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.

scholarly journals Location-Aided Uplink Transmission for User-Centric Cell-Free Massive MIMO Systems: A Fairness Priority Perspective

2022 ◽  
Author(s):  
Chen Wei ◽  
Kui Xu ◽  
Zhexian Shen ◽  
Xiaochen Xia ◽  
Wei Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Access Point ◽  
Estimation Accuracy ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output ◽  
User Centric ◽  
Assignment Scheme

Abstract In this paper, we investigate the uplink transmission for user-centric cell-free massive multiple-input multiple-output (MIMO) systems. The largest-large-scale-fading-based access point (AP) selection method is adopted to achieve a user-centric operation. Under this user-centric framework, we propose a novel inter-cluster interference-based (IC-IB) pilot assignment scheme to alleviate pilot contamination. Considering the local characteristics of channel estimates and statistics, we propose a location-aided distributed uplink combining scheme based on a novel proposed metric representing inter-user interference to balance the relationship among the spectral efficiency (SE), user equipment (UE) fairness and complexity, in which the normalized local partial minimum mean-squared error (LP-MMSE) combining is adopted for some APs, while the normalized maximum ratio (MR) combining is adopted for the remaining APs. A new closed-form SE expression using the normalized MR combining is derived and a novel metric to indicate the UE fairness is also proposed. Moreover, the max-min fairness (MMF) power control algorithm is utilized to further ensure uniformly good service to the UEs. Simulation results demonstrate that the channel estimation accuracy of our proposed IC-IB pilot assignment scheme outperforms that of the conventional pilot assignment schemes. Furthermore, although the proposed location-aided uplink combining scheme is not always the best in terms of the per-UE SE, it can provide the more fairness among UEs and can achieve a good trade-off between the average SE and computational complexity.

scholarly journals Space-Time Trellis Coding with Equalization

2019 ◽  
Vol 4 (9) ◽  
pp. 207-211
Author(s):  
Ibukunoluwa Adetutu Adebanjo ◽  
Yekeen Olajide Olasoji ◽  
Micheal Olorunfunmi Kolawole
Keyword(s):  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Space Time ◽  
Wireless Channel ◽  
Cyclic Prefix ◽  
Single Carrier ◽  
Minimum Mean Squared Error ◽  
Mmse Receiver ◽  
Input Multiple Output

As we are entering the 5G era, high demand is made of wireless communication. Consistent effort has been ongoing in multiple-input multiple-output (MIMO) systems, which provide correlation on temporal and spatial domain, to meet the high throughput demand. To handle the characteristic nature of wireless channel effectively and improve the system performance, this paper considers the combination of diversity and equalization. Space-Time trellis code is combined with single-carrier modulation using two-choice equalization techniques, namely: minimum mean squared error (MMSE) equalizer and orthogonal triangular (QR) detection. MMSE gives an optimal balance between noise enhancement and net inter-symbol interference (ISI) in the transmitted signal. Use of these equalizers provides the platform of investigating the bit error rate (BER) and the pairwise error probability (PEP) at the receiver, as well as the effect of cyclic prefix reduction on the receivers. It was found that the MMSE receiver outperforms the QR receiver in terms of BER, while in terms of PEP; the QR receiver outperforms the MMSE receiver. When a cyclic prefix reduction test was carried out on both receivers, it yields a significant reduction in BER of both receivers but has no significant effect on the overall performance.

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.

scholarly journals Linear detectors and precoding methods for massive MIMO

2021 ◽  
Vol 42 (2) ◽  
pp. 209
Author(s):  
Jean Marcel Faria Tonin ◽  
Taufik Abrao
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Wireless Channel ◽  
Single Input Single Output ◽  
Single Output ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output

