An efficient iterative detection scheme for coded MIMO systems

Ahmed, Saleem; Kim, Sooyoung

doi:10.1109/icoin.2013.6496419

Cited by 2 publications

(6 citation statements)

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“…The number of outer iterations (turbo decoder iterations), I d is set to 4 and number of inner iterations (MIMO detector iterations), I m is set to 2. As we can see that, at E b /N 0 of 6.5 dB, the proposed method with β = −0.8 produces nearly the same BER as the method proposed in [7]. Fig.…”

Section: Simulation Resultsmentioning

confidence: 60%

“…9 shows the number of MAP calculations only at the second iteration. As we can see, compared to the method in [7], the proposed method in this paper reduces much higher complexity when β = −0.8 with negligible BER performance degradation. Fig.…”

Section: Simulation Resultsmentioning

confidence: 80%

“…Fig. 8 shows the BER performance comparison of the proposed method with the full search MAP detector and method proposed in [7]. The number of outer iterations (turbo decoder iterations), I d is set to 4 and number of inner iterations (MIMO detector iterations), I m is set to 2.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Fig. 9 represents the comparison of complexity between the proposed method with the full search MAP detector and method proposed in [7]. In each iteration the complexity is reduced.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In [7], we proposed a method to reduce the complexity of iterative receiver. The proposed method was based on reducing the complexity of the MIMO detector by setting the threshold, which makes the decision of using the same LLR value or performing the MAP calculations again using the LLR value received from the channel decoder.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of reduced search iterative MIMO detection schemes

Ahmed

Kim

2013

2013 International Conference on ICT Convergence (ICTC)

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This paper presents a complexity reduction method for iterative MIMO detection scheme. We first investigate the statistical characteristics of the log-likelihood ratios (LLRs) across the MIMO detector and decoder, and set a threshold value for the reduced search MIMO detector. Based on this threshold value, the decision is made whether re-estimation of MIMO detection using the soft information provided by the decoder is necessary. This is to eliminate unnecessary repetitive calculation for symbols with high reliability. As iteration goes by, complexity is largely reduced. We compare the performance of the proposed scheme by using maximum likelihood (ML) or maximum a posteriori (MAP). Simulation results show that the proposed complexity reduction method reduces the complexity by about 30% with negligible bit error rate (BER) performance degradation.

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Section: Simulation Resultsmentioning

confidence: 60%

Section: Simulation Resultsmentioning

confidence: 80%

Section: Simulation Resultsmentioning

confidence: 99%

“…Fig. 9 represents the comparison of complexity between the proposed method with the full search MAP detector and method proposed in [7]. In each iteration the complexity is reduced.…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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