Soft-decision equalizers for in-service error rate monitoring

Cid-Sueiro, J.; San‐José‐Revuelta, Luis M.; Figueiras-Vidal, Anı́bal R.

doi:10.1016/s0165-1684(00)00061-x

Cited by 7 publications

(2 citation statements)

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“…This approach offers notable capabilities, such as efficient implementation, possibility to include procedures to reduce complexity, and on-line performance monitoring via in-service blind Bit Error Rate (BER) estimation. This paper expands upon previous work of the author on Bayesian single-and multi-user detectors for wireless communications, specifically, the simple method proposed in [30], which was based on the assumption of a memoryless detector and the survival of only the fittest hypothesis (see Section III-A), and the work on Bayesian single-user equalizers [32][33][34].…”

Section: Introductionmentioning

confidence: 74%

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Hypotheses Control-based Strategies for the Development of Near-optimum Bayesian Detectors for CDMA Systems

San‐José‐Revuelta

2007

J VLSI Sign Process Syst Sign Im

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This paper deals with the development of a new family of simplification procedures that can be applied to those communications problems analyzed using the Bayesian formulation. Specifically, our work focuses on near-optimum Bayesian multiuser detectors for synchronous DS/CDMA systems. The complexity of the theoretical Bayesian approach grows exponentially with both the number of active users and the number of symbols received, constituting, this way, not a viable detection solution. Therefore, the development of suboptimal algorithms by making use of a new set of simplifications strategies becomes a crucial issue to be addressed. In this work, a global framework for multiuser Bayesian equalization is first established by developing a general algorithm suitable for blind (non-data-aided) communications scenarios. Afterwards, a group of simplification techniques is introduced and, finally, the performance is evaluated and compared to that of the most well-known traditional multiuser detectors.

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Section: Introductionmentioning

confidence: 74%

“…Next, the decorrelator detector offers an intermediate trade-off between computational load and efficiency. The Bayesian approach shows very good BER figures and also offers the capability of non-data-aided on-line BER estimation, which can be of much interest in many applications [32,33].…”

Section: Near-far Performancementioning

confidence: 99%