Asymptotically optimal blind fusion of bit estimates

In wireless communications, it is often desirable to merge bit decisions from multiple receivers to improve overall link performance. It is well known that in order to optimally fuse bit decisions from a network of receivers, precise knowledge of receiver bit error rates (BERs) is needed. This information, however, is rarely available in practice. In this work, we present an iterative procedure for blindly estimating receivers BERs to enable near optimal blind fusion of bit decisions in a multi-receiver network. We show that the solution of the estimation problem is a structured eigenvalue task and propose a modified power method procedure to perform it. We prove that the desired solution is a stable point of the algorithm and the algorithm is locally stable. Furthermore, we show via simulations that the technique results in excellent performance in nearly all practical operating scenarios.

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“…Furthermore, in [3] it was shown that the estimates derived in [2] are the maximum likelihood estimates (MLEs) of the receiver BERs.…”

Section: The Modified Power Methods Algorithmmentioning

confidence: 99%

Blind estimation of channel BERs in a multi-receiver network

Dixit

Douglas

Orsak

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing

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Performance Analysis of Optimal Blind Fusion of Bits

Delmas¹,

Meurisse²

2007

IEEE Trans. Signal Process.

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Abstract-This paper is devoted to a statistical performance analysis of blind estimation of bit error rates (BERs) of a bank of detectors, using empirical estimation algorithms that have appeared in the literature (by Dixit et al.). In particular, we prove that these blind estimators asymptotically (in the number of observed bits) achieve the accuracy obtained with perfect knowledge of the transmitted bits. We propose a maximum-likelihood solution which follows from the standard expectation-maximization (EM) algorithm, considered to be a reference algorithm. Finally, the optimal fusion rule is revisited and our theoretical results are compared to Monte Carlo simulations.Index Terms-Fusion of bits, performance analysis, expectationmaximization (EM) algorithm.

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Noise-Enhanced Blind Multiple Error Rate Estimators in Wireless Relay Networks

Liu

2012

IEEE Trans. Veh. Technol.

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Asymptotically optimal blind fusion of bit estimates

Cited by 3 publications

References 4 publications

Blind estimation of channel BERs in a multi-receiver network

Blind estimation of channel BERs in a multi-receiver network

Performance Analysis of Optimal Blind Fusion of Bits

Noise-Enhanced Blind Multiple Error Rate Estimators in Wireless Relay Networks

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