Cooperative Interference Mitigation in Wireless Cellular Networks

Cooperative Interference Mitigation in Wireless Cellular Networks Seyed Arvin Ayoughi Doctor of Philosophy The Edward S. Rogers Sr. Department of Electrical & Computer Engineering University of Toronto 2019 In this thesis, we explore potentials of cooperative communication at receivers’ side in the downlink of wireless cellular networks for interference mitigation and signal enhancement. We investigate two regimes of latency and reliability of communication: one for providing high long-term average user rates for supporting a quality of service that is suitable for human visual and auditory perception, and the other for providing an ultrareliable low-latency machine-type wireless communication for streaming information in control applications. We consider three different models of cooperative communication. First, we study deploying a multi-antenna relay node that provides a nearby cell-edge user with extra dimensions over an out-of-band relaying link. We model this scenario by a Gaussian multiple-input multiple-output (MIMO) relay channel with correlated noise across relay and destination antennas, and analyze the capacity of this channel. This type of relay deployment is most effective when the number of receive antennas is small and the number of relay antennas is large enough. Second, we study deploying a multi-antenna half-duplex amplify-and-forward relay node that simultaneously provides multiple cell-edge users with extra dimensions. We show that the optimized relaying significantly improves the long-term average rates of cell-edge users, even after accounting for the extra bandwidth required for half-duplex relaying, provided that the relay is equipped with sufficiently many antennas. Third, we study cooperation among receivers for combating fading and mitigating interference for ultrareliable low-latency wireless communication. We consider multiple interfering broadcasts from controllers to their corresponding actuators. The recently-proposed Occupy CoW protocol efficiently exploits the spatial diversity of distributed receivers for combating deep fading. It consists of two consecutive phases: the broadcast phase and the cooperation

[1]  Chao Tian,et al.  Remote Vector Gaussian Source Coding With Decoder Side Information Under Mutual Information and Distortion Constraints , 2009, IEEE Transactions on Information Theory.

[2]  Hua Wang,et al.  Gaussian Interference Channel Capacity to Within One Bit , 2007, IEEE Transactions on Information Theory.

[3]  How to exploit spatial diversity in wireless industrial networks , 2008, Annu. Rev. Control..

[4]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[5]  Sven Nordholm,et al.  MMSE-Based Transceiver Design Algorithms for Interference MIMO Relay Systems , 2015, IEEE Transactions on Wireless Communications.

[6]  Rudolf Ahlswede,et al.  Source coding with side information and a converse for degraded broadcast channels , 1975, IEEE Trans. Inf. Theory.

[7]  Taesoo Kwon,et al.  Cooperative Cellular Wireless Networks: Adaptive resource allocation in cooperative cellular networks , 2011 .

[8]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[9]  Anant Sahai,et al.  Cooperative communication for high-reliability low-latency wireless control , 2015, 2015 IEEE International Conference on Communications (ICC).

[10]  Wei Yu,et al.  A DoF analysis of compress-and-forward in MIMO Gaussian relay channel with correlated noises , 2015, 2015 IEEE 14th Canadian Workshop on Information Theory (CWIT).

[11]  Wei Yu,et al.  Optimized MIMO transmission and compression for interference mitigation with cooperative relay , 2015, 2015 IEEE International Conference on Communications (ICC).

[12]  Dirk Timmermann,et al.  Survey on real-time communication via ethernet in industrial automation environments , 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

[13]  W. Härdle,et al.  Applied Multivariate Statistical Analysis , 2003 .

[14]  Michael Gastpar,et al.  The Distributed Karhunen–Loève Transform , 2006, IEEE Transactions on Information Theory.

[15]  Sung Hoon Lim,et al.  Distributed Decode–Forward for Relay Networks , 2015, IEEE Transactions on Information Theory.

[16]  A. Wittneben,et al.  A new bandwidth efficient transmit antenna modulation diversity scheme for linear digital modulation , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.

[17]  Wei Yu,et al.  Capacity of the Gaussian Relay Channel with Correlated Noises to Within a Constant Gap , 2012, IEEE Communications Letters.

[18]  Young-Han Kim,et al.  The Approximate Capacity of the MIMO Relay Channel , 2014, IEEE Transactions on Information Theory.

[19]  Suhas N. Diggavi,et al.  Approximate Capacity of a Class of Gaussian Interference-Relay Networks , 2011, IEEE Transactions on Information Theory.

[20]  Theodore S. Rappaport,et al.  Wireless Communications: Principles and Practice (2nd Edition) by , 2012 .

[21]  Young-Han Kim,et al.  Capacity of a Class of Deterministic Relay Channels , 2006, 2007 IEEE International Symposium on Information Theory.

[22]  Lassi Hentila,et al.  WINNER II Channel Models , 2009 .

[23]  Jean-Pierre Thomesse,et al.  Fieldbus Technology in Industrial Automation , 2005, Proceedings of the IEEE.

[24]  Emre Telatar,et al.  Bounds on the capacity region of a class of interference channels , 2007, 2007 IEEE International Symposium on Information Theory.

[25]  Gregory W. Wornell,et al.  Cooperative diversity in wireless networks: Efficient protocols and outage behavior , 2004, IEEE Transactions on Information Theory.

[26]  Wei Yu,et al.  Enhance cell-edge rates by amplify-forward shared relays in dense cellular networks , 2017, 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[27]  Syed Ali Jafar,et al.  The Effect of Noise Correlation in Amplify-and-Forward Relay Networks , 2009, IEEE Transactions on Information Theory.

