Iterative Near-Maximum-Likelihood Detection in Rank-Deficient Downlink SDMA Systems
Iterative Near-Maximum-Likelihood Detection in Rank-Deficient Downlink SDMA Systems
Abstract—In this paper, a precoded and iteratively detected downlink multiuser system is proposed, which is capable of operating in rankdeficient scenarios, when the number of transmitters exceeds the number of receivers. The literature of uplink space division multiple access (SDMA) systems is rich, but at the time of writing there is a paucity of information on the employment of SDMA techniques in the downlink. Hence, we propose a novel precoded downlink SDMA (DL-SDMA) multiuser communication system, which invokes a low-complexity nearmaximum-likelihood sphere decoder and is particularly suitable for the aforementioned rank-deficient scenario. Powerful iterative decoding is carried out by exchanging extrinsic information between the precoder’s decoder and the outer channel decoder. Furthermore, we demonstrate with the aid of extrinsic information transfer charts that our proposed precoded DL-SDMA system has a better convergence behavior than its nonprecoded DL-SDMA counterpart. Quantitatively, the proposed system having a normalized system load of Ls = 1.333, i.e., 1.333 times higher effective throughput facilitated by having 1.333 times more DL-SDMA transmitters than receivers, exhibits a “turbo cliff” at an Eb/N0 of 5 dB and hence results in an infinitesimally low bit error rate (BER). By contrast, at Eb/N0 = 5 dB, the equivalent system dispensing with precoding exhibits a BER in excess of 10%. Index Terms—Iterative decoding, maximum likelihood detection, space division multiple access (SDMA) downlink, sphere decoding.
653-657
Wei, C.Y.
a8cbdf52-ebba-4154-9055-1e9768e2ab88
Akhtman, J.
d4fd2b26-c123-463d-847c-80adc83a89fa
Ng, S.X.
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
January 2008
Wei, C.Y.
a8cbdf52-ebba-4154-9055-1e9768e2ab88
Akhtman, J.
d4fd2b26-c123-463d-847c-80adc83a89fa
Ng, S.X.
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Wei, C.Y., Akhtman, J., Ng, S.X. and Hanzo, L.
(2008)
Iterative Near-Maximum-Likelihood Detection in Rank-Deficient Downlink SDMA Systems.
IEEE Transactions on Vehicular Technology, 57 (1), .
Abstract
Abstract—In this paper, a precoded and iteratively detected downlink multiuser system is proposed, which is capable of operating in rankdeficient scenarios, when the number of transmitters exceeds the number of receivers. The literature of uplink space division multiple access (SDMA) systems is rich, but at the time of writing there is a paucity of information on the employment of SDMA techniques in the downlink. Hence, we propose a novel precoded downlink SDMA (DL-SDMA) multiuser communication system, which invokes a low-complexity nearmaximum-likelihood sphere decoder and is particularly suitable for the aforementioned rank-deficient scenario. Powerful iterative decoding is carried out by exchanging extrinsic information between the precoder’s decoder and the outer channel decoder. Furthermore, we demonstrate with the aid of extrinsic information transfer charts that our proposed precoded DL-SDMA system has a better convergence behavior than its nonprecoded DL-SDMA counterpart. Quantitatively, the proposed system having a normalized system load of Ls = 1.333, i.e., 1.333 times higher effective throughput facilitated by having 1.333 times more DL-SDMA transmitters than receivers, exhibits a “turbo cliff” at an Eb/N0 of 5 dB and hence results in an infinitesimally low bit error rate (BER). By contrast, at Eb/N0 = 5 dB, the equivalent system dispensing with precoding exhibits a BER in excess of 10%. Index Terms—Iterative decoding, maximum likelihood detection, space division multiple access (SDMA) downlink, sphere decoding.
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Published date: January 2008
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 265119
URI: http://eprints.soton.ac.uk/id/eprint/265119
ISSN: 0018-9545
PURE UUID: 35688b40-2a89-44d2-a0dd-245a541a0568
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Date deposited: 27 Jan 2008 17:24
Last modified: 18 Mar 2024 02:48
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Author:
C.Y. Wei
Author:
J. Akhtman
Author:
S.X. Ng
Author:
L. Hanzo
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