Analog network coding in the multiple access relay channel: Error rate analysis and optimal power allocation
In this paper, we consider Analog Network Coding (ANC) in the Multiple Access Relay Channel (MARC) with multiple relays, and provide the following three-fold contribution: 1) we introduce a tractable mathematical framework for computing the Symbol Error Rate (SER) of Maximum-Likelihood (ML), Zero-Fo...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) |
| Repositorio: | r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) |
| OAI Identifier: | oai:cttc.fundanetsuite.com:p1877 |
| Acceso en línea: | https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=1877 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84933524428&doi=10.1109%2fTWC.2015.2399671&partnerID=40&md5=1368946cc624bd604391e8de7b1ca71a |
| Access Level: | acceso abierto |
| Palabra clave: | Beamforming Channel coding Codes (symbols) Electric network topology Electric relays Errors Fading channels Intelligent systems Maximum likelihood Mean square error Monte Carlo methods Radio receivers Analog network coding Analog network coding (ANC) Mathematical frameworks Minimum mean square error receiver Multiple access relay channel Optimal power allocation Symbol error rate (SER) Zero-forcing Network coding |
| Sumario: | In this paper, we consider Analog Network Coding (ANC) in the Multiple Access Relay Channel (MARC) with multiple relays, and provide the following three-fold contribution: 1) we introduce a tractable mathematical framework for computing the Symbol Error Rate (SER) of Maximum-Likelihood (ML), Zero-Forcing (ZF), and Minimum Mean Square Error (MMSE) receivers; 2) by capitalizing on this tractable mathematical framework, we formulate a power allocation problem that is proved to be convex for ML, ZF and MMSE receivers; and 3) we provide closed-form expressions of the optimal power to be allocated to the sources and the relays for ZF and MMSE receivers. With the aid of Monte Carlo simulations, we validate the accuracy of the proposed mathematical framework for various network topologies and channel conditions, as well as study the effectiveness of optimal power allocation. It is shown, in particular, that power optimization is beneficial as the number of sources increases and if the quality of the source-relay links is better than the quality of the relay-destination links. © 2002-2012 IEEE. |
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