Detection in multiple-input-multiple-output (MIMO) wireless communication systems is a crucial procedure in receivers since the multiple access transmission schemes generate interference due to the simultaneous transmission along with the several antennas, unlike single-input-single-output (SISO) transmission schemes. Precoding is a technique in MIMO systems used to mitigate the effects of the channel over the received signal. Hence, it is possible to adjust continuously the transmitted information to reverse the effect of the wireless channel at the receiver side. In this work, linear sub-optimal detectors and precoders for massive MIMO (M-MIMO) systems are implemented, analyzed, and compared in terms of performance-complexity trade-off. It is also being considered numerical results in both channel scenarios: a) receiver and transmitter have perfect channel state information (CSI); b) complex channel coefficients are estimated with different levels of inaccuracy. Monte-Carlo simulations (MCS) reveal that linear zero-forcing (ZF) and minimum mean squared error (MMSE) massive MIMO detectors result in a certain robustness against multi-user interference when operating under low and medium system loading, L = K/M, thanks to the favourable propagation phenomenon arising in massive MIMO systems.

scholarly journals Dynamically Subarray-Connected Hybrid Precoding Scheme for Multiuser Millimeter-Wave Massive MIMO Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guangyan Liao ◽  
Feng Zhao
Keyword(s):  
Millimeter Wave ◽  
Massive Mimo ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Hybrid Precoding ◽  
Minimum Mean Squared Error ◽  
Specific Subset ◽  
Input Multiple Output

Hybrid precoding is widely used in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. However, most prior work on hybrid precoding focused on the fully connected hybrid architectures and the subconnected but fixed architectures in which each radio frequency (RF) chain is connected to a specific subset of the antennas. The limited work shows that dynamic subarray architectures address the tradeoff between achievable spectral efficiency and energy efficiency of mmWave massive MIMO systems. Nevertheless, in the multiuser hybrid precoding systems, the existing dynamic subarray schemes ignore the fairness of users and the problem of user selection. In this paper, we propose a novel multiuser hybrid precoding scheme for dynamic subarray architectures. Firstly, we select a multiuser set among all users according to the analog effective channel information of the base station (BS) and then design the subset of the antennas to each RF by the fairness antenna-partitioning algorithm. Finally, the optimal analog precoding vector is designed according to each subarray, and the digital precoding is designed by the minimum mean-squared error (MMSE) criterion. The simulation results show that the performance advantages of the proposed multiuser hybrid precoding scheme for dynamic subarray architectures.

Computational Complexity Reduction of MMSE-IC MIMO Turbo Detection

2019 ◽  
Vol 28 (13) ◽  
pp. 1950228 ◽  
Author(s):  
Mostafa Rizk ◽  
Amer Baghdadi ◽  
Michel Jézéquel
Keyword(s):  
Wireless Communication ◽  
Error Rate ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Rate Performance ◽  
High Data ◽  
Minimum Mean Squared Error ◽  
Turbo Detection

High data rates and error-rate performance approaching close to theoretical limits are key trends for evolving digital wireless communication applications. To address the first requirement, multiple-input multiple-output (MIMO) techniques are adopted in emergent wireless communication standards and applications. On the other hand, turbo concept is used to alleviate the destructive effects of the channel and ensure error-rate performance close to theoretical limits. At the receiver side, the incorporation of MIMO techniques and turbo processing leads to increased complexity that has a severe impact on computation speed, power consumption and implementation area. Because of its increased complexity, the detector is considered critical among all receiver components. Low-complexity algorithms are developed at the cost of decreased performance. Minimum mean-squared error (MMSE) solution with iterative detection and decoding shows an acceptable tradeoff. In this paper, the complexity of the MMSE algorithm in turbo detection context is investigated thoroughly. Algorithmic computations are surveyed to extract the characteristics of all involved parameters. Consequently, several decompositions are applied leading to enhanced performance and to a significant reduction of utilized computations. The complexity of the algorithm is evaluated in terms of real-valued operations. The proposed decompositions save an average of [Formula: see text] and [Formula: see text] of required operations for 2 [Formula: see text] 2 and 4 [Formula: see text] 4 MIMO systems, respectively. In addition, the hardware implementation designed applying the devised simplifications and decompositions outperforms available state-of-the-art implementations in terms of maximum operating frequency, execution time, and performance.

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.

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 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.

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