scholarly journals A Low-Complexity and High-Decoding Performance Scheme for the MIMO-SCMA System

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenping Ge ◽  
Haofeng Zhang ◽  
Shiqing Qian ◽  
Lili Ma ◽  
Gecheng Zhang
Keyword(s):  
Error Rate ◽  
Message Passing ◽  
Multiple Input Multiple Output ◽  
High Capacity ◽  
Block Code ◽  
Low Complexity ◽  
Spectrum Efficiency ◽  
Performance Loss ◽  
Message Passing Algorithm ◽  
Input Multiple Output

Sparse code multiple access (SCMA) has been proposed to obtain high capacity and support massive connections. When combined with the multiple-input multiple-output (MIMO) techniques, the spectrum efficiency of the SCMA system can be further improved. However, the detectors of the MIMO-SCMA system have high computational complexity. For the maximum likelihood (ML) detection, though it is optimal decoding algorithm for the MIMO-SCMA system, the detection complexity would grow exponentially with the number of both the antennas and users increase. In this paper, we consider a space-time block code (STBC) based MIMO-SCMA system where SCMA is used for multiuser access. Besides, we propose a low-complexity utilizing joint message passing algorithm (JMPA) detection, which narrowing the range of superimposed constellation points, called joint message passing algorithm based on sphere decoding (S-JMPA). But for the S-JMPA detector, the augment of the amount of access users and antennas leads to the degradation of decoding performance, the STBC is constructed to compensate the performance loss of the S-JMPA detector and ensure good bit error rate (BER) performance. The simulation results show that the proposed method achieves a close error rate performance to ML, JMPA, and a fast convergence rate. Moreover, compared to the ML detector, it also significantly reduces the detection complexity of the algorithms.

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 Low-Complexity Joint Weighted Neumann Series and Gauss-Seidel Soft-Output Detection  for Massive MIMO Systems

2021 ◽  
Author(s):  
Xiaoming Dai ◽  
Tiantian Yan ◽  
Yuanyuan Dong ◽  
Yuquan Luo ◽  
Hua Li
Keyword(s):  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Neumann Series ◽  
Low Complexity ◽  
Computation Method ◽  
Likelihood Ratios ◽  
Performance Loss ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output

Abstract We introduce a joint weighted Neumann series (WNS) and Gauss-Seidel (GS) approach to implement an approximated linear minimum mean-squared error (LMMSE) detector for uplink massive multiple-input multiple-output (M-MIMO) systems. We first propose to initialize the GS iteration by a WNS method, which produces a closer-to-LMMSE initial solution than the conventional zero vector and diagonal-matrix based scheme. Then the GS algorithm is applied to implement an approximated LMMSE detection iteratively. Furthermore, based on the WNS, we devise a low-complexity approximate log-likelihood ratios (LLRs) computation method whose performance loss is negligible compared with the exact method. Numerical results illustrate that the proposed joint WNS-GS approach outperforms the conventional method and achieves near-LMMSE performance with significantly lower computational complexity.

Design and Implementation of a Low-Complexity Multiuser Vector Precoder

2012 ◽  
Vol 3 (1) ◽  
pp. 31-48 ◽  
Author(s):  
Maitane Barrenechea ◽  
Luis Barbero ◽  
Mikel Mendicute ◽  
John S. Thompson
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Performance Loss ◽  
Dirty Paper Coding ◽  
Multiple Input ◽  
Input Multiple Output ◽  
The Cost ◽  
Complexity Constraints ◽  
Novel Design

Precoding techniques are used in the downlink of multiuser multiple-input multiple-output (MIMO) systems in order to separate the information data streams aimed at scattered user terminals. Vector precoding (VP) is one of the most promising non-linear precoding schemes, which achieves a performance close to the optimum albeit impractical dirty paper coding (DPC) with a feasible complexity. This contribution presents a novel design for the hardware implementation of a high-throughput vector precoder based on the Fixed Sphere Encoder (FSE) algorithm. The proposed fixed-complexity scheme greatly reduces the complexity of the most intricate part of VP, namely the search for the perturbing signal in an infinite lattice. Additionally, an optimized reduced-complexity implementation is presented which considerably reduces the resource usage at the cost of a small performance loss. Provided simulation results show the better performance of the proposed vector precoder in comparison to other fixed-complexity approaches, such as the K-Best precoder, under similar complexity constraints.

Recursive Spatial Multiplexing with Adaptive Interference Whitening

2017 ◽  
Vol 6 (2) ◽  
pp. 43-59
Author(s):  
Usama Y. Mohamad ◽  
Ibrahim A. Shah ◽  
Thomas Hunziker ◽  
Dirk H. Dahlhaus
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Mean Squared Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Spatial Multiplexing ◽  
Rate Performance ◽  
Mimo Channels ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output

This article describes how recursive spatial multiplexing (RSM) is a closed-loop multiple-input multiple-output (MIMO) structure for achieving the capacity offered by MIMO channels with a low-complexity detector. The authors investigate how to make RSM able to provide a bit-error rate performance, which is robust against different types and levels of interference. The interference arising from simultaneous transmission of information signals is taken into account in the RSM scheme at the receiver using a whitening approach. Here, the covariance matrix is estimated and used subsequently for defining the retransmission subspace identifier to be fed back to the transmitter. The performance of this adaptive RSM scheme is compared with standard linear detection schemes like zero-forcing and minimum mean-squared error receivers. It turns out that the adaptive interference whitening substantially improves the bit-error rate performance. Moreover, adaptive RSM leads to a performance being independent of the correlation coefficient of the interference signals.

