Design of Linear Precoders for Correlated Sources in MIMO Multiple Access Channels

© 2018 IEEE. This version of the article has been accepted for publication, after peer review. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The Version of Record is available online at: https://doi.org/10.1109/TCOMM.2018.2863362[Abstract]: This paper focuses on distributed linear precoding when users transmit correlated information over a fading multiple-input and multiple-output multiple access channel. The precoders are optimized in order to minimize the sum-mean square error (MSE) between the source and the estimated symbols. When sources are correlated, minimizing the sum-MSE results in a non-convex optimization problem. The precoders for an arbitrary number of users and transmit and receive antennas are thus obtained via a projected steepest-descent algorithm and a low-complexity heuristic approach. For the more restrictive case of two single-antenna users, a closed-form expression for the minimum sum-MSE precoders is derived. Moreover, for the scenario with a single receive antenna and any number of users, a solution is obtained by means of a semi-definite relaxation. Finally, we also consider precoding schemes where the precoders are decomposed into complex scalars and unit norm vectors. Simulation results show a significant improvement when source correlation is exploited at precoding, especially for low signal-to-noise ratios and when the number of receive antennas is lower than the number of transmitting nodes.This work has been funded by Office of Naval Research Global of United States (N62909-15-1-2014), the Xunta de Galicia (ED431C 2016-045, ED341D R2016/012, ED431G/01), the Agencia Estatal de Investigación of Spain (TEC2015-69648-REDC, TEC2016-75067-C4-1-R) and ERDF funds of the EU (AEI/FEDER, UE).United States. Office of Naval Research Global of United States; N62909-15-1-2014Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED341D R2016/012Xunta de Galicia; ED431G/0

Analog Transmission of Correlated Sources Over Fading SIMO Multiple Access Channels

© 2017 IEEE. This version of the article has been accepted for publication, after peer review. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The Version of Record is available online at: https://doi.org/10.1109/TCOMM.2017.2695197.[Abstract]: Joint source-channel coding for discrete-time analog sources is an appealing transmission approach because of its extremely low delay and complexity. When the users access the channel orthogonally, analog transmission of correlated information over fading multiple access channels (MACs) using modulo-like mappings provides better performance than uncoded transmission. In this paper, we propose a simplified decoder for modulo mappings in possibly non-orthogonal MAC scenarios with a single-antenna users and a multiple-antenna receiver. Sphere decoding is investigated to reduce the computational complexity when the number of users is large. In addition, affordable strategies are proposed to optimize the mapping parameters according to the channel conditions and the source correlation. The obtained results show that the use of modulo mappings is suitable when the number of antennas at the receiver is larger than the number of users and for high correlation between user data.This work has been funded by the ONRG of United States (N62909-15-1-2014), the NSF (award CCF-1618653), Xunta de Galicia (ED431C 2016-045), the Agencia Estatal de Investigación of Spain (TEC2013-47141-C4-1-R, TEC2016-75067-C4-1-R) and ERDF funds of the EU (AEI/FEDER, UE).United States. Office of Naval Research; N62909-15-1-2014United States. National Science Foundation; CCF-1618653Xunta de Galicia; ED431C 2016-04

Lattice-Based Analog Mappings for Low-Latency Wireless Sensor Networks

© 2023 IEEE. This version of the article has been accepted for publication, after peer review. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The Version of Record is available online at: https://doi.org/10.1109/JIOT.2023.3273194.[Abstract]: We consider the transmission of spatially correlated analog information in a wireless sensor network (WSN) through fading single-input and multiple-output (SIMO) multiple access channels (MACs) with low-latency requirements. A lattice-based analog joint source-channel coding (JSCC) approach is considered where vectors of consecutive source symbols are encoded at each sensor using an n -dimensional lattice and then transmitted to a multiantenna central node. We derive a minimum mean square error (MMSE) decoder that accounts for both the multidimensional structure of the encoding lattices and the spatial correlation. In addition, a sphere decoder is considered to simplify the required searches over the multidimensional lattices. Different lattice-based mappings are approached and the impact of their size and density on performance and latency is analyzed. Results show that, while meeting low-latency constraints, lattice-based analog JSCC provides performance gains and higher reliability with respect to the state-of-the-art JSCC schemes.This work was supported in part by the Xunta de Galicia under Grant ED431C 2020/15, and in part by MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR under Grant PID2019-104958RB-C42 (ADELE), Grant TED2021-130240B-I00 (IVRY), and Grant BES-2017-081955. CITIC is funded by Xunta de Galicia through the collaboration agreement between the Consellería de Cultura, Educación, Formación Profesional e Universidades, and the Galician universities for the strengthening of the research centers of the Galician University System (CIGUS).Xunta de Galicia; ED431C 2020/1

A Deterministic Annealing Framework for Global Optimization of Delay-Constrained Communication and Control Strategies

This dissertation is concerned with the problem of global optimization of delay constrained communication and control strategies. Specifically, the objective is to obtain optimal encoder and decoder functions that map between the source space and the channel space, to minimize a given cost functional. The cost surfaces associated with these problems are highly complex and riddled with local minima, rendering gradient descent based methods ineffective. This thesis proposes and develops a powerful non-convex optimization method based on the concept of deterministic annealing (DA) - which is derived from information theoretic principles with analogies to statistical physics, and was successfully employed in several problems including vector quantization, classification and regression. DA has several useful properties including reduced sensitivity to initialization and strong potential to avoid poor local minima. DA-based optimization methods are developed here for the following fundamental communication problems: the Wyner-Ziv setting where only a decoder has access to side information, the distributed setting where independent encoders transmit over independent channels to a central decoder, and analog multiple descriptions setting which is an extension of the well known source coding problem of multiple descriptions. Comparative numerical results are presented, which show strict superiority of the proposed method over gradient descent based optimization methods as well as prior approaches in literature. Detailed analysis of the highly non-trivial structure of obtained mappings is provided. The thesis further studies the related problem of global optimization of controller mappings in decentralized stochastic control problems, including Witsenhausen's celebrated 1968 counter-example. It is well-known that most decentralized control problems do not admit closed-form solutions and require numerical optimization. An optimization method is developed, based on DA, for a class of decentralized stochastic control problems. Comparative numerical results are presented for two test problems that show strict superiority of the proposed method over prior approaches in literature, and analyze the structure of obtained controller functions