and family annual income (p-value=0.043) influence channel choice for accessing information, with those living in Manipur state preferring official channels and those earning INR 9,00,001 annually or more preferring informal channels.
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2

Tulay, Halit Bugra, and Can Emre Koksal. "Road State Inference via Channel State Information." IEEE Transactions on Vehicular Technology 72, no. 7 (July 2023): 8329–41. http://dx.doi.org/10.1109/tvt.2023.3244085.

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3

Li, Ying, Yi Jun Zhu, Lan Ma, and Yao Zhu. "On the Capacity of MIMO Channels with Outdated Channel State Information." Advanced Materials Research 204-210 (February 2011): 2053–56. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.2053.

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A Multiple-input multiple-output (MIMO) time-varying flat fading channel is considered. The transmitter obtained the channel state information (CSI) relying on the reciprocity principle or by the feedback from the receiver. Thus, channel state information at the transmitter (CSIT) is outdated due to the delay between the estimation of the channel and the transmission of the data. In order to achieve the maximum channel capacity, the transmitter linearly precoded the signal before transmission based on the outdated CSIT. Under the assumptions of wide-sense stationary uncorrelated scattering Rayleigh fading channels and Jake’s model, the instantaneous mutual information and ergodic capacity is derived for MIMO channels with outdated CSIT. The information outage probability of MIMO channel with outdated CSIT is also presented.
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4

Dai, Bin, A. Vinck, Yuan Luo, and Xiaohu Tang. "Wiretap Channel with Action-Dependent Channel State Information." Entropy 15, no. 2 (January 28, 2013): 445–73. http://dx.doi.org/10.3390/e15020445.

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5

Yin, Xinxing, Liang Pang, and Zhi Xue. "Wiretap Channel with Rate-Limited Channel State Information." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/643265.

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We revisit a channel coding problem where the channel state information (CSI) is rate-limited (or coded) and available to the channel encoder. A wiretapper is added into this model, and the confidential message is intended only for the legal receiver and should be kept from being eavesdropped by the wiretapper. Equivocation analysis is provided to evaluate the level of information leakage to the wiretapper. We characterize an achievable rate-equivocation region as well as an outer bound for this security model. To achieve the rate-equivocation triples, we propose an efficient coding scheme, in which the coded CSI serves as the CSI for the channel encoder, based onGel’fand and Pinsker’s codingandWyner’s random coding. Furthermore, an example of Gaussian wiretap channel with rate-limited CSI is presented, of which a lower bound on the secrecy capacity is obtained. By simulation, we find there exists an optimal rate of the coded CSI at which the biggest secrecy transmission rate of the Gaussian case is achieved.
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6

Sutivong, A., M. Chiang, T. M. Cover, and Y. H. Kim. "Channel Capacity and State Estimation for State-Dependent Gaussian Channels." IEEE Transactions on Information Theory 51, no. 4 (April 2005): 1486–95. http://dx.doi.org/10.1109/tit.2005.844108.

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7

Nguyen, Gam D., Sastry Kompella, Clement Kam, and Jeffrey E. Wieselthier. "Information freshness over a Markov channel: The effect of channel state information." Ad Hoc Networks 86 (April 2019): 63–71. http://dx.doi.org/10.1016/j.adhoc.2018.10.010.

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8

Tan, Bo, Qingchao Chen, Kevin Chetty, Karl Woodbridge, Wenda Li, and Robert Piechocki. "Exploiting WiFi Channel State Information for Residential Healthcare Informatics." IEEE Communications Magazine 56, no. 5 (May 2018): 130–37. http://dx.doi.org/10.1109/mcom.2018.1700064.

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9

Tadayon, Navid, Muhammed Tahsin Rahman, Shuo Han, Shahrokh Valaee, and Wei Yu. "Decimeter Ranging With Channel State Information." IEEE Transactions on Wireless Communications 18, no. 7 (July 2019): 3453–68. http://dx.doi.org/10.1109/twc.2019.2914194.

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10

Zhan, Jiening, and Michael Gastpar. "Functional Forwarding of Channel State Information." IEEE Transactions on Information Theory 60, no. 2 (February 2014): 1008–18. http://dx.doi.org/10.1109/tit.2013.2291002.

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11

Ma, Yongsen, Gang Zhou, and Shuangquan Wang. "WiFi Sensing with Channel State Information." ACM Computing Surveys 52, no. 3 (July 27, 2019): 1–36. http://dx.doi.org/10.1145/3310194.

