Mikalai Kisialiou

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Despite its optimal bit-error-rate (BER) performance, the maximum-likelihood (ML) detection is known to be NP-hard and suffers from high computational complexity. The currently popular suboptimal detectors either achieve a polynomial time complexity at the expense of BER performance degradation (e.g., MMSE Detector), or offer a near ML performance with a(More)
In this paper we develop two quasi-maximum likelihood (ML) channel detectors for multiuser detection: semidefinite relaxation (SDR) detector and phase-shift-keying (PSK) detector. These detectors can deliver near-ML bit error rate (BER) performance with a polynomial worst-case complexity. The SDR detector for binary-phase-shift-keying (BPSK) constellation(More)
We develop a computationally efficient and memory efficient approach to (near) maximum a posteriori probability demodulation for MIMO systems with QPSK signalling, based on semidefinite relaxation. Existing approaches to this problem require either storage of a large list of candidate bit-vectors, or the solution of multiple binary quadratic problems. In(More)
Two efficient list-based “soft”-output demodulators are developed for iterative receivers in multiple-input multiple-output (MIMO) communication systems with QPSK signaling. The proposed demodulators are based on the semidefinite relaxation (SDR) technique, and hence their computational costs are bounded by a low-order polynomial of the number(More)
Blind signal detection in multi-user CDMA system is particularly attractive when only the desired user signature is known to a given receiver. A problem common to several existing blind multi-user CDMA detectors is that the detection performance is very sensitive to the Signature Waveform Mismatch (SWM) which may be caused by channel distortion. In this(More)
Existing approaches to the maximum-likelihood (ML) detection problem in digital communications either suffer from exponential complexity (e.g. sphere decoder and its variants) or exhibit significant bit-error-rate (BER) degradation (e.g. LMMSE detector). In this paper we present an efficient implementation of a semi-definite relaxation-based detector (SDR(More)
We study the role of information feedback for the problem of distributed signal tracking/estimation using a sensor network with a fusion center. Assuming that the fusion center has sufficient energy to reliably feed back its intermediate estimates, we show that the sensors can substantially reduce their power consumption by using the feedback information in(More)