Relevant bibliographies by topics / Multi-hop MIMO Networks

Academic literature on the topic 'Multi-hop MIMO Networks'

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Published: 6 September 2023

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Journal articles on the topic "Multi-hop MIMO Networks"

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ONO, Fumie, and Kei SAKAGUCHI. "STBC MIMO Network Coding for Bi-directional Multi-Hop Relay Networks." IEICE Transactions on Communications E92-B, no. 12 (2009): 3676–82. http://dx.doi.org/10.1587/transcom.e92.b.3676.

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Smarra, F., A. D'Innocenzo, and M. D. Di Benedetto. "Fault Tolerant Stabilizability of MIMO Multi-Hop Control Networks." IFAC Proceedings Volumes 45, no. 26 (September 2012): 79–84. http://dx.doi.org/10.3182/20120914-2-us-4030.00048.

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Zeng, Huacheng, Yi Shi, Y. Hou, Rongbo Zhu, and Wenjing Lou. "A novel MIMO DoF model for multi-hop networks." IEEE Network 28, no. 5 (September 2014): 81–85. http://dx.doi.org/10.1109/mnet.2014.6915444.

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Peng, Yu Yang, Jaeho Choi, Zi Chen Ren, and Jae Ho Choi. "Energy Efficient Multi-Hop Wireless Sensor Networks with Cooperative MIMO Scheme." Advanced Materials Research 660 (February 2013): 124–29. http://dx.doi.org/10.4028/www.scientific.net/amr.660.124.

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For wireless sensor networks, energy efficiency is one of the most important subjects in recent research. In this paper, an energy-efficient multi-hop scheme based on cooperative MIMO (multiple-input multiple-output) technique is proposed for wireless sensor networks. Different from other papers, we consider a single cluster transmission scenario in which energy consumption is optimized by selecting the hop length and modulation constellation size. The optimal energy consumption formula is derived and proved mathematically. In addition, the minimum energy consumption per bit is calculated numerically.
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Gunduz, Deniz, Mohammad A. Khojastepour, Andrea Goldsmith, and H. Vincent Poor. "Multi-hop MIMO relay networks: diversity-multiplexing trade-off analysis." IEEE Transactions on Wireless Communications 9, no. 5 (May 2010): 1738–47. http://dx.doi.org/10.1109/twc.2010.05.090915.

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Chen, Chih-Liang, Wayne E. Stark, and Sau-Gee Chen. "Energy-Bandwidth Efficiency Tradeoff in MIMO Multi-Hop Wireless Networks." IEEE Journal on Selected Areas in Communications 29, no. 8 (September 2011): 1537–46. http://dx.doi.org/10.1109/jsac.2011.110904.

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Kwon, Beom, Jongrok Park, and Sanghoon Lee. "Virtual MIMO broadcasting transceiver design for multi-hop relay networks." Digital Signal Processing 46 (November 2015): 97–107. http://dx.doi.org/10.1016/j.dsp.2015.08.003.

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Lee, Kyu-haeng, and Daehee Kim. "Cross-Layer Optimization for Heterogeneous MU-MIMO/OFDMA Networks." Sensors 21, no. 8 (April 13, 2021): 2744. http://dx.doi.org/10.3390/s21082744.

