A blind adaptive MAP algorithm for the recovery of cochannel signals

Giridhar, K.; Mathur, Abhishek; Shynk, J.J.

doi:10.1109/milcom.1994.473821

Cited by 7 publications

(3 citation statements)

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“…In [74], the authors describe a blind adaptive joint detector. The detector jointly estimates both channel and transmitted data for each signal.…”

Section: Joint Detectionmentioning

confidence: 99%

Joint Demodulation of Low-Entropy Narrowband Cochannel Signals

Meehan¹,

Kragh²,

Clark³

2007

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government.Approved for public release; distribution is unlimited.Reception of one or more signals, overlapping in frequency and time with the desired signal, is commonly called cochannel interference. Joint detection is the optimal minimum probability of error decision rule for cochannel interference. This dissertation investigates the optimum approach and a number of suboptimum approaches to joint detection when a priori information based in fields, or sets of transmitted symbols, is available. In the general case the solution presents itself as a time-varying estimation problem that may be efficiently solved with a modified Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm. The low-entropy properties of a particular signal of interest, the Automatic Identification System (AIS), are presented. Prediction methods are developed for this signal to be used as a priori information for a joint field-based maximum a posteriori (MAP) detector. Advanced joint detection techniques to mitigate cochannel interference are found to have superior bit error rate (BER) performance than can be obtained compared to traditional methods. ABSTRACTReception of one or more signals, overlapping in frequency and time with the desired signal, is commonly called cochannel interference. Joint detection is the optimal minimum probability of error decision rule for cochannel interference. This dissertation investigates the optimum approach and a number of suboptimum approaches to joint detection when a priori information based in fields, or sets of transmitted symbols, is available. In the general case the solution presents itself as a time-varying estimation problem that may be efficiently solved with a modified Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm.

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“…In [74], the authors describe a blind adaptive joint detector. The detector jointly estimates both channel and transmitted data for each signal.…”

Section: Joint Detectionmentioning

confidence: 99%

Joint Demodulation of Low-Entropy Narrowband Cochannel Signals

Meehan¹,

Kragh²,

Clark³

2007

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“…In this way, the accuracy of the gradient value entering the computation of is enhanced. Using the above assumptions, namely, and , the conditional gradient estimates for the th MAP stage are given by (21) yielding the following LMS update for the th conditional channel estimate in the th stage (22) The corresponding unconditional estimate is (23) These summations are defined in a manner similar to that in (8). When -spaced estimators are employed, separate cost functions are defined for the even sample and the odd sample .…”

Section: Joint Blind Mapsd (Jbmapsd) Algorithmmentioning

confidence: 99%

“…Finally, we describe a blind MAP cochannel symbol detector for a priori unknown channels. When implemented as a two-stage structure, this joint blind MAPSD (JBMAPSD) algorithm [23] adaptively computes first the stronger (primary) signal and the corresponding channel estimates. The secondary stage is adapted once the primary coefficients are close to convergence (which is typically about 100-200 samples later).…”

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confidence: 99%

Nonlinear techniques for the joint estimation of cochannel signals

Giridhar

Shynk

Mathur

et al. 1997

IEEE Trans. Commun.

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Cochannel interference occurs when two or more signals overlap in frequency and are present concurrently. Unlike in spread-spectrum multiple-access systems where the different users necessarily share the same channel, cochannel interference is a severe hindrance to frequency-and time-division multipleaccess communications, and is typically minimized by interference rejection/suppression techniques. In this paper, rather than using interference suppression, we are interested in the joint estimation of the information-bearing narrow-band cochannel signals. Novel joint estimators are proposed that employ a singleinput demodulator with oversampling to compensate for timing uncertainties. Assuming finite impulse-response channel characteristics, maximum likelihood (ML) and maximum a posteriori (MAP) criteria are used to derive cochannel detectors of varying complexities and degrees of performance. In particular, a (suboptimal) two-stage joint MAP symbol detector (JMAPSD) is introduced that has a lower complexity than the single-stage estimators while accruing only a marginal loss in error-rate performance at high signal-to-interference ratios. Assuming only reliable estimates of the primary and secondary signal powers, a blind adaptive JMAPSD algorithm for a priori unknown channels is also derived. The performance of these nonlinear joint estimation algorithms is studied through example computer simulations for two cochannel sources.

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