Optimization of MIMO Relays for Multipoint-to-Multipoint Communications: Nonrobust and Robust Designs
In this paper, we propose algorithms to jointly optimize the multiple multiantenna relays which assist multipoint-to-multipoint communications in wireless networks. Assuming that the knowledge of the second order statistics of the channels such as covariance matrices are available, the multiple-inpu...
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| Published in | IEEE transactions on signal processing Vol. 58; no. 12; pp. 6355 - 6368 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
IEEE
01.12.2010
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1053-587X 1941-0476 |
| DOI | 10.1109/TSP.2010.2077632 |
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| Abstract | In this paper, we propose algorithms to jointly optimize the multiple multiantenna relays which assist multipoint-to-multipoint communications in wireless networks. Assuming that the knowledge of the second order statistics of the channels such as covariance matrices are available, the multiple-input-multiple-output (MIMO) relays are designed using two different methods: (1) minimize the sum of the powers of the relays while fulfilling the signal-to-interference-plus-noise ratio (SINR) requirements for all destinations and (2) maximize the minimum of the SINRs of all destinations satisfying the transmit power constraint of each MIMO relay. Furthermore, considering the fact that the covariance matrices of the channels between the MIMO relays and destinations are subject to uncertainty due to feedback and quantization errors, the robust versions of the aforementioned methods based on worst-case concept are proposed. It is shown that the proposed nonrobust as well as robust designs are nonconvex optimization problems but they can be solved accurately and efficiently using the standard semidefinite relaxation and randomization techniques. Computer simulations verify the improved performance of the robust designs over nonrobust methods. |
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| AbstractList | In this paper, we propose algorithms to jointly optimize the multiple multiantenna relays which assist multipoint-to-multipoint communications in wireless networks. Assuming that the knowledge of the second order statistics of the channels such as covariance matrices are available, the multiple-input-multiple-output (MIMO) relays are designed using two different methods: 1) minimize the sum of the powers of the relays while fulfilling the signal-to-interference-plus-noise ratio (SINR) requirements for all destinations and 2) maximize the minimum of the SINRs of all destinations satisfying the transmit power constraint of each MIMO relay. Furthermore, considering the fact that the covariance matrices of the channels between the MIMO relays and destinations are subject to uncertainty due to feedback and quantization errors, the robust versions of the aforementioned methods based on worst-case concept are proposed. It is shown that the proposed nonrobust as well as robust designs are nonconvex optimization problems but they can be solved accurately and efficiently using the standard semidefinite relaxation and randomization techniques. Computer simulations verify the improved performance of the robust designs over nonrobust methods. |
| Author | Chalise, Batu Krishna Vandendorpe, Luc |
| Author_xml | – sequence: 1 givenname: Batu Krishna surname: Chalise fullname: Chalise, Batu Krishna email: batu.chalise@villanova.edu organization: Univ. Catholique de Louvain, Louvain-la-Neuve, Belgium – sequence: 2 givenname: Luc surname: Vandendorpe fullname: Vandendorpe, Luc email: luc.vandendorpe@uclouvain.be organization: ICTEAM Inst., Univ. Catholique de Louvain, Louvain-la-Neuve, Belgium |
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| Keywords | Performance evaluation Second order Parameter estimation Non convex programming Relay Worst case method Wireless telecommunication Data broadcast Information dissemination Optimization Multicast Relaxation Randomization Covariance Channel estimation Channel state information MIMO system Quantization error Computer simulation robust MIMO relays Order statistic Algorithm Statistical method worst-case performance optimization Telecommunication network Signal processing Wireless network channel uncertainty and convex optimization Signal to interference plus noise ratio |
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| SubjectTerms | Algorithms Applied sciences Channel estimation Channel state information channel uncertainty and convex optimization Channels Covariance Covariance matrix Detection, estimation, filtering, equalization, prediction Exact sciences and technology Information, signal and communications theory Interference Mathematical analysis Matrices Matrix methods MIMO Miscellaneous Optimization Quality of service Relays robust MIMO relays Robustness Signal and communications theory Signal processing Signal, noise Statistics Studies Telecommunications and information theory Wireless networks worst-case performance optimization |
| Title | Optimization of MIMO Relays for Multipoint-to-Multipoint Communications: Nonrobust and Robust Designs |
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