scholarly journals Improved QRD-M Detection Algorithm for Generalized Spatial Modulation Scheme

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaorong Jing ◽  
Mingyue Wang ◽  
Wei Zhou ◽  
Hongqing Liu
Keyword(s):  
Computational Complexity ◽  
Maximum Likelihood ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Spatial Modulation ◽  
Modulation Scheme ◽  
Transmission Scheme ◽  
Imperfect Detection ◽  
Input Multiple Output

Generalized spatial modulation (GSM) is a spectral and energy efficient multiple-input multiple-output (MIMO) transmission scheme. It will lead to imperfect detection performance with relatively high computational complexity by directly applying the original QR-decomposition with M algorithm (QRD-M) to the GSM scheme. In this paper an improved QRD-M algorithm is proposed for GSM signal detection, which achieves near-optimal performance but with relatively low complexity. Based on the QRD, the improved algorithm firstly transforms the maximum likelihood (ML) detection of the GSM signals into searching an inverted tree structure. Then, in the searching process of the M branches, the branches corresponding to the illegitimate transmit antenna combinations (TACs) and related to invalid number of active antennas are cut in order to improve the validity of the resultant branches at each level by taking advantage of characteristics of GSM signals. Simulation results show that the improved QRD-M detection algorithm provides similar performance to maximum likelihood (ML) with the reduced computational complexity compared to the original QRD-M algorithm, and the optimal value of parameter M of the improved QRD-M algorithm for detection of the GSM scheme is equal to modulation order plus one.

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.

scholarly journals Low-Complexity Transmit Antenna Selection in Large-Scale Spatial Modulation Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Peng Wei ◽  
Lu Yin ◽  
Yue Xiao ◽  
Xu He ◽  
Shaoqian Li
Keyword(s):  
Computational Complexity ◽  
System Performance ◽  
Large Scale ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Spatial Modulation ◽  
Transmit Antenna Selection ◽  
Input Multiple Output

Transmit antenna selection (TAS) is an efficient way for improving the system performance of spatial modulation (SM) systems. However, in the case of large-scale multiple-input multiple-output (MIMO) configuration, the computational complexity of TAS in large-scale SM will be extremely high, which prohibits the application of TAS-SM in a real large-scale MIMO system for future 5G wireless communications. For solving this problem, in this paper, two novel low-complexity TAS schemes, named as norm-angle guided subset division (NAG-SD) and threshold-based NAG-SD ones, are proposed to offer a better tradeoff between computational complexity and system performance. Simulation results show that the proposed schemes can achieve better performance than traditional TAS schemes, while effectively reducing the computational complexity in large-scale spatial modulation systems.

scholarly journals Power Scaling for Spatial Modulation with Limited Feedback

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Yue Xiao ◽  
Qian Tang ◽  
Lisha Gong ◽  
Ping Yang ◽  
Zongfei Yang
Keyword(s):  
System Performance ◽  
Multiple Input Multiple Output ◽  
Main Idea ◽  
Limited Feedback ◽  
Low Complexity ◽  
Spatial Diversity ◽  
Spectrum Efficiency ◽  
Spatial Modulation ◽  
Power Scaling ◽  
Input Multiple Output

Spatial modulation (SM) is a recently developed multiple-input multiple-output (MIMO) technique which offers a new tradeoff between spatial diversity and spectrum efficiency, by introducing the indices of transmit antennas as a means of information modulation. Due to the special structure of SM-MIMO, in the receiver, maximum likelihood (ML) detector can be combined with low complexity. For further improving the system performance with limited feedback, in this paper, a novel power scaling spatial modulation (PS-SM) scheme is proposed. The main idea is based on the introduction of scaling factor (SF) for weighting the modulated symbols on each transmit antenna of SM, so as to enlarge the minimal Euclidean distance of modulated constellations and improve the system performance. Simulation results show that the proposed PS-SM outperforms the conventional adaptive spatial modulation (ASM) with the same feedback amount and similar computational complexity.

scholarly journals Parallel Complex Quadrature Spatial Modulation

2020 ◽  
Vol 11 (1) ◽  
pp. 330
Author(s):  
Sheriff Murtala ◽  
Nishal Muchena ◽  
Tasnim Holoubi ◽  
Manar Mohaisen ◽  
Kang-Sun Choi
Keyword(s):  
Bit Error Rate ◽  
Spectral Efficiency ◽  
Multiple Input Multiple Output ◽  
Spatial Modulation ◽  
Transmission Scheme ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Transmission ◽  
And Performance ◽  
Ber Performance

In this paper, we propose a new multiple-input multiple-output (MIMO) transmission scheme, called parallel complex quadrature spatial modulation (PCQSM). The proposed technique is based on the complex quadrature spatial modulation (CQSM) to further increase the spectral efficiency of the communication system. CQSM transmits two different complex symbols at each channel use. In contrast with CQSM, the new transmission scheme splits the transmit antennas into groups, and modulates the two signal symbols using the conventional CQSM before transmission. Based on the selected modulation order and the number of possible groups that can be realized, the incoming bits modulate the two signal symbols and the indices of the transmit antennas in each group. We demonstrated that while the complexity and performance of the proposed scheme is the same as that of CQSM, the number of required transmit antennas is significantly reduced. The proposed PCQSM achieves such a benefit without requiring any additional radio frequency (RF) chains. The results obtained from Monte Carlo simulation showed that at a Bit Error Rate (BER) of 10−4, the performance of the PCQSM with two antenna groups closely matches that of CQSM, and outperformed quadrature spatial modulation (QSM) and parallel quadrature spatial modulation (PQSM) by over 0.7 dB. As the number of antenna groups increased to 4, the BER performance of PCQSM with reduced number of transmit antenna and modulation order matches that of QSM. The BER of the proposed scheme using maximum likelihood (ML) receiver is also analyzed theoretically and compared with the BER obtained via simulations.