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12

Chia, Yeow-Khiang, and Abbas El Gamal. "Wiretap Channel With Causal State Information." IEEE Transactions on Information Theory 58, no. 5 (May 2012): 2838–49. http://dx.doi.org/10.1109/tit.2011.2181329.

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13

Zhang, Lili, Jinhua Jiang, and Shuguang Cui. "Gaussian Interference Channel with State Information." IEEE Transactions on Wireless Communications 12, no. 8 (August 2013): 4058–71. http://dx.doi.org/10.1109/twc.2013.052213.121598.

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14

DORLAS, T. C., and C. MORGAN. "CALCULATING A MAXIMIZER FOR QUANTUM MUTUAL INFORMATION." International Journal of Quantum Information 06, supp01 (July 2008): 745–50. http://dx.doi.org/10.1142/s0219749908004055.

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We obtain a maximizer for the quantum mutual information for classical information sent over the quantum amplitude damping channel. This is achieved by limiting the ensemble of input states to antipodal states, in the calculation of the product state capacity for the channel. We also consider the product state capacity of a convex combination of two memoryless channels and demonstrate in particular that it is in general not given by the minimum of the capacities of the respective memoryless channels.
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15

Rosenzweig, A., Y. Steinberg, and S. Shamai. "On Channels With Partial Channel State Information at the Transmitter." IEEE Transactions on Information Theory 51, no. 5 (May 2005): 1817–30. http://dx.doi.org/10.1109/tit.2005.846422.

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16

Caire, G., and S. Shamai. "On the capacity of some channels with channel state information." IEEE Transactions on Information Theory 45, no. 6 (1999): 2007–19. http://dx.doi.org/10.1109/18.782125.

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17

Bloch, Matthieu R., and J. Nicholas Laneman. "Exploiting Partial Channel State Information for Secrecy over Wireless Channels." IEEE Journal on Selected Areas in Communications 31, no. 9 (September 2013): 1840–49. http://dx.doi.org/10.1109/jsac.2013.130916.

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18

Akhbari, B., M. R. Aref, and R. Khosravi-Farsani. "Cooperative relay broadcast channels with partial causal channel state information." IET Communications 5, no. 6 (April 15, 2011): 760–74. http://dx.doi.org/10.1049/iet-com.2010.0093.

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19

Kramer, Gerhard. "Information Rates for Channels with Fading, Side Information and Adaptive Codewords." Entropy 25, no. 5 (April 27, 2023): 728. http://dx.doi.org/10.3390/e25050728.

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Generalized mutual information (GMI) is used to compute achievable rates for fading channels with various types of channel state information at the transmitter (CSIT) and receiver (CSIR). The GMI is based on variations of auxiliary channel models with additive white Gaussian noise (AWGN) and circularly-symmetric complex Gaussian inputs. One variation uses reverse channel models with minimum mean square error (MMSE) estimates that give the largest rates but are challenging to optimize. A second variation uses forward channel models with linear MMSE estimates that are easier to optimize. Both model classes are applied to channels where the receiver is unaware of the CSIT and for which adaptive codewords achieve capacity. The forward model inputs are chosen as linear functions of the adaptive codeword’s entries to simplify the analysis. For scalar channels, the maximum GMI is then achieved by a conventional codebook, where the amplitude and phase of each channel symbol are modified based on the CSIT. The GMI increases by partitioning the channel output alphabet and using a different auxiliary model for each partition subset. The partitioning also helps to determine the capacity scaling at high and low signal-to-noise ratios. A class of power control policies is described for partial CSIR, including a MMSE policy for full CSIT. Several examples of fading channels with AWGN illustrate the theory, focusing on on-off fading and Rayleigh fading. The capacity results generalize to block fading channels with in-block feedback, including capacity expressions in terms of mutual and directed information.
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20

Rosgen, Bill. "Computational distinguishability of degradable and antidegradable channels." Quantum Information and Computation 10, no. 9&10 (September 2010): 735–46. http://dx.doi.org/10.26421/qic10.9-10-2.

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A channel is degradable if there exists a second channel that maps the output state of the channel to the environment state. These channels satisfy the property that the output state contains more information about the input than the environment does. A complementary class of channels is the antidegradable channels, which admit channels that map the environment state to the output state of the channel. In this paper we show that the computational problem of distinguishing two channels remains -complete when restricted to these classes of channels. This is shown using a construction of Cubitt, Ruskai, and Smith that embeds any channel into a degradable channel, and a related construction for the case of antidegradable channels.
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21

Falaye, Babatunde James, Guo-Hua Sun, Oscar Camacho-Nieto, and Shi-Hai Dong. "JRSP of three-particle state via three tripartite GHZ class in quantum noisy channels." International Journal of Quantum Information 14, no. 07 (October 2016): 1650034. http://dx.doi.org/10.1142/s0219749916500349.

