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In multiple-input multiple-output (MIMO) wireless systems, the receiver must extract each transmitted signal from received signals. Iterative signal detection with belief propagation (BP) can improve the error rate performance, by increasing the number of detection and decoding iterations in MIMO systems. This number of iterations is, however, limited in actual systems because each additional iteration increases latency, receiver size, and so on. This paper proposes a convergence acceleration technique that can achieve better error rate performance with fewer iterations than the conventional iterative signal detection. Since the Log-Likelihood Ratio (LLR) of one bit propagates to all other bits with BP, improving some LLRs improves overall decoder performance. In our proposal, all the coded bits are divided into groups and only one group is detected in each iterative signal detection whereas in the conventional approach, each iterative signal detection run processes all coded bits, simultaneously. Our proposal increases the frequency of initial LLR update by increasing the number of iterative signal detections and decreasing the number of coded bits that the receiver detects in one iterative signal detection. Computer simulations show that our proposal achieves better error rate performance with fewer detection and decoding iterations than the conventional approach.

- Publication
- IEICE TRANSACTIONS on Communications Vol.E91-B No.8 pp.2640-2647

- Publication Date
- 2008/08/01

- Publicized

- Online ISSN
- 1745-1345

- DOI
- 10.1093/ietcom/e91-b.8.2640

- Type of Manuscript
- PAPER

- Category
- Wireless Communication Technologies

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Satoshi GOUNAI, Tomoaki OHTSUKI, "Convergence Acceleration of Iterative Signal Detection for MIMO System with Belief Propagation" in IEICE TRANSACTIONS on Communications,
vol. E91-B, no. 8, pp. 2640-2647, August 2008, doi: 10.1093/ietcom/e91-b.8.2640.

Abstract: In multiple-input multiple-output (MIMO) wireless systems, the receiver must extract each transmitted signal from received signals. Iterative signal detection with belief propagation (BP) can improve the error rate performance, by increasing the number of detection and decoding iterations in MIMO systems. This number of iterations is, however, limited in actual systems because each additional iteration increases latency, receiver size, and so on. This paper proposes a convergence acceleration technique that can achieve better error rate performance with fewer iterations than the conventional iterative signal detection. Since the Log-Likelihood Ratio (LLR) of one bit propagates to all other bits with BP, improving some LLRs improves overall decoder performance. In our proposal, all the coded bits are divided into groups and only one group is detected in each iterative signal detection whereas in the conventional approach, each iterative signal detection run processes all coded bits, simultaneously. Our proposal increases the frequency of initial LLR update by increasing the number of iterative signal detections and decreasing the number of coded bits that the receiver detects in one iterative signal detection. Computer simulations show that our proposal achieves better error rate performance with fewer detection and decoding iterations than the conventional approach.

URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e91-b.8.2640/_p

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@ARTICLE{e91-b_8_2640,

author={Satoshi GOUNAI, Tomoaki OHTSUKI, },

journal={IEICE TRANSACTIONS on Communications},

title={Convergence Acceleration of Iterative Signal Detection for MIMO System with Belief Propagation},

year={2008},

volume={E91-B},

number={8},

pages={2640-2647},

abstract={In multiple-input multiple-output (MIMO) wireless systems, the receiver must extract each transmitted signal from received signals. Iterative signal detection with belief propagation (BP) can improve the error rate performance, by increasing the number of detection and decoding iterations in MIMO systems. This number of iterations is, however, limited in actual systems because each additional iteration increases latency, receiver size, and so on. This paper proposes a convergence acceleration technique that can achieve better error rate performance with fewer iterations than the conventional iterative signal detection. Since the Log-Likelihood Ratio (LLR) of one bit propagates to all other bits with BP, improving some LLRs improves overall decoder performance. In our proposal, all the coded bits are divided into groups and only one group is detected in each iterative signal detection whereas in the conventional approach, each iterative signal detection run processes all coded bits, simultaneously. Our proposal increases the frequency of initial LLR update by increasing the number of iterative signal detections and decreasing the number of coded bits that the receiver detects in one iterative signal detection. Computer simulations show that our proposal achieves better error rate performance with fewer detection and decoding iterations than the conventional approach.},

keywords={},

doi={10.1093/ietcom/e91-b.8.2640},

ISSN={1745-1345},

month={August},}

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TY - JOUR

TI - Convergence Acceleration of Iterative Signal Detection for MIMO System with Belief Propagation

T2 - IEICE TRANSACTIONS on Communications

SP - 2640

EP - 2647

AU - Satoshi GOUNAI

AU - Tomoaki OHTSUKI

PY - 2008

DO - 10.1093/ietcom/e91-b.8.2640

JO - IEICE TRANSACTIONS on Communications

SN - 1745-1345

VL - E91-B

IS - 8

JA - IEICE TRANSACTIONS on Communications

Y1 - August 2008

AB - In multiple-input multiple-output (MIMO) wireless systems, the receiver must extract each transmitted signal from received signals. Iterative signal detection with belief propagation (BP) can improve the error rate performance, by increasing the number of detection and decoding iterations in MIMO systems. This number of iterations is, however, limited in actual systems because each additional iteration increases latency, receiver size, and so on. This paper proposes a convergence acceleration technique that can achieve better error rate performance with fewer iterations than the conventional iterative signal detection. Since the Log-Likelihood Ratio (LLR) of one bit propagates to all other bits with BP, improving some LLRs improves overall decoder performance. In our proposal, all the coded bits are divided into groups and only one group is detected in each iterative signal detection whereas in the conventional approach, each iterative signal detection run processes all coded bits, simultaneously. Our proposal increases the frequency of initial LLR update by increasing the number of iterative signal detections and decreasing the number of coded bits that the receiver detects in one iterative signal detection. Computer simulations show that our proposal achieves better error rate performance with fewer detection and decoding iterations than the conventional approach.

ER -