scholarly journals OFDM-Based Generalized Optical MIMO

2020 ◽  
Author(s):  
Chen Chen ◽  
Xin Zhong ◽  
Shu Fu ◽  
Xin Jian ◽  
Min Liu ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Orthogonal Frequency Division Multiplexing ◽  
Direct Detection ◽  
Multiple Input Multiple Output ◽  
Detection Algorithm ◽  
Spatial Multiplexing ◽  
Spatial Modulation ◽  
Input Multiple Output ◽  
The Time Domain

<p>The combination of multiple-input multiple-output (MIMO) transmission and orthogonal frequency division multiplexing (OFDM) modulation has been shown to be an effective way to substantially enhance the capacity of bandlimited optical wireless communication (OWC) systems. In this paper, we propose four OFDM-based generalized optical MIMO techniques for intensity modulation/direct detection (IM/DD) OWC systems, including OFDM-based frequency-domain generalized spatial modulation (FD-GSM), frequency-domain generalized spatial multiplexing (FD-GSMP), time-domain generalized spatial modulation (TD-GSM) and time-domain generalized spatial multiplexing (TD-GSMP). For OFDM-based FD-GSM and FDGSMP, spatial mapping is performed in the frequency domain, while it is carried out in the time domain for OFDM-based TDGSM and TD-GSMP. To efficiently estimate both spatial and constellation symbols in each OFDM-based generalized optical MIMO technique, a corresponding maximum-likelihood (ML) detection algorithm is designed. Extensive simulations are conducted to evaluate and compare the performance of the proposed four OFDM-based generalized optical MIMO techniques in a typical indoor environment. Simulation results demonstrate the superiority of OFDM-based TD-GSM and TD-GSMP for various spectral efficiencies of 4, 5 and 6 bits/s/Hz, when a relatively high secondary direct current (DC) bias is adopted.</p>

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 Robust Hybrid Iterative Linear Detector for Massive MIMO Uplink Systems

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 306 ◽  
Author(s):  
Mahmoud A. Albreem ◽  
Mohammed H. Alsharif ◽  
Sunghwan Kim
Keyword(s):  
Computational Complexity ◽  
Convergence Rate ◽  
Massive Mimo ◽  
High Performance ◽  
Large Scale ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Initial Vector ◽  
High Data

Fifth-generation (5G) communications system is commercially introduced by several mobile operators where sub-6 GHz bands are the backbone of the 5G networks. A large-scale multiple-input multiple-output (MIMO), or massive MIMO (mMIMO), technology has a major impact to secure high data rate, high spectral efficiency, and quality of service (QoS). It could also have a major role in the beyond-5G systems. A massive number of antennas seek advanced signal processing to detect and equalize the signal. However, optimal detectors, such as the maximum likelihood (ML) and maximum posterior (MAP), are not desirable in implementation due to extremely high complexity. Therefore, sub-optimum solutions have been introduced to obtain and guarantee enough balance between the performance and the computational complexity. In this paper, a robust and joint low complexity detection algorithm is proposed based on the Jacobi (JA) and Gauss–Seidel (GS) methods. In such iterative methods, the performance, complexity, and convergence rate are highly dependent on the initial vector. In this paper, initial solution is proposed by exploiting the benefits of a stair matrix to obtain a fast convergence rate, high performance, and low complexity. Numerical results show that proposed algorithm achieves high accuracy and relieve the computational complexity even when the BS-to-user-antenna ratio (BUAR) is small.

scholarly journals Impact of Stair and Diagonal Matrices in Iterative Linear Massive MIMO Uplink Detectors for 5G Wireless Networks

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 71 ◽  
Author(s):  
Mahmoud A. Albreem ◽  
Mohammed H. Alsharif ◽  
Sunghwan Kim
Keyword(s):  
Computational Complexity ◽  
Iterative Methods ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Matrix Inversion ◽  
Multiple Input ◽  
The Matrix ◽  
Input Multiple Output ◽  
The Impact

In massive multiple-input multiple-output (M-MIMO) systems, a detector based on maximum likelihood (ML) algorithm attains optimum performance, but it exhaustively searches all possible solutions, hence, it has a very high complexity and realization is denied. Linear detectors are an alternative solution because of low complexity and simplicity in implementation. Unfortunately, they culminate in a matrix inversion that increases the computational complexity in high loaded systems. Therefore, several iterative methods have been proposed to approximate or avoid the matrix inversion, such as the Neuamnn series (NS), Newton iterations (NI), successive overrelaxation (SOR), Gauss–Siedel (GS), Jacobi (JA), and Richardson (RI) methods. However, a detector based on iterative methods requires a pre-processing and initialization where good initialization impresses the convergence, the performance, and the complexity. Most of the existing iterative linear detectors are using a diagonal matrix ( D ) in initialization because the equalization matrix is almost diagonal. This paper studies the impact of utilizing a stair matrix ( S ) instead of D in initializing the linear M-MIMO uplink (UL) detector. A comparison between iterative linear M-MIMO UL detectors with D and S is presented in performance and computational complexity. Numerical Results show that utilization of S achieves the target performance within few iterations, and, hence, the computational complexity is reduced. A detector based on the GS and S achieved a satisfactory bit-error-rate (BER) with the lowest complexity.

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