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We present a scheme for joint remote state preparation (JRSP) of three-particle state via three tripartite Greenberger–Horne–Zeilinger (GHZ) entangled states as the quantum channel linking the parties. We use eight-qubit mutually orthogonal basis vector as measurement point of departure. The likelihood of success for this scheme has been found to be [Formula: see text]. However, by putting some special cases into consideration, the chances can be ameliorated to [Formula: see text] and 1. The effects of amplitude-damping noise, phase-damping noise and depolarizing noise on this scheme have been scrutinized and the analytical derivations of fidelities for the quantum noisy channels have been presented. We found that for [Formula: see text], the states conveyed through depolarizing channel lose more information than phase-damping channel while the information loss through amplitude damping channel is most minimal.
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22

Alekseev, V. M. "COVERT CHANNELS OF INFORMATION TRANSFER." World of Transport and Transportation 15, no. 4 (August 28, 2017): 50–56. http://dx.doi.org/10.30932/1992-3252-2017-15-4-5.

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For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version).ABSTRACT The article deals with the organization of hidden channels of information transfer with the help of embedded agents in operating systems. The current state of research in this field of science, comparison with the world level, shows that there are no theoretical developments of hidden channel analyzers, as well as software and hardware implementation of their models. The author offers his approach to creating covert channel analyzers based on methods of self-organization, as well as an algorithm for network operations that allows to perform the functions of entanglement of packets in order to destroy the process of transmitting information over hidden channels. Keywords: information channels, corporate network, hidden channel, analyzer, secret agent, packet, perceptron.
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23

Jiang, Y., W. W. Hager, and J. Li. "Tunable Channel Decomposition for MIMO Communications Using Channel State Information." IEEE Transactions on Signal Processing 54, no. 11 (November 2006): 4405–18. http://dx.doi.org/10.1109/tsp.2006.880233.

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24

Pereg, Uzi, Christian Deppe, and Holger Boche. "Quantum Channel State Masking." IEEE Transactions on Information Theory 67, no. 4 (April 2021): 2245–68. http://dx.doi.org/10.1109/tit.2021.3050529.

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25

Roh, J. C., and B. D. Rao. "Multiple antenna channels with partial channel state information at the transmitter." IEEE Transactions on Wireless Communications 3, no. 2 (March 2004): 677–88. http://dx.doi.org/10.1109/twc.2003.821144.

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26

Liu, Jialing, Nicola Elia, and Sekhar Tatikonda. "Capacity-Achieving Feedback Schemes for Gaussian Finite-State Markov Channels With Channel State Information." IEEE Transactions on Information Theory 61, no. 7 (July 2015): 3632–50. http://dx.doi.org/10.1109/tit.2015.2437380.

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27

Weber, T., A. Sklavos, and M. Meurer. "Imperfect channel-state information in MIMO transmission." IEEE Transactions on Communications 54, no. 3 (March 2006): 543–52. http://dx.doi.org/10.1109/tcomm.2006.869783.

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28

Che, Rongjie, and Honglong Chen. "Channel State Information Based Indoor Fingerprinting Localization." Sensors 23, no. 13 (June 22, 2023): 5830. http://dx.doi.org/10.3390/s23135830.

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Indoor localization is one of the key techniques for location-based services (LBSs), which play a significant role in applications in confined spaces, such as tunnels and mines. To achieve indoor localization in confined spaces, the channel state information (CSI) of WiFi can be selected as a feature to distinguish locations due to its fine-grained characteristics compared with the received signal strength (RSS). In this paper, two indoor localization approaches based on CSI fingerprinting were designed: amplitude-of-CSI-based indoor fingerprinting localization (AmpFi) and full-dimensional CSI-based indoor fingerprinting localization (FuFi). AmpFi adopts the amplitude of the CSI as the localization fingerprint in the offline phase, and in the online phase, the improved weighted K-nearest neighbor (IWKNN) is proposed to estimate the unknown locations. Based on AmpFi, FuFi is proposed, which considers all of the subcarriers in the MIMO system as the independent features and adopts the normalized amplitudes of the full-dimensional subcarriers as the fingerprint. AmpFi and FuFi were implemented on a commercial network interface card (NIC), where FuFi outperformed several other typical fingerprinting-based indoor localization approaches.
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29

Adhikari, Satyabrata, Indranil Chakrabarty, and Pankaj Agrawal. "Probabilistic secret sharing through noise quantum channe." Quantum Information and Computation 12, no. 3&4 (March 2012): 253–61. http://dx.doi.org/10.26421/qic12.3-4-5.