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To enable the full benefits from MU-MIMO (Multiuser-Multiple Input Multiple Output) and OFDMA (Orthogonal Frequency Division Multiple Access) to be achieved, the optimal use of these two technologies for a given set of network resources has been investigated in a rich body of literature. However, most of these studies have focused either on maximizing the performance of only one of these schemes, or have considered both but only for single-hop networks, in which the effect of the interference between nodes is relatively limited, thus causing the network performance to be overestimated. In addition, the heterogeneity of the nodes has not been sufficiently considered, and in particular, the joint use of OFDMA and MU-MIMO has been assumed to be always available at all nodes. In this paper, we propose a cross-layer optimization framework that considers both OFDMA and MU-MIMO for heterogeneous wireless networks. Not only does our model assume that the nodes have different capabilities, in terms of bandwidth and the number of antennas, but it also supports practical use cases in which nodes can support either OFDMA or MU-MIMO, or both at the same time. Our optimization model carefully takes into account the interactions between the key elements of the physical layer to the network layer. In addition, we consider multi-hop networks, and capture the complicated interference relationships between nodes as well as multi-path routing via multi-user transmissions. We formulate the proposed model as a Mixed Integer Linear Programming (MILP) problem, and initially model the case in which each node can selectively use either OFDMA or MU-MIMO; we then extend this to scenarios in which they are jointly used. As a case study, we apply the proposed model to sum-rate maximization and max–min fair allocation, and verify through MATLAB numerical evaluations that it can take appropriate advantage of each technology for a given set of network resources. Based on the optimization results, we also observe that when the two technologies are jointly used, more multi-user transmissions are enabled thanks to flexible resource allocation, meaning that greater use of the link capacity is achieved.
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Erdogan, Eylem, Sultan Çolak, Hakan Alakoca, Mustafa Namdar, Arif Basgumus, and Lutfiye Durak-Ata. "Interference Alignment in Multi-Hop Cognitive Radio Networks under Interference Leakage." Applied Sciences 8, no. 12 (December 4, 2018): 2486. http://dx.doi.org/10.3390/app8122486.

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In this work, we examine the interference alignment (IA) performance of a multi-input multi-output (MIMO) multi-hop cognitive radio (CR) network in the presence of multiple primary users. In the proposed architecture, it is assumed that linear IA is adopted at the secondary network to alleviate the interference between primary and secondary networks. By doing so, the secondary source can communicate with the secondary destination via multiple relays without causing any interference to the primary network. Even though linear IA can suppress the interference in CR networks considerably, interference leakages may occur due to a fast fading channel. To this end, we focus on the performance of the secondary network for two different cases: (i) the interference is perfectly aligned; (ii) the impact of interference leakages. For both cases, closed-form expressions of outage probability and ergodic capacity are derived. The results, which are validated by Monte Carlo simulations, show that interference leakages can deteriorate both system performance and the diversity gains considerably.
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ZHOU, Chao, Xing-Gong ZHANG, and Zong-Ming GUO. "Optimization Scheme for Multi-User Video Transmission Over MIMO Multi-Hop Wireless Networks." Journal of Software 24, no. 2 (December 27, 2013): 279–94. http://dx.doi.org/10.3724/sp.j.1001.2013.04201.

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Dissertations / Theses on the topic "Multi-hop MIMO Networks"

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Cavalcante, Ãtalo Vitor. "Tensor approach for channel estimation in MIMO multi-hop cooperative networks." Universidade Federal do CearÃ, 2014. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12442.

