scholarly journals Simplified QR-decomposition based and lattice reduction-assisted multi-user multiple-input–multiple-output precoding scheme

2016 ◽  
Vol 10 (5) ◽  
pp. 586-593 ◽  
Author(s):  
Shu Fang ◽  
Zong-di Yue ◽  
Chengyi Lu ◽  
Yuan-chao Han ◽  
Jian Wu
Keyword(s):  
Multiple Input Multiple Output ◽  
Qr Decomposition ◽  
Lattice Reduction ◽  
Multiple Input ◽  
Input Multiple Output

Lattice Reduction Algorithm Based Uplink MC-CDMA

2015 ◽  
Vol 738-739 ◽  
pp. 391-396
Author(s):  
Umut Yunus ◽  
Askar Hamdulla ◽  
Zhen Hong Jia ◽  
Kurban Ubul
Keyword(s):  
Communication Systems ◽  
Multiple Access ◽  
Multiple Input Multiple Output ◽  
Lattice Reduction ◽  
Rate Performance ◽  
Multiple Input ◽  
High Spectral Efficiency ◽  
Input Multiple Output ◽  
Cdma Systems ◽  
Multi Access

MC-CDMA integrates the advantages of OFDM with those of CDMA, it has high spectral efficiency, robustness against multi-path propagation and multiple access flexibility. Due to the above mentioned merits, it has been considered as a candidate for future wireless. In recent years, lattice reduction technique is discussed in multiple input multiple output communication systems, and has been shown with its better performance. The purpose of this paper is to express a model for uplink MC-CDMA systems in matrix form and then to propose a lattice reduction aided multiuser detection, in order to ameliorate the affects of inter-carrier interference and multi access interference. The effectiveness of the proposed method is evaluated by the bit error rate performance.

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.

scholarly journals Early Neighbor Rejection-Aided Tabu Search Detection for Large MIMO Systems

2021 ◽  
Vol 11 (16) ◽  
pp. 7305
Author(s):  
Uzokboy Ummatov ◽  
Jin-Sil Park ◽  
Gwang-Jae Jang ◽  
Ju-Dong Lee
Keyword(s):  
Computational Complexity ◽  
Tabu Search ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Qr Decomposition ◽  
Efficient Computation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ordering Schemes

In this study, a low complexity tabu search (TS) algorithm for multiple-input multiple-output (MIMO) systems is proposed. To reduce the computational complexity of the TS algorithm, early neighbor rejection (ENR) and layer ordering schemes are employed. In the proposed ENR-aided TS (ENR-TS) algorithm, the least promising k neighbors are excluded from the neighbor set in each layer, which reduces the computational complexity of neighbor examination in each TS iteration. For efficient computation of the neighbors’ metrics, the ENR scheme can be incorporated into QR decomposition-aided TS (ENR-QR-TS). To further reduce the complexity and improve the performance of the ENR-QR-TS scheme, a layer ordering scheme is employed. The layer ordering scheme determines the order in which layers are detected based on their expected metrics, which reduces the risk of excluding likely neighbors in early layers. The simulation results show that the ENR-TS achieves nearly the same performance as the conventional TS while providing up to 82% complexity reduction.

scholarly journals A CORDIC based QR Decomposition Technique for MIMO Detection

2018 ◽  
Vol 8 (5) ◽  
pp. 2731
Author(s):  
Shirly Edward A. ◽  
Malarvizhi S.
Keyword(s):  
Complexity Analysis ◽  
Multiple Input Multiple Output ◽  
Qr Decomposition ◽  
Mimo Detection ◽  
Hardware Complexity ◽  
Channel Matrix ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Processing Techniques ◽  
Complex Channel

CORDIC based improved real and complex QR Decomposition (QRD) for channel pre-processing operations in (Multiple-Input Multiple-Output) MIMO detectors are presented in this paper. The proposed design utilizes pipelining and parallel processing techniques and reduces the latency and hardware complexity of the module respectively. Computational complexity analysis report shows the superiority of our module by 16% compared to literature. The implementation results reveal that the proposed QRD takes shorter latency compared to literature. The power consumption of 2x2 real channel matrix and 2x2 complex channel matrix was found to be 12mW and 44mW respectively on the state-of-the-art Xilinx Virtex 5 FPGA.

Sign in / Sign up

Export Citation Format

Share Document