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In this paper, Sphere Decoding (SD) algorithms for Spatial Modulation (SM) are developed to reduce the computational complexity of Maximum-Likelihood (ML) detectors. Two SDs specifically designed for SM are proposed and analysed in terms of…

Information Theory · Computer Science 2013-05-31 Abdelhamid Younis , Sinan Sinanović , Marco Di Renzo , Raed Mesleh , Harald Haas

A complexity-adaptive tree search algorithm is proposed for $\boldsymbol{G}_N$-coset codes that implements maximum-likelihood (ML) decoding by using a successive decoding schedule. The average complexity is close to that of the successive…

Information Theory · Computer Science 2021-09-03 Peihong Yuan , Mustafa Cemil Coşkun

Sphere decoding (SD) of polar codes is an efficient method to achieve the error performance of maximum likelihood (ML) decoding. But the complexity of the conventional sphere decoder is still high, where the candidates in a target sphere…

Information Theory · Computer Science 2013-08-14 Kai Niu , Kai Chen , Jiaru Lin

Low-complexity precoding {algorithms} are proposed in this work to reduce the computational complexity and improve the performance of regularized block diagonalization (RBD) {based} precoding {schemes} for large multi-user {MIMO} (MU-MIMO)…

Information Theory · Computer Science 2013-04-25 Keke Zu , Rodrigo C. de Lamare , Martin Haardt

We consider the problem of designing a low-complexity decoder for antipodal uniquely decodable (UD) /errorless code sets for overloaded synchronous code-division multiple access (CDMA) systems, where the number of signals Kamax is the…

Signal Processing · Electrical Eng. & Systems 2022-05-11 Michel Kulhandjian , Claude D'Amours , Hovannes Kulhandjian , Halim Yanikomeroglu , Dimitris A. Pados , Gurgen Khachatrian

We present a low-complexity and low-latency decoding algorithm for a class of Reed-Muller (RM) subcodes that are defined based on the product of smaller RM codes. More specifically, the input sequence is shaped as a multi-dimensional array,…

Information Theory · Computer Science 2022-02-09 Mohammad Vahid Jamali , Mohammad Fereydounian , Hessam Mahdavifar , Hamed Hassani

Reed-Muller (RM) codes are known for their good maximum likelihood (ML) performance in the short block-length regime. Despite being one of the oldest classes of channel codes, finding a low complexity soft-input decoding scheme is still an…

Information Theory · Computer Science 2021-07-19 Marvin Geiselhart , Ahmed Elkelesh , Moustafa Ebada , Sebastian Cammerer , Stephan ten Brink

The computational complexity of the Maximum Likelihood decoding algorithm in [1], [2] for orthogonal space-time block codes is smaller than specified.

Information Theory · Computer Science 2009-08-08 Ender Ayanoglu

In this paper, we propose an optimal but low-complexity optimization method for nonsquare differential massive MIMO. While a discrete nonlinear optimization is required for the conventional nonsquare differential coding, we newly modify it…

Signal Processing · Electrical Eng. & Systems 2023-05-29 Yuma Katsuki , Naoki Ishikawa

In this work, a new fast-decodable space-time block code (STBC) is proposed. The code is full-rate and full-diversity for 4x2 multiple-input multiple-output (MIMO) transmission. Due to the unique structure of the codeword, the proposed code…

Information Theory · Computer Science 2014-01-08 Ming Liu , Maryline Hélard , Jean-François Hélard , Matthieu Crussière

This letter introduces two fast maximum-likelihood (ML) detection methods for 4*4 quasi-orthogonal space-time block code (QOSTBC). The first algorithm with a relatively simple design exploits structure of quadrature amplitude modulation…

Information Theory · Computer Science 2017-06-14 Adel Ahmadi , Siamak Talebi

We describe two implementations of the optimal error correction algorithm known as the maximum likelihood decoder (MLD) for the 2D surface code with a noiseless syndrome extraction. First, we show how to implement MLD exactly in time…

Quantum Physics · Physics 2014-10-01 Sergey Bravyi , Martin Suchara , Alexander Vargo

Spatial Modulation (SM) is a recently developed low-complexity Multiple-Input Multiple-Output scheme that uses antenna indices and a conventional signal set to convey information. It has been shown that the Maximum-Likelihood (ML) detection…

Information Theory · Computer Science 2013-01-17 Rakshith Rajashekar , K. V. S. Hari

Reed-Muller (RM) codes are known for their good maximum likelihood (ML) performance in the short block-length regime. Despite being one of the oldest classes of channel codes, finding a low complexity soft-input decoding scheme is still an…

Information Theory · Computer Science 2021-07-28 Marvin Geiselhart , Ahmed Elkelesh , Moustafa Ebada , Sebastian Cammerer , Stephan ten Brink

This paper considers the average complexity of maximum likelihood (ML) decoding of convolutional codes. ML decoding can be modeled as finding the most probable path taken through a Markov graph. Integrated with the Viterbi algorithm (VA),…

Information Theory · Computer Science 2016-11-17 Jie Luo

In this paper, we propose a fast decoder algorithm for uniquely decodable (errorless) code sets for overloaded synchronous optical code-division multiple-access (O-CDMA) systems. The proposed decoder is designed in a such a way that the…

Information Theory · Computer Science 2019-02-27 Michel Kulhandjian , Hovannes Kulhandjian , Claude D'Amours , Halim Yanikomeroglu , Gurgen Khachatrian

Sphere decoding (SD) is a low complexity maximum likelihood (ML) detection algorithm, which has been adapted for different linear channels in digital communications. The complexity of the SD has been shown to be exponential in some cases,…

Information Theory · Computer Science 2007-07-13 Luay Azzam , Ender Ayanoglu

In this paper, we investigate symbol-level precoding (SLP) and efficient decoding techniques for downlink transmission, where we focus on scenarios where the base station (BS) transmits multiple QAM constellation streams to users equipped…

Signal Processing · Electrical Eng. & Systems 2024-10-30 X. Tong , A. Li , L. Lei , X. Hu , F. Dong , S. Chatzinotas , C. Masouros

In this paper, a derandomized algorithm for sampling decoding is proposed to achieve near-optimal performance in lattice decoding. By setting a probability threshold to sample candidates, the whole sampling procedure becomes deterministic,…

Information Theory · Computer Science 2016-11-17 Zheng Wang , Shuiyin Liu , Cong Ling

Multiple-input multiple-output (MIMO) systems have been widely acclaimed in order to provide high data rates. Recently Lattice Reduction (LR) aided detectors have been proposed to achieve near Maximum Likelihood (ML) performance with low…

Information Theory · Computer Science 2016-02-22 Mehnaz Rahman , Gwan S. Choi