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CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior
In this dissertation the problem of channel estimation in cooperative MIMO systems is investigated. More specifically, channel estimation techniques have been developed for a communication system assisted by relays with amplify-and-forward (AF) processing system in a three-hop scenario. The techniques developed use training sequences and enable, at the receiving node, the estimation of all the channels involved in the communication process. In an initial scenario, we consider a communication system with N transmit antennas and M receive antennas and between these nodes we have two relay groups with R1 and R2 antennas each. We propose protocols based on temporal multiplexing to coordinate the retransmission of the signals. At the end of the training phase, the receiving node estimates the channel matrices by combining the received data. By exploiting the multilinear (tensorial) structure of the sets of signals, we can model the received data through tensor models, such as PARAFAC and PARATUCK2 . This work proposes the combined use of these models and algebraic techniques to explore the spatial diversity. Secondly, we consider that the number of transmit and receive antennas at the relays may be different and that the data can travel in a bidirectional scheme (two-way). In order to validate the algorithms we use Monte-Carlo simulations in which we compare our proposed models with competing channel estimation algorithms, such as, the PARAFAC and Khatri-Rao factorization based algorithms in terms of NMSE and bit error rate.
Nesta dissertaÃÃo o problema de estimaÃÃo de canal em sistemas MIMO cooperativos à investigado. Mais especificamente, foram desenvolvidas tÃcnicas para estimaÃÃo de canal em um sistema de comunicaÃÃo assistida por relays com processamento do tipo amplifica-e-encaminha (do inglÃs, amplify-and-forward) em um cenÃrio de 3 saltos. As tÃcnicas desenvolvidas utilizam sequÃncia de treinamento e habilitam, no nà receptor, a estimaÃÃo de todos os canais envolvidos no processo de comunicaÃÃo. Em um cenÃrio inicial, consideramos um sistema de comunicaÃÃo com N antenas transmissoras e M antenas receptoras e entre esses nÃs temos dois grupos de relays com R1 e R2 antenas cada um. Foram desenvolvidos protocolos de transmissÃo baseado em multiplexaÃÃo temporal para coordenar as retransmissÃes dos sinais. Ao final da fase de treinamento, o nà receptor faz a estimaÃÃo das matrizes de canal atravÃs da combinaÃÃo dos dados recebidos. Explorando a estrutura multilinear (tensorial) dos diversos conjuntos de sinais, podemos modelar os dados recebidos atravÃs de modelos tensoriais, tais como: PARAFAC e PARATUCK2. Este trabalho propÃe a utilizaÃÃo combinada desses modelos e de tÃcnicas algÃbricas para explorar a diversidade espacial. Em um segundo momento, consideramos que o nÃmero de antenas transmissoras e receptoras dos relays podem ser diferentes e ainda que os dados podem trafegar em um esquema bidirecional (do inglÃs, two-way). Para fins de validaÃÃo dos algoritmos utilizamos simulaÃÃes de Monte-Carlo em que comparamos os modelos propostos com outros algoritmos de estimaÃÃo de canal, tais como os algoritmos baseados em PARAFAC e FatoraÃÃo de Khatri-Rao em termos de NMSE e taxa de erro de bit.
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Gao, Cunhao. "Some Modeling and Optimization Problems in Cognitive Radio Ad Hoc Networks." Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/35020.