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In a realistic situation, the secret sharing of classical or quantum information will involve the transmission of this information through noisy channels. We consider a three qubit pure state. This state becomes a mixed-state when the qubits are distributed over noisy channels. We focus on a specific noisy channel, the phase-damping channel. We propose a protocol for secret sharing of classical information with this and related noisy channels. This protocol can also be thought of as cooperative superdense coding. We also discuss other noisy channels to examine the possibility of secret sharing of classical information.
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Maddah-Ali, Mohammad Ali, and David Tse. "Completely Stale Transmitter Channel State Information is Still Very Useful." IEEE Transactions on Information Theory 58, no. 7 (July 2012): 4418–31. http://dx.doi.org/10.1109/tit.2012.2193116.

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31

Okandeji, Alexander Akpofure. "Multicast Beamforming for SWIPT in MISO Full-Duplex Systems." Nigerian Journal of Technological Research 16, no. 1 (March 9, 2021): 26–33. http://dx.doi.org/10.4314/njtr.v16i1.4.

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This paper considers the multicast transmit beamforming and receive power splitting problem for sum transmit power minimization for a simultaneous wireless information and power transfer (SWIPT) system subject to signal-to-interference-plus-noise ratio (SINR), and energy harvesting constraints at the receiver. In particular, we consider the case of perfect and imperfect channel state information (CSI) at the base station. Using semidefinite relaxation (SDR) technique, we obtain solution to the problem with imperfect channel state information of the self-interfering channels. Keywords: Simultaneous wireless information and power transfer, channel state information, Energy harvesting, semidefinite relaxation.
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32

Agarwal, Manish, Dongning Guo, and Michael L. Honig. "Limited-Rate Channel State Feedback for Multicarrier Block Fading Channels." IEEE Transactions on Information Theory 56, no. 12 (December 2010): 6116–32. http://dx.doi.org/10.1109/tit.2010.2080970.

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33

Draper, Stark C., Frank R. Kschischang, and Brendan Frey. "Rateless Coding for Arbitrary Channel Mixtures With Decoder Channel State Information." IEEE Transactions on Information Theory 55, no. 9 (September 2009): 4119–33. http://dx.doi.org/10.1109/tit.2009.2025577.

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34

Simoens, S., O. Munoz-Medina, J. Vidal, and A. del Coso. "On the Gaussian MIMO Relay Channel With Full Channel State Information." IEEE Transactions on Signal Processing 57, no. 9 (September 2009): 3588–99. http://dx.doi.org/10.1109/tsp.2009.2020744.

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35

Zhen, Ziyang, Ju Jiang, Zhisheng Wang, and Xinhua Wang. "Information Fusion Based Decoupling Control for Multivariable Nonlinear System." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/361581.

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A decoupling control method based on information fusion estimation for a nonlinear system is presented in the paper. For each main channel and its coupled channels of the system, according to the information fusion theorem, the estimation of the system future state is obtained by fusing the information of the desired output trajectory of the system. Furthermore, approximate optimal control rule is obtained by fusing the system future state information and the control energy soft constraint information. Then an information fusion based decoupling control (IFBDC) system is established for the nonlinear coupled multiple-input multiple-output systems. This system cannot only control every channel to track reference signals, but also control any channel to be decoupled with other channels. Finally, a robot manipulator system is given to investigate the effectiveness of the decoupling control strategy, analyze its key parameters, and analyze the computational cost. The simulation results show that the IFBDC method is characterized by adjustable decoupling degree and high control quality.
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Salehkalaibar, Sadaf, Mohammad Hossein Yassaee, Vincent Y. F. Tan, and Mehrasa Ahmadipour. "State Masking Over a Two-State Compound Channel." IEEE Transactions on Information Theory 67, no. 9 (September 2021): 5651–73. http://dx.doi.org/10.1109/tit.2021.3096646.

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37

Liu, An, Xinming Huang, Youjian Liu, Haige Xiang, and Wu Luo. "Capacity bounds of MIMO channels with asymmetric channel state information at transmitter." IEEE Communications Letters 13, no. 8 (August 2009): 564–66. http://dx.doi.org/10.1109/lcomm.2009.090991.

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38

Pastore, Adriano, Tobias Koch, and Javier Rodriguez Fonollosa. "A Rate-Splitting Approach to Fading Channels With Imperfect Channel-State Information." IEEE Transactions on Information Theory 60, no. 7 (July 2014): 4266–85. http://dx.doi.org/10.1109/tit.2014.2321567.