[28]  Anant Sahai,et al.  Real-Time Cooperative Communication for Automation Over Wireless , 2016, IEEE Transactions on Wireless Communications.

[29]  Wei Yu,et al.  Interference Mitigation via Relaying , 2017, IEEE Transactions on Information Theory.

[30]  Robert W. Heath,et al.  Is the PHY layer dead? , 2011, IEEE Communications Magazine.

[31]  Brett Schein,et al.  Distributed coordination in network information theory , 2001 .

[32]  Wei Yu,et al.  Capacity of a Class of Modulo-Sum Relay Channels , 2007, IEEE Transactions on Information Theory.

[33]  Jeffrey G. Andrews,et al.  Femtocell networks: a survey , 2008, IEEE Communications Magazine.

[34]  T. Markham,et al.  A Generalization of the Schur Complement by Means of the Moore–Penrose Inverse , 1974 .

[35]  Armin Dammann.  Contents , 2018, Clinical Neurophysiology.

[36]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[37]  Anant Sahai,et al.  Network coding for high-reliability low-latency wireless control , 2016, 2016 IEEE Wireless Communications and Networking Conference.

[38]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[39]  Yindi Jing,et al.  Distributed Space-Time Coding in Wireless Relay Networks , 2006, IEEE Transactions on Wireless Communications.

[40]  Calyampudi R. Rao,et al.  Linear statistical inference and its applications , 1965 .

[41]  Franz Rellich,et al.  Perturbation Theory of Eigenvalue Problems , 1969 .

[42]  Aitor del Coso,et al.  Distributed compression for MIMO coordinated networks with a backhaul constraint , 2009, IEEE Transactions on Wireless Communications.

[43]  Philippe J. Sartori,et al.  Cooperative Algorithms for MIMO Amplify-and-Forward Relay Networks , 2011, IEEE Transactions on Signal Processing.

[44]  Anant Sahai,et al.  Predicting Wireless Channels for Ultra-Reliable Low-Latency Communications , 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

[45]  Tirkkonen Olav,et al.  Selective multi-hop relaying for ultra-reliable communication in a factory environment , 2016 .

[46]  Jean-Dominique Decotignie,et al.  Ethernet-Based Real-Time and Industrial Communications , 2005, Proceedings of the IEEE.

[47]  Raphael Thomas Livius Rolny.  Future mobile communication: from cooperative cells to the post-cellular relay carpet , 2016 .

[48]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[49]  Abbas El Gamal,et al.  Capacity theorems for the relay channel , 1979, IEEE Trans. Inf. Theory.

[50]  Armin Wittneben,et al.  The relay carpet: Ubiquitous two-way relaying in cooperative cellular networks , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[51]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[52]  Aaron D. Wyner,et al.  On source coding with side information at the decoder , 1975, IEEE Trans. Inf. Theory.

[53]  Kenichi Higuchi,et al.  Non-orthogonal access with SIC in cellular downlink for user fairness enhancement , 2011, 2011 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS).

[54]  Sae-Young Chung,et al.  Noisy network coding , 2010 .

[55]  Deqiang Chen.  User Cooperation Diversity , 2003 .

[56]  Mohammad Reza Aref,et al.  Slepian–Wolf Coding Over Cooperative Relay Networks , 2011, IEEE Transactions on Information Theory.

[57]  James Stewart,et al.  Essential Calculus: Early Transcendentals , 2006 .

[58]  Andrea J. Goldsmith,et al.  Study of Gaussian Relay Channels with Correlated Noises , 2010, IEEE Transactions on Communications.

[59]  Sae-Young Chung,et al.  Aligned interference neutralization and the degrees of freedom of the 2 × 2 × 2 interference channel , 2010, 2011 IEEE International Symposium on Information Theory Proceedings.

[60]  C. E. M. Pearce,et al.  Some New Bounds for Singular Values and Eigenvalues of Matrix Products , 2000, Ann. Oper. Res..

[61]  E. Meulen,et al.  Three-terminal communication channels , 1971, Advances in Applied Probability.

[62]  Abbas El Gamal,et al.  Network Information Theory , 2021, 2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT).

[63]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[64]  Armin Wittneben,et al.  Spectral efficient protocols for half-duplex fading relay channels , 2007, IEEE Journal on Selected Areas in Communications.

[65]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.

[66]  Zhi-Quan Luo,et al.  An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[67]  Dina Katabi,et al.  SourceSync: a distributed wireless architecture for exploiting sender diversity , 2010, SIGCOMM '10.

[68]  Ke Wang Helmersson,et al.  Deployment Strategies for Ultra-Reliable and Low-Latency Communication in Factory Automation , 2015, 2015 IEEE Globecom Workshops (GC Wkshps).

[69]  Anass Benjebbour,et al.  Non-Orthogonal Multiple Access (NOMA) for Cellular Future Radio Access , 2013, 2013 IEEE 77th Vehicular Technology Conference (VTC Spring).

[70]  Wei Yu,et al.  Fair Scheduling and Resource Allocation for Wireless Cellular Network with Shared Relays , 2012, IEEE J. Sel. Areas Commun..

[71]  Michael Gastpar,et al.  Cooperative strategies and capacity theorems for relay networks , 2005, IEEE Transactions on Information Theory.

[72]  Mohammad Reza Aref,et al.  The capacity of the semideterministic relay channel , 1982, IEEE Trans. Inf. Theory.

[73]  Suhas N. Diggavi,et al.  Wireless Network Information Flow: A Deterministic Approach , 2009, IEEE Transactions on Information Theory.