A New Low-Complexity Near-ML Detection Algorithm for Spatial Modulation

2013 ◽  
Vol 2 (1) ◽  
pp. 90-93 ◽  
Author(s):  
Qian Tang ◽  
Yue Xiao ◽  
Ping Yang ◽  
Qiaoling Yu ◽  
Shaoqian Li
Keyword(s):  
Low Complexity ◽  
Detection Algorithm ◽  
Spatial Modulation ◽  
Ml Detection

Low-Complexity Soft-ML Detection Algorithm for Modified-DCM in WiMedia UWB Systems

2013 ◽  
Vol E96.B (3) ◽  
pp. 910-913 ◽  
Author(s):  
Kilhwan KIM ◽  
Jangyong PARK ◽  
Jihun KOO ◽  
Yongsuk KIM ◽  
Jaeseok KIM
Keyword(s):  
Low Complexity ◽  
Detection Algorithm ◽  
Ml Detection

Low-Complexity ML Detection for Spatial Modulation MIMO With APSK Constellation

2015 ◽  
Vol 64 (9) ◽  
pp. 4315-4321 ◽  
Author(s):  
Cong Li ◽  
Yuzhen Huang ◽  
Marco Di Renzo ◽  
Jinlong Wang ◽  
Yunpeng Cheng
Keyword(s):  
Low Complexity ◽  
Spatial Modulation ◽  
Ml Detection

scholarly journals Fast Scalable Architecture of a Near-ML Detector for a MIMO-QSM Receiver

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1509 ◽  
Author(s):  
Ismael Lopez ◽  
L. Pizano-Escalante ◽  
Joaquin Cortez ◽  
O. Longoria-Gandara ◽  
Armando Garcia
Keyword(s):  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Spatial Modulation ◽  
Impact Performance ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Receiver Performance ◽  
Limited Precision ◽  
Numerical Precision

This paper presents a proposal for an architecture in FPGA for the implementation of a low complexity near maximum likelihood (Near-ML) detection algorithm for a multiple input-multiple output (MIMO) quadrature spatial modulation (QSM) transmission system. The proposed low complexity detection algorithm is based on a tree search and a spherical detection strategy. Our proposal was verified in the context of a MIMO receiver. The effects of the finite length arithmetic and limited precision were evaluated in terms of their impact on the receiver bit error rate (BER). We defined the minimum fixed point word size required not to impact performance adversely for n T transmit antennas and n R receive antennas. The results showed that the proposal performed very near to optimal with the advantage of a meaningful reduction in the complexity of the receiver. The performance analysis of the proposed detector of the MIMO receiver under these conditions showed a strong robustness on the numerical precision, which allowed having a receiver performance very close to that obtained with floating point arithmetic in terms of BER; therefore, we believe this architecture can be an attractive candidate for its implementation in current communications standards.

An Improved MIMO-OFDM Detection Algorithm Based on OSIC

2014 ◽  
Vol 696 ◽  
pp. 201-206
Author(s):  
Da Jiang Yang ◽  
Zi Fa Zhong
Keyword(s):  
Signal Detection ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Optimal Detection ◽  
Ofdm Signal ◽  
Mimo Ofdm ◽  
Ml Detection ◽  
Improved Algorithm

This paper proposes a MIMO-OFDM signal detection algorithm with joint ML and MMSE-OSIC based on researches of ML algorithm and MMSE-OSIC algorithm. This kind of algorithm is an improved algorithm of MMSE-OSIC. Comparing to the traditional MMSE-OSIC algorithm, this algorithm uses ML detection on the relatively weaker signal layer. According to the experiment, it was found close to the optimal detection performance, much less complicated than the ML algorithm, which is a near-optimal and low-complexity MIMO-OFDM detection algorithm.

A Single Symbol Maximum-Likehood Decoder for Four Transimit Antenna QOSTBC

2013 ◽  
Vol 427-429 ◽  
pp. 1502-1505
Author(s):  
Nai Qian Zhang ◽  
Li Biao Jin ◽  
Guo Cheng Wu ◽  
Jie Cong Lin
Keyword(s):  
Block Code ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Modulation Scheme ◽  
Time Block ◽  
Orthogonal Space ◽  
Symbol Detection ◽  
Single Complex ◽  
High Level ◽  
Ml Detection

This letter proposes a very low-complexity maximum likelihood (ML) detection algorithm for the quasi-orthogonal space-time block code (QOSTBC) with four transmits antennas. The low-complexity single-complex-symbol detection is based on QR decomposition and the expansion of equalization via a diagonal matrix transformation. The proposed strategy enables the QOSTBC to achieve ML performance with significant reduction in computational load for any high-level modulation scheme.

Sign in / Sign up

Export Citation Format

Share Document