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Since its inception, cognitive radio (CR) has quickly been accepted as the enabling radio technology for next-generation wireless communications. A CR promises unprecedented flexibility in radio functionalities via programmability at the lowest layer, which was once done in hardware. Due to its spectrum sensing, learning, and adaptation capabilities, CR is able to address the heart of the problem associated with spectrum scarcity (via dynamic spectrum access (DSA)) and interoperability (via channel switching). It is envisioned that CR will be employed as a general radio platform upon which numerous wireless applications can be implemented. For both theoretical and practical purposes, it is important for network researchers to model a cognitive radio ad hoc network (CRN) and optimize its performance. Such efforts are important not only for theoretical understanding, but also in that such results can be used as benchmarks for the design of distributed algorithms and protocols. However, due to some unique characteristics associated with CRNs, existing analytical techniques may not be applied directly. As a result, new theoretical results, along with new mathematical techniques, need to be developed. In this thesis, we focus on modeling and optimization of CRNs. In particular, we will study multicast communications in CRN and MIMO-empowered CRN, which we describe as follows. An important service that must be supported by CRNs is multicast. Although there are a lot of research on multicast in ad hoc networks, those results cannot be applied to a CRN, because of the complexity associated with a CR node (e.g., multiple available frequency bands, difference in available bands from neighboring nodes). In addition, a single-layer approach (e.g., multicast routing) is overly simplistic when resource optimization (i.e., minimizing network resource) is the main objective. For this purpose, a cross-layer approach is usually necessary, which should include joint consideration of multiple lower layers, in addition to network layer. However, such a joint formulation is usually highly complex and difficult. In this thesis, we aim to develop some novel algorithms that provide near-optimal solutions. Our goal is to minimize the required network-wide resource to support a set of multicast sessions, with a certain bit rate for each multicast session. The unique characteristics associated with CR and distinguish this problem from existing multicast research for ad hoc networks. In this work, we formulate this problem via a cross-layer approach with joint consideration of scheduling and routing. Although the problem formulation is in the form of mixed integer linear program (MILP), we are successful in developing a polynomial time algorithm that offers highly competitive solution. The main ideas of the algorithm include identification of key integer variables, fixing these variables via a series of relaxed linear program (LP), and tying up such integer fixing with a bottom-up tree construction. By comparing with a lower bound, we find that the proposed algorithm can provide a solution that is very close to the optimum. In parallel to the development of CR for DSA, multiple-input multiple-output (MIMO) has widely been accepted and now implemented in commercial wireless products to increase capacity. The goal of MIMO and how it operates are largely independent and orthogonal to CR. Instead of exploiting idle channels for wireless communications, MIMO attempts to increase capacity within the same channel via space-time processing. Assuming that CR and MIMO will ultimately marry each other and offer the ultimate flexibility in DSA and spectrum efficiency, we would like to inquire the potential capacity gain in this marriage. In particular, we are interested in how such marriage will affect the capacity of a user communication session in a multi-hop CRN. We explore MIMO-empowered CR network, which we call CRNMIMO, to achieve ultimate flexibility in DSA and spectrum efficiency. Given that CR and MIMO handle interference at different levels (across channels vs. within a channel), we are interested in how joint optimization of both will maximize user capacity in a multi-hop network. To answer this question, we develop a tractable mathematical model for CRNMIMO, which captures the essence of channel assignment (for CR) and degree-of-freedom (DoF) allocation (for MIMO). Based on this mathematical model, we use numerical results to show how channel assignment in CRN and DoF allocation in MIMO can be jointly optimized to maximize capacity. More important, for a CRNMIMO with AMIMO antennas at each node, we show that joint optimization of CR and MIMO offers more than AMIMO-fold capacity increase than a CRN with only a single antenna at each node.
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Qin, Xiaoqi. "On Throughput Maximization in a Multi-hop MIMO Ad Hoc Network." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23160.

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In recent years, there has been a growing research interest in throughput optimization problems in a multi-hop wireless network. MIMO (multiple-input multiple-output), as an advanced physical layer technology, has been employed in multi-hop wireless networks to increase throughput with a given bandwidth or transmit power. It exploits the use of multiple antennas at the transmitter and receiver to increase spectral efficiency by leveraging its spatial multiplexing (SM) and interference cancellation (IC) capabilities. Instead of carrying complex manipulations on matrices, degree-of-freedom(DoF) based MIMO models, which require only simple computations, are widely used in networking research to exploit MIMO\'s SM and IC capabilities.
In this thesis, we employ a new DoF model, which can ensure feasible solution and achieve
a higher DoF region than previous DoF-based models. Based on this model, we study the DoF scheduling for a multi-hop MIMO network. Specifically, we aim to maximize the minimum rate among all sessions in the network. Some researches have been done based on this model to solve throughput optimization problems with the assumption that the route of each session is given priori. Although the fixed routing decreases the size of the problem, it also limits the performance of the network to a great extent.
The goal of this thesis is to employ this new model to solve the throughput maximization
problem by jointly considering flow routing, scheduling, and DoF allocation for SM and IC. We
formulate it as a mixed integer linear program (MILP), which cannot be solved efficiently by
commercial softwares even for moderate sized networks. Thus, we develop an efficient polynomial time algorithm by customizing the sequential fixing framework. Through simulation results, we show that this algorithm can efficiently provide near-optimal solutions for networks with different sizes.
Master of Science
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Katayama, Masaaki, Takaya Yamazato, and Zheng Huang. "Optimal Cluster Partitioning for Wireless Sensor Networks with Cooperative MISO Scheme." IEEE, 2010. http://hdl.handle.net/2237/14500.

