Joint Precoder Design for Distributed Transmission of Correlated Sources in Sensor Networks
We consider the problem of transmitting multiple spatially distributed correlated sources to a common destination (e.g. a fusion center or an access point) in wireless sensor networks (WSNs). The correlated data from multiple sensors are jointly transmitted to the destination via orthogonal channels...
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| Published in: | IEEE transactions on wireless communications Vol. 12; no. 6; pp. 2918 - 2929 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York, NY
IEEE
01.06.2013
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 1536-1276, 1558-2248 |
| Online Access: | Get full text |
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| Abstract | We consider the problem of transmitting multiple spatially distributed correlated sources to a common destination (e.g. a fusion center or an access point) in wireless sensor networks (WSNs). The correlated data from multiple sensors are jointly transmitted to the destination via orthogonal channels. We assume that the channel between each sensor and the receiver is multiple-input multiple-output (MIMO), with each sensor and the receiver equipped with multiple transmit/receive antennas. In this framework, we study the problem of joint linear precoder design for all sensors by assuming the knowledge of the instantaneous channel state information (CSI), aiming at maximizing the mutual information between the sources and the received signals at the destination. We propose a Gauss-Seidel iterative approach which successively optimizes the precoding matrix associated with each sensor, while fixing the other precoding matrices. Numerical results show that the proposed algorithm that takes into account the spatial correlation across sensors can achieve higher capacity than conventional methods that neglect the spatial correlation. |
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| AbstractList | We consider the problem of transmitting multiple spatially distributed correlated sources to a common destination (e.g. a fusion center or an access point) in wireless sensor networks (WSNs). The correlated data from multiple sensors are jointly transmitted to the destination via orthogonal channels. We assume that the channel between each sensor and the receiver is multiple-input multiple-output (MIMO), with each sensor and the receiver equipped with multiple transmit/receive antennas. In this framework, we study the problem of joint linear precoder design for all sensors by assuming the knowledge of the instantaneous channel state information (CSI), aiming at maximizing the mutual information between the sources and the received signals at the destination. We propose a Gauss-Seidel iterative approach which successively optimizes the precoding matrix associated with each sensor, while fixing the other precoding matrices. Numerical results show that the proposed algorithm that takes into account the spatial correlation across sensors can achieve higher capacity than conventional methods that neglect the spatial correlation. |
| Author | Jun Fang Zhi Chen Hongbin Li Yu Gong |
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| CitedBy_id | crossref_primary_10_1109_TSP_2020_3037513 crossref_primary_10_1109_TSP_2021_3114982 crossref_primary_10_1016_j_inffus_2016_12_008 crossref_primary_10_1109_ACCESS_2019_2933052 crossref_primary_10_1109_TWC_2017_2762672 crossref_primary_10_1109_TCOMM_2018_2794363 crossref_primary_10_1109_TCOMM_2021_3091181 crossref_primary_10_1109_TSP_2020_3037495 crossref_primary_10_1109_JIOT_2021_3049384 crossref_primary_10_1109_TSP_2015_2439239 crossref_primary_10_1016_j_sigpro_2013_12_015 crossref_primary_10_1109_JIOT_2020_2996744 |
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| Keywords | Parameter estimation Spatial correlation Wireless telecommunication Iterative method sensor networks Remote sensing Information source Coding Channel estimation Precoder design Pretreatment Receiving antenna Gauss Seidel method Antenna array Signal detection MIMO system Multisensor Gauss-Seidel approach Coding circuit Measurement sensor Distributed source signal Algorithm distributed correlated sources Transmitting antenna Point estimation Wireless network Numerical simulation Sensor array Mutual information |
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| SubjectTerms | Antennas Applied sciences Channels Correlation Covariance matrices Detection, estimation, filtering, equalization, prediction distributed correlated sources Exact sciences and technology Gauss-Seidel approach Information, signal and communications theory Joints Linear programming Optimization Precoder design Radiocommunications Receivers Remote sensors sensor networks Sensors Services and terminals of telecommunications Signal and communications theory Signal, noise Studies Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Telemetry. Remote supervision. Telewarning. Remote control Transmission Transmission and modulation (techniques and equipments) Wireless networks Wireless sensor networks |
| Title | Joint Precoder Design for Distributed Transmission of Correlated Sources in Sensor Networks |
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