Transmit beamforming for physical-layer multicasting
This paper considers the problem of downlink transmit beamforming for wireless transmission and downstream precoding for digital subscriber wireline transmission, in the context of common information broadcasting or multicasting applications wherein channel state information (CSI) is available at th...
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| Published in | IEEE transactions on signal processing Vol. 54; no. 6; pp. 2239 - 2251 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
IEEE
01.06.2006
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.2006.872578 |
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| Abstract | This paper considers the problem of downlink transmit beamforming for wireless transmission and downstream precoding for digital subscriber wireline transmission, in the context of common information broadcasting or multicasting applications wherein channel state information (CSI) is available at the transmitter. Unlike the usual "blind" isotropic broadcasting scenario, the availability of CSI allows transmit optimization. A minimum transmission power criterion is adopted, subject to prescribed minimum received signal-to-noise ratios (SNRs) at each of the intended receivers. A related max-min SNR "fair" problem formulation is also considered subject to a transmitted power constraint. It is proven that both problems are NP-hard; however, suitable reformulation allows the successful application of semidefinite relaxation (SDR) techniques. SDR yields an approximate solution plus a bound on the optimum value of the associated cost/reward. SDR is motivated from a Lagrangian duality perspective, and its performance is assessed via pertinent simulations for the case of Rayleigh fading wireless channels. We find that SDR typically yields solutions that are within 3-4 dB of the optimum, which is often good enough in practice. In several scenarios, SDR generates exact solutions that meet the associated bound on the optimum value. This is illustrated using measured very-high-bit-rate Digital Subscriber line (VDSL) channel data, and far-field beamforming for a uniform linear transmit antenna array. |
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| AbstractList | This paper considers the problem of downlink transmit beamforming for wireless transmission and downstream precoding for digital subscriber wireline transmission, in the context of common information broadcasting or multicasting applications wherein channel state information (CSI) is available at the transmitter. Unlike the usual “blind isotropic broadcasting scenario, the availability of CSI allows transmit optimization. A minimum transmission power criterion is adopted, subject to prescribed minimum received signal-to-noise ratios (SNRs) at each of the intended receivers. A related max-min SNR “fair problem formulation is also considered subject to a transmitted power constraint. It is proven that both problems are NP-hard; however, suitable reformulation allows the successful application of semidefinite relaxation (SDR) techniques. SDR yields an approximate solution plus a bound on the optimum value of the associated cost/reward. SDR is motivated from a Lagrangian duality perspective, and its performance is assessed via pertinent simulations for the case of Rayleigh fading wireless channels. We find that SDR typically yields solutions that are within 3-4 dB of the optimum, which is often good enough in practice. In several scenarios, SDR generates exact solutions that meet the associated bound on the optimum value. This is illustrated using measured very-high-bit-rate Digital Subscriber line (VDSL) channel data, and far-field beamforming for a uniform linear transmit antenna array. A minimum transmission power criterion is adopted, subject to prescribed minimum received signal-to-noise ratios (SNRs) at each of the intended receivers. |
| Author | Sidiropoulos, N.D. Zhi-Quan Luo Davidson, T.N. |
| Author_xml | – sequence: 1 givenname: N.D. surname: Sidiropoulos fullname: Sidiropoulos, N.D. organization: Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada – sequence: 2 givenname: T.N. surname: Davidson fullname: Davidson, T.N. organization: Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada – sequence: 3 surname: Zhi-Quan Luo fullname: Zhi-Quan Luo |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17828758$$DView record in Pascal Francis |
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| CODEN | ITPRED |
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| Cites_doi | 10.1007/s101070050100 10.1080/10556789908805766 10.1137/S1052623401395899 10.1109/78.992139 10.1007/978-1-4615-4381-7 10.1137/050642691 10.1109/JSAC.2002.1007389 10.1109/TSP.2002.806865 10.1007/s101070050006 10.1109/TIT.1972.1054829 10.1017/CBO9780511804441 |
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| Keywords | Performance evaluation Parameter estimation Wireless telecommunication Transmitter Downlink Data broadcast Information dissemination Beam forming Optimization Multicast semidefinite programming Relaxation Subscriber minimization of total radiation power Channel estimation very-high-bit-rate Digital Subscriber line (VDSL) precoding Broadcasting Availability Maximin problem Rayleigh channels semidefinite relaxation (SDR) downlink beamforming Digital transmission Simulation multicasting Minimax method NP hard problem convex optimization Approximate solution Software radio Signal to noise ratio |
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| References | ref13 Garey (ref4) 1979 ref12 Wolkowicz (ref14) 2000 ref15 Jindal (ref6) Bengtsson (ref1) 2001 Lopez (ref7) 2002 ref11 ref10 ref2 ref16 ref9 ref3 ref5 Luo (ref8) 2004 |
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| Snippet | This paper considers the problem of downlink transmit beamforming for wireless transmission and downstream precoding for digital subscriber wireline... A minimum transmission power criterion is adopted, subject to prescribed minimum received signal-to-noise ratios (SNRs) at each of the intended receivers. |
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| SubjectTerms | Algorithms Applied sciences Array signal processing Availability Beamforming Broadcasting Channel state information Channels convex optimization Cost function Detection, estimation, filtering, equalization, prediction Digital Downlink downlink beamforming Exact sciences and technology Exact solutions Fading Information, signal and communications theory Lagrangian functions Linear antenna arrays minimization of total radiation power Multicasting Optimization Rayleigh channels semidefinite programming semidefinite relaxation (SDR) Signal and communications theory Signal to noise ratio Signal, noise Studies Telecommunications and information theory Transmitters very-high-bit-rate Digital Subscriber line (VDSL) precoding |
| Title | Transmit beamforming for physical-layer multicasting |
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