L
Lajos Hanzo
Researcher at University of Southampton
Publications - 2188
Citations - 69620
Lajos Hanzo is an academic researcher from University of Southampton. The author has contributed to research in topics: Bit error rate & MIMO. The author has an hindex of 101, co-authored 2040 publications receiving 54380 citations. Previous affiliations of Lajos Hanzo include University of New South Wales & Beihang University.
Papers
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Adaptive-TTCM-Aided Near-Instantaneously Adaptive Dynamic Network Coding for Cooperative Cognitive Radio Networks
TL;DR: It was found that the joint holistic design of the ATTCM-ADNC-CCR scheme is either capable of freeing up an approximately 40% of the PU's bandwidth in comparison to its noncooperative counterpart or increasing the attainable throughput by 2 bits/symbol.
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A turbo-coded burst-by-burst adaptive wide-band speech transceiver
TL;DR: The proposed joint adaptation of source- codec, channel-codec, and modulation regime results in attractive, robust, high-quality audio systems, capable of conveying near-unimpaired wide-band audio signals over fading dispersive channels for signal-to-noise ratios (SNR) in excess of about 5 dB.
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Iterative Receiver Design for Polar-Coded SCMA Systems
TL;DR: An edge-cancellation-aided iterative detection and decoding algorithm is proposed for polar-coded sparse code multiple access (SCMA), which jointly performs Gaussian-approximated message passing (GA-MP) detection of SCMA supported by the soft list decoding of polar codes.
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Channel Feedback Codebook Design for Millimeter-Wave Massive MIMO Systems Relying on Lens Antenna Array
TL;DR: This letter proposes a reduced-dimensional subspace codebook (RDSC) for LAA-aided mmWave systems and carries out mathematical performance analysis of the proposed RDSC and shows that its feedback overhead is rendered proportional to the relatively small number of dominant paths per user.
Joint Detection CDMA Techniques for Third-generation Transceivers
E.L. Kuan,Lajos Hanzo +1 more
TL;DR: The optimum multiuser detector was proposed and analyzed by Verd u [1] for an asynchronous Gaussian channel and consisted of a bank of matched lters followed by the Viterbi algorithm to detect the most likely sequence transmitted by K users.