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Huang, Zheng, Takaya Yamazato, and Masaaki Katayama. "Energy Efficiency of Cooperative MISO Technique in Multi-hop Wireless Sensor Networks." IEEE, 2008. http://hdl.handle.net/2237/12137.

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Liu, Jia-wei, and 劉家維. "MIMO-Assisted Congestion-Adaptive Routing for Multi-Hop Mobile Ad Hoc Networks." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/27348166041333198920.

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碩士
國立中山大學
電機工程學系研究所
99
A packet will be dropped when it arrives at a congested node in a routing path. The authors of [22] proposed the CRP protocol that can alleviate the congestion problem by splitting the traffic to the bypass nodes. In this thesis, we propose a new routing protocol, called MIMO-assisted congestion-adaptive routing protocol (MCRP for short), for multi-hop mobile ad hoc networks (MANETs for short). In MCRP, nodes periodically record the information of their rate-link/range-link neighbors. MCRP alleviates the congestion problem by dynamically adjusting the MIMO antenna mode and splitting the traffic to the downstream range-link neighbors. In addition, MCRP can quickly reestablish the routing path when it is broken due to node failure or mobility. Simulation results show that MCRP outperforms the existing protocols in terms of packet delivery ratio and end-to-end throughput.
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Chen, Jing-Yu, and 陳璟裕. "Power Allocation Scheme in Multi-Hop MIMO Amplify-and-Forward Relay Networks." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/73986072037846988595.

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碩士
國立中山大學
通訊工程研究所
99
With perfect channel state information at all the transmission terminals, the asymptotic capacity of multi-hop multiple-input multiple-output(MIMO) amplify-andforward(AF) relay channels is derived. Although the derivation is based on the assumption of a large number of antennas, simulation results show that the derived expression is surprisingly accurate for even a small number of antennas, and may even be superior to existing results. In addition, based on the asymptotic result, we present different power allocation schemes to (i) minimization the transmit power; (ii) maximization the network throughput; (iii) minimization the transmit power over all source. Fortunately, the proposed power allocation problems can be formulated using geometric programming(GP). Therefore, the optimal power distribution among the multi-hop relay can be obtained efficiently. For multiuser scenarios, since it is possible that the QoS of each user cannot be satisfied simultaneously, we study jointly admission control and power allocation optimization problem. This joint problem is NP-hard. Therefor, we propose an iterative algorithm to reduced the complexity.
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Som, Pritam. "Performance Analysis of Space Shift Keying in Cooperative Relaying Systems." Thesis, 2014. http://etd.iisc.ac.in/handle/2005/4111.