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39

Longoria-Gandara, O., and R. Parra-Michel. "Estimation of Correlated MIMO Channels using Partial Channel State Information and DPSS." IEEE Transactions on Wireless Communications 10, no. 11 (November 2011): 3711–19. http://dx.doi.org/10.1109/twc.2011.091411.101199.

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40

Ravindran, Niranjay, and Nihar Jindal. "Multi-User Diversity vs. Accurate Channel State Information in MIMO Downlink Channels." IEEE Transactions on Wireless Communications 11, no. 9 (September 2012): 3037–46. http://dx.doi.org/10.1109/twc.2012.071612.101350.

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41

Yuheng Huang and J. A. Ritcey. "16-qam bicm-id in fading channels with imperfect channel state information." IEEE Transactions on Wireless Communications 2, no. 5 (September 2003): 1000–1007. http://dx.doi.org/10.1109/twc.2003.817432.

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42

Lavanis, Nandita, Devendra Jalihal, Arun Pachai Kannu, and Srikrishna Bhashyam. "Finite-SNR outage analysis for MIMO channels with imperfect channel state information." Physical Communication 22 (March 2017): 58–64. http://dx.doi.org/10.1016/j.phycom.2016.12.005.

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43

Fadel Shady, Mohamed, and Aria Nosratinia. "MISO Broadcast Channel under Unequal Link Coherence Times and Channel State Information." Entropy 22, no. 9 (September 1, 2020): 976. http://dx.doi.org/10.3390/e22090976.

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The broadcast channel may experience unequal link coherence times due to a number of factors including variation in node mobility or local scattering conditions. This means the block fading model for different links may have nonidentical block length, and the channel state information for the links may also not be identical. The faster the fading and the shorter the fading block length, the more often the link needs to be trained and estimated at the receiver, and the more likely that channel state information (CSI) is stale or unavailable at the transmitter. This paper investigates a MISO broadcast channel where some receivers experience longer coherence intervals and other receivers experience shorter coherence intervals and must estimate their receive-side CSI (CSIR) frequently. We consider a variety of transmit-side CSI (CSIT) conditions for the abovementioned model, including no CSIT, delayed CSIT, or hybrid CSIT. To investigate the degrees of freedom region, we employ interference alignment and beamforming along with a product superposition that allows simultaneous but noncontaminating transmission of pilots and data to different receivers. Outer bounds employ the extremal entropy inequality as well as a bounding of the performance of a discrete, memoryless, multiuser, multilevel broadcast channel. For several cases, inner and outer bounds are established that either partially meet, or the gap diminishes with increasing coherence times.
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44

Tsibonis, V., L. Georgiadis, and L. Tassiulas. "Exploiting Wireless Channel State Information for Throughput Maximization." IEEE Transactions on Information Theory 50, no. 11 (November 2004): 2566–82. http://dx.doi.org/10.1109/tit.2004.836687.

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45

Adireddy, S., and L. Tong. "Exploiting Decentralized Channel State Information for Random Access." IEEE Transactions on Information Theory 51, no. 2 (February 2005): 537–61. http://dx.doi.org/10.1109/tit.2004.840878.

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46

Gopalan, Aditya, Constantine Caramanis, and Sanjay Shakkottai. "On Wireless Scheduling With Partial Channel-State Information." IEEE Transactions on Information Theory 58, no. 1 (January 2012): 403–20. http://dx.doi.org/10.1109/tit.2011.2169543.

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47

Khaleghi Bizaki, H., and A. Falahati. "Tomlinson–Harashima precoding with imperfect channel state information." IET Communications 2, no. 1 (2008): 151. http://dx.doi.org/10.1049/iet-com:20060697.

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48

Lan Zhang, Ying-Chang Liang, Yan Xin, and H. V. Poor. "Robust cognitive beamforming with partial channel state information." IEEE Transactions on Wireless Communications 8, no. 8 (August 2009): 4143–53. http://dx.doi.org/10.1109/twc.2009.080698.

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49

Samuel, Michael, and Michael Fitz. "Iterative Sphere Detectors for Imperfect Channel State Information." IEEE Transactions on Communications 59, no. 10 (October 2011): 2796–807. http://dx.doi.org/10.1109/tcomm.2011.081711.090448.

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50

Ye, Sigen, Rick Blum, and Leonard Cimini. "Adaptive OFDM Systems With Imperfect Channel State Information." IEEE Transactions on Wireless Communications 5, no. 10 (November 2006): 3255–65. http://dx.doi.org/10.1109/twc.2006.05004.

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