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

Low-Complexity MIMO MMSE Receiver with Performance Enhancement via Coordinate Interleaving

2020 ◽  
Vol 29 (14) ◽  
pp. 2050231
Author(s):  
Serdar Özyurt ◽  
Mustafa Öztürk ◽  
Enver Çavuş
Keyword(s):  
Performance Enhancement ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Complexity Reduction ◽  
Error Performance ◽  
Signal Space Diversity ◽  
Mmse Receiver ◽  
Field Programmable ◽  
Input Multiple Output

Multiple-input multiple-output (MIMO) Minimum mean-square error (MMSE) receivers are widely adopted in the latest communication standards and reducing the complexity of these receivers while preserving the error performance is highly desirable. In this work, we study the error performance and implementation complexity of MIMO MMSE receivers when combined with a coordinate interleaved signal space diversity (SSD) technique. Contrary to the well-known trade-off between the error performance and implementation complexity, the proposed system leads to a considerably simplified MIMO MMSE receiver with significant performance gains when compared to the original MIMO MMSE receiver. Unlike the standard MIMO MMSE receiver, the proposed coordinate interleaved technique induces a block diagonal transmit correlation matrix providing both performance enhancement and complexity reduction. The results show that the error performance can be improved more than 10[Formula: see text]dB with up to 71% computational complexity reduction. The complexity comparison between the original and proposed approaches is also verified by means of field-programmable gate array (FPGA) implementation.

scholarly journals Partial Nulling Regularized Block Diagonalization Using Unfair Channel Selection for Post-Coding with Low-Complexity

2020 ◽  
Vol 10 (19) ◽  
pp. 6809
Author(s):  
Hyun-Sun Hwang ◽  
Jae-Hyun Ro ◽  
Young-Hwan You ◽  
Duckdong Hwang ◽  
Hyoung-Kyu Song
Keyword(s):  
Performance Enhancement ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Diversity Gain ◽  
Block Diagonalization ◽  
Time Diversity ◽  
Multiple Input ◽  
Input Multiple Output ◽  
User Interference

A number of requirements for 5G mobile communication are satisfied by adopting multi-user multiple input multiple output (MU-MIMO) systems. The inter user interference (IUI) which is an inevitable problem in MU-MIMO systems becomes controllable when the precoding scheme is used. The proposed scheme, which is one of the precoding schemes, is built on regularized block diagonalization (RBD) precoding and utilizes the partial nulling concept, which is to leave part of the IUI at the same time. Diversity gain is obtained by leaving IUI, which is made by choosing the row vectors of the channel matrix that are not nullified. Since the criterion for choosing the row vectors of the channel is the power of the channel, the number of selected row vectors of the channel for each device can be unfair. The proposed scheme achieves performance enhancement by obtaining diversity gain. Therefore, the bit error rate (BER) performance is better and the computational complexity is lower than RBD when the same data rate is achieved. When the number of reduced data streams is not enough for most devices to achieve diversity gain, the proposed scheme has better performance compared to generalized block diagonalization (GBD). The low complexity at the receiver is achieved compared to GBD by using the simple way to remove IUI.

scholarly journals Performance enhancement of MIMO detectors using wavelet de-noising filters

2016 ◽  
Vol 5 (4) ◽  
pp. 131
Author(s):  
Reham Wgeeh ◽  
Amr Hussein ◽  
Mahmoud Attia
Keyword(s):  
Error Rate ◽  
Communication Systems ◽  
Performance Enhancement ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Antenna Element ◽  
Detection Techniques ◽  
Information Signal ◽  
Input Multiple Output

Multiple-Input Multiple-Output (MIMO) technology has attracted great attention in many wireless communication systems. It provides significant enhancement in the spectral efficiency, throughput, and link reliability. There are numerous MIMO signal detection techniques that have been studied in the previous decades such as Maximum Likelihood (ML), Zero Forcing (ZF), Minimum Mean Square Error (MMSE) detectors, etc. It is well known that the additive and multiplicative noise in the information signal can significantly degrade the performance of MIMO detectors. During the last few years, the noise problem has been the focus of much research, and its solution could lead to profound improvements in symbol error rate performance of the MIMO detectors. In this paper, ML, ZF, and MMSE based wavelet de-noising detectors are proposed. In these techniques, the noise contaminated signals from each receiving antenna element are de-noised individually in parallel to boost the SNR of each branch. The de-noised signals are applied directly to the desired signal detector. The simulation results revealed that the proposed detectors constructed on de-noising basis achieve better symbol error rate (SER) performance than that of systems currently in use.

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