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Spatial modulation (SM) is a relatively new and attractive modulation technique for multi-antenna wireless systems. In SM, only one among ns = 2m available transmit antennas, chosen on the basis of m information bits, is activated at a time. A symbol from a conventional modulation alphabet (e.g., PSK) is transmitted through this chosen antenna. Space shift keying (SSK) is a special case of SM. In SSK, instead of sending a symbol from an alphabet, a signal known to the receiver, say a ‘+1’, is transmitted through the chosen antenna. SSK has the advantage of simple detection at the receiver. In this thesis, we are concerned with the performance analysis of SSK in cooperative relaying systems. We consider decode-and-forward (DF) relaying protocol, where the relays decode the received signal and forward the decoded signal towards the destina-tion. We consider three different models of cooperative relaying, namely, i) dual-hop relaying, ii) multi-hop relaying, and iii) cooperative multicasting. We also consider a cyclic-prefix single carrier (CPSC) communication system in a point-to-point chan-nel, and analyze the performance of both SM and SSK in that system under frequency selective fading. Dual-hop relaying: First, we consider a cooperative relaying system consisting of a source node, a destination node, and a relay node. We consider two commonly used re-laying techniques at the relay, namely, i) incremental relaying, and ii) threshold based relaying. We adopt selection combining at the destination. One way to perform se-lection combining operation is to use the knowledge of instantaneous signal-to-noise-ratio (SNR) as a metric for selection. However, in SSK, instantaneous SNR is difficult to be ascertained at the receiver side despite the availability of channel knowledge, be-cause the transmit antenna index itself is not known. To overcome this difficulty, we propose a new metric specific to SSK to carry out selection among the competing links. For the considered relaying schemes, we derive exact analytical expressions for the end-to-end average bit error probability (ABEP) for binary SSK (i.e., SSK with ns = 2) in closed-form. Simulations validate the end-to-end ABEP predicted by the analytical expressions. We then consider a dual-hop cooperative relaying system which consists of multiple relays. We propose a relay selection scheme for this system. In this system too, the des-tination adopts selection combining. Here, we use the proposed metric for both relay selection as well as selection combining. For this system, we derive an exact analytical expression for the end-to-end ABEP in closed-form for binary SSK. Analytical results agree with simulation results. For non-binary SSK (i.e., SSK with ns > 2), we derive an approximate closed-form expression for the end-to-end ABEP. The analytical ABEP results follow the simulated ABEP results closely. Multi-hop relaying: Next, we consider SSK in multi-hop multiple-input multiple-output (MIMO) networks. We consider two different systems of multi-hop coopera-tion, where each node has multiple antennas and employs SSK. In system I, a multi-hop diversity relaying scheme is considered. In system II, a multi-hop multi-branch relaying scheme is considered. In both the systems, we adopt DF relaying, where each relay forwards the signal only when it decodes correctly. We analyze the end-to-end ABEP and diversity order of SSK in both the systems. For binary SSK, our analytical ABEP expression is exact, and our numerical results show that the ABEPs evaluated through the analytical expression overlap with those obtained through simulations. For non-binary SSK, we derive an approximate ABEP expression, where the analyt-ically evaluated ABEP results closely follow the simulated ABEP results. We present comparisons between the ABEPs of SSK and conventional PSK, and show the instances where SSK outperforms PSK. We also present the diversity analyses for SSK in systems I and II, which predict the achievable diversity orders as a function of system parame-ters. Cooperative multicast: Next, we consider SSK in dual-hop DF cooperative multicast networks, where a source node communicates with multiple destination nodes with the help of relay nodes. We consider two different systems of cooperative multicast, namely, system III and system IV, where each node has multiple antennas and employs SSK, and communication happens in two phases. In system III, multiple relay nodes exist between the source and destination nodes. The relays that decode correctly can forward the signal to the destination nodes. We propose and analyze a relay selection scheme for this system. In system IV, the destination nodes can act as relays. Specifically, the destination nodes that decode correctly from the signal received on the direct path from source in the first phase forward to other destination nodes that did not decode correctly. For system III, we derive an exact closed-form expression of end-to-end ABEP for binary SSK, and an approximate closed-form expression of ABEP for non-binary SSK. We also present the diversity analysis for system III which predicts the achievable diversity order as a function of the system parameters. For system IV, we derive approximate closed-form ABEP expressions. The ABEP results obtained through the approximate analysis closely follow those obtained from simulations for both binary and non-binary SSK. Single carrier system: Finally, we study SM and SSK in CPSC systems on MIMO inter-symbol interference (ISI) channels. We present a diversity analysis of MIMO-CPSC systems under SSK and SM signaling. Our analysis shows that the diversity order achieved by (nt, nr ) SSK scheme and (nt, nr , ΘM ) SM scheme in MIMO-CPSC systems under maximum-likelihood detection is nr , where nt and nr denote the number of transmit and receive antennas, respectively, and ΘM denotes the modulation alpha-bet of size M . Bit error rate simulation results validate this predicted diversity order. Simulation results also show that MIMO-CPSC with SM and SSK achieves better per-formance compared to MIMO-OFDM with SM and SSK.
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Pourahmadi, Vahid. "On the Optimal Transmission Strategies for Sources without Channel State Information." Thesis, 2011. http://hdl.handle.net/10012/6320.

