Combined QRD-M and Successive Interference Cancellation Detection Algorithm for MIMO Systems

2014 ◽  
Vol 556-562 ◽  
pp. 2834-2837
Author(s):  
Li Liu ◽  
Xin Song ◽  
Ying Hua Han ◽  
Fu Lai Liu ◽  
Jin Kuan Wang
Keyword(s):  
Interference Cancellation ◽  
Mimo Systems ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Successive Interference Cancellation ◽  
Candidate Sequence ◽  
Trade Off ◽  
Simulation Results

In order to get better trade-off between detection performance and calculating complexity, an improved detection algorithm was presented here. QRD-M algorithm is performed for several layers firstly, and successive interference cancellation detection algorithm was used to detect the bottom several layers parallel, and the candidate sequence with smaller PAM was selected out as the answer. Simulation results show the validity of proposed algorithm.

Sorted QR-Decomposition Based Parallel Detection Algorithm for MIMO Systems

2013 ◽  
Vol 427-429 ◽  
pp. 591-595
Author(s):  
Li Liu ◽  
Jin Kuan Wang ◽  
Xin Song ◽  
Ying Hua Han ◽  
Dong Mei Yan
Keyword(s):  
Maximum Likelihood ◽  
Interference Cancellation ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
Detection Performance ◽  
System Capacity ◽  
Parallel Detection ◽  
Ml Detection

Multiple input multiple output (MIMO) wireless communication system can increase system capacity enormously. Maximum likelihood (ML) detection algorithm can obtain the optimal detection performance with exponential computational complexity that results it difficulty to use in practice. Classical ordered successive interference cancellation (SIC) algorithm suffers from error propagation and high complexity, so an improved parallel SIC algorithm based on Maximum likelihood (ML) detection is proposed, in which signal detection is performed at two stages. ML detections for one layer is carried out firstly, and redundancy of candidate sequences are selected to perform parallel detection for improving detection performance for next step. Sorted QR decomposition based SIC algorithm are performed in second step in order to reduce calculating complexity. By adjusting the number of candidate sequences, tradeoff between detection performance and calculating complexity can be obtained properly.

Study of BLAST Signal Detection Algorithm in LTE System

2013 ◽  
Vol 756-759 ◽  
pp. 3183-3188
Author(s):  
Tao Lei ◽  
Deng Ping He ◽  
Fang Tang Chen
Keyword(s):  
Signal Detection ◽  
High Speed ◽  
Data Communication ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Detection Algorithms ◽  
High Speed Data ◽  
Simulation Results ◽  
Better Than

BLAST can achieve high speed data communication. Its signal detection directly affects performance of BLAST receiver. This paper introduced several signal detection algorithmsZF algorithm, MMSE algorithm, ZF-SIC algorithm and MMSE-SIC algorithm. The simulation results show that the traditional ZF algorithm has the worst performance, the traditional MMSE algorithm and the ZF-SIC algorithm is similar, but with the increase of the SNR, the performance of ZF-SIC algorithm is better than MMSE algorithm. MMSE-SIC algorithm has the best detection performance in these detection algorithms.

Performance of OQAM/GFDM in Spatial Multiplexing MIMO Systems

2020 ◽  
Vol 11 (2) ◽  
pp. 39-57
Author(s):  
Simon Wissam Tarbouche ◽  
Abdel-Nasser Assimi
Keyword(s):  
Interference Cancellation ◽  
Pulse Shaping ◽  
Matched Filter ◽  
Mimo Systems ◽  
Mimo System ◽  
Spatial Multiplexing ◽  
Frequency Division ◽  
Fifth Generation ◽  
Additional Processing ◽  
Simulation Results

Generalized frequency division multiplexing (GFDM) is a prominent candidate to be used by the mobile Fifth Generation (5G) physical layer. Nevertheless, the integration of GFDM with Spatial Multiplexing (SM) MIMO system is essential to fulfill the data rate requirements. SM detection of MIMO-GFDM becomes a more challenging topic because of ICI and ISI due to the non-orthogonal nature of GFDM, along with IAI. In this article, the authors propose a system that combines the Offset-Quadrature Amplitude Modulation (OQAM) with GFDM to mitigate self-induced interference, by using a simple Matched Filter (MF) detector and minimum additional processing at the receiver. Simulation results show a considerable achieved improvement in BER by the proposed OQAM/GFDM compared to QAM/GFDM when using MMSE-based Ordered Successive Interference Cancellation (OSIC) detector. Furthermore, this system is unaffected by the roll-off factor variations of used pulse-shaping filters.

Depth-First QRD-M Detection Algorithm for MIMO Systems

2013 ◽  
Vol 347-350 ◽  
pp. 3478-3481
Author(s):  
Li Liu ◽  
Jin Kuan Wang ◽  
Xin Song ◽  
Yin Hua Han ◽  
Yu Huan Wang
Keyword(s):  
Ordered Set ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
Detection Performance ◽  
Detection Scheme ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ml Detection

Maximum likelihood (ML) detection algorithm for multiple input multiple output (MIMO) systems provided the best bit error rate (BER) performance with heavy calculating complexity. The use of QR decomposition with M-algorithm (QRD-M) had been proposed to provide near-ML detection performance and lower calculating complexity. However, its complexity still grew exponentially with increasing dimension of the transmitted signal. To reduce the problem, an improved detection scheme was proposed here. After constructing the tree detecting model of MIMO systems, the ML search of one layer was done, the branch metrics were calculated and sorted, which gave an ordered set of the layer, then depth-first search were used to search the left layers with termination methods. The proposed algorithm provides near QRD-M detection performance.

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