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With the growth of multimedia services, it is essential to find new transmission schemes to support higher data rates in wireless networks. In this thesis, we study networks in which the Channel State Information (CSI) is only available at the destination. We focus on the analysis of three different network setups. For each case, we propose a transmission scheme which maximizes the average performance of the network. The first scenario, which is studied in Chapter 2, is a multi-hop network in which the channel gain of each hop changes quasi-statically from one transmission block to the other. Our main motivation to study this network is the recent advances in deployment of relay nodes in wireless networks (e.g., LTE-A and IEEE 802.16j). In this setup, we assume that all nodes are equipped with a single antenna and the relay nodes are not capable of data buffering over multiple transmission blocks. The proposed transmission scheme is based on infinite-layer coding at all nodes (the source and all relays) in conjunction with the Decode-and-Forward DF relaying. The objective is to maximize the statistical average of the received rate per channel use at the destination. To find the optimal parameters of this code, we first formulate the problem for a two-hop scenario and describe the code design algorithm for this two-hop setting. The optimality of infinite-layer DF coding is also discussed for the case of two-hop networks. The result is then generalized to multi-hop scenarios. To show the superiority of the proposed scheme, we also evaluate the achievable average received rate of infinite-layer DF coding and compare it with the performance of previously known schemes. The second scenario, studied in Chapter 3, is a single-hop network in which both nodes are equipped with multiple antennas, while the channel gain changes quasi-statically and the CSI is not available at the source. The main reason for selecting this network setup is to study the transmission of video signals (compressed using a scalable video coding technique, e.g., SVC H.264/AVC) over a Multiple-Input Multiple-Output (MIMO) link. In this setup, although scalable video coding techniques compress the video signal into layers with different importance (for video reconstruction), the source cannot adapt the number of transmitted layers to the capacity of the channel (since it does not have the CSI in each time slot). An alternative approach is to always transmit all layers of the compressed video signal, but use unequal error protection for different layers. With this motivation, we focus on the design of multilayer codes for a MIMO link in which the destination is only able to perform successive decoding (not joint-decoding). In this chapter, we introduce a design rule for construction of multilayer codes for MIMO systems. We also propose a algorithm that uses this design rule to determine the parameters of the multilayer code. The performance analysis of the proposed scheme is also discussed in this chapter. In the two previous scenarios, the ambiguity of the source regarding the channel state comes from the fact that the channel gains randomly change in each transmission block and there is no feedback to notify the source about the current state of the channel. Apart from these, there are some scenarios in which the channel state is unknown at the source, even though the channel gain is fixed and the source knows its value. The third scenario of this thesis presents an example of such network setups. More precisely, in Chapter 4, we study a multiple access network with K users and one Access Point (AP), where all nodes are equipped with multiple antennas. To access the network, each user independently decides whether to transmit in a time slot or not (no coordination between users). Considering a two-user random access network, we first derive the optimal value of network average Degrees of Freedom (DoF) (introduced in Section 4.1). Generalizing the result to multiuser networks, we propose an upper-bound for the network average DoF of a K-user random access network. This upper-bound is then analyzed for different network configurations to identify the network classes in which the proposed upper-bound is tight. It is also shown that simple single-stream data transmission achieves the upper-bound in most network settings. However, for some network configurations, we need to apply multi-stream data transmission in conjunction with interference alignment to reach the upper-bound. Some illustrative examples are also presented in this chapter.
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Book chapters on the topic "Multi-hop MIMO Networks"

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Luo, Lin, Dengyuan Wu, and Hang Liu. "MIMO-Aware Spectrum Access and Scheduling in Multi-hop Multi-channel Wireless Networks." In Wireless Algorithms, Systems, and Applications, 161–72. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07782-6_15.

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Zhang, Peng, Xu Ding, Jing Wang, Zengwei Lyu, and Lei Shi. "The Throughput Optimization for Multi-hop MIMO Networks Based on Joint IA and SIC." In Wireless Algorithms, Systems, and Applications, 96–104. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59019-2_11.

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Ashraf, Usman, Syed Salman Haider Rizvi, and Mohammad Faisal Azeem. "Performance Evaluation of Routing Metrics in Wireless Multi-Hop Networks." In Advances in Data Mining and Database Management, 85–104. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9767-6.ch006.

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In the world of wireless communication technologies, the new standard IEEE 802.11n (MIMO) has revolutionized the available wireless bandwidth. Significant industrial and academic research has been initiated on this new technology around the world. Moreover, international as well as local manufacturers are highly interested in commercialization and performance improvement of this new technology. This is a research project in which we will perform comprehensive benchmarking of IEEE 802.11n in wireless multi-hop environments. In this project we evaluate the performance of routing metrics: Hop Count (HC) and Expected Transmission Count (ETX) on a test bed at A-Block Air University.
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Conference papers on the topic "Multi-hop MIMO Networks"

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Kudathanthirige, Dhanushka, and Gayan Amarasuriya. "Multi-Hop Massive MIMO Relay Networks." In 2018 IEEE International Conference on Communications (ICC 2018). IEEE, 2018. http://dx.doi.org/10.1109/icc.2018.8422417.

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Zeng, Huacheng, Yi Shi, Y. Thomas Hou, Wenjing Lou, Sastry Kompella, and Scott F. Midkiff. "On interference alignment for multi-hop MIMO networks." In IEEE INFOCOM 2013 - IEEE Conference on Computer Communications. IEEE, 2013. http://dx.doi.org/10.1109/infcom.2013.6566926.

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Lang, Y., D. Wubben, and K. D. Kammeyer. "Power Allocations for Adaptive Distributed MIMO Multi-Hop Networks." In ICC 2009 - 2009 IEEE International Conference on Communications. IEEE, 2009. http://dx.doi.org/10.1109/icc.2009.5199351.

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Khattab, A., A. Sabharwal, and E. W. Knightly. "Fair Randomized Antenna Allocation in Asynchronous MIMO Multi-Hop Networks." In 17th International Conference on Computer Communications and Networks 2008. IEEE, 2008. http://dx.doi.org/10.1109/icccn.2008.ecp.39.

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Kolomytsev, Maksym, and Kostiantyn Shalbanov. "Efficiency estimation of using MIMO technology in multi-hop networks." In 2014 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom). IEEE, 2014. http://dx.doi.org/10.1109/blackseacom.2014.6849022.

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Dash, Dipti, and Debarshi Kumar Sanyal. "Topology-Transparent Scheduling for Dense Multi-hop MIMO Wireless Networks." In 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE). IEEE, 2018. http://dx.doi.org/10.1109/icrieece44171.2018.9009283.

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Shi, Yi, Jia Liu, Canming Jiang, Cunhao Gao, and Y. Thomas Hou. "An optimal link layer model for multi-hop MIMO networks." In IEEE INFOCOM 2011 - IEEE Conference on Computer Communications. IEEE, 2011. http://dx.doi.org/10.1109/infcom.2011.5934994.

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Zeng, Huacheng, Yi Shi, Y. Thomas Hou, and Wenjing Lou. "An efficient DoF scheduling algorithm for multi-hop MIMO networks." In IEEE INFOCOM 2013 - IEEE Conference on Computer Communications. IEEE, 2013. http://dx.doi.org/10.1109/infcom.2013.6566950.

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Coso, Aitor, Stefano Savazzi, Umberto Spagnolini, and Christian Ibars. "Virtual MIMO Channels in Cooperative Multi-hop Wireless Sensor Networks." In 2006 40th Annual Conference on Information Sciences and Systems. IEEE, 2006. http://dx.doi.org/10.1109/ciss.2006.286439.

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Hamdaoui, Bechir, and Kang G. Shin. "Constraint Design and Modelling of Multi-Hop Multi-Band Wireless MIMO Networks." In 2008 International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, 2008. http://dx.doi.org/10.1109/iwcmc.2008.158.

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