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.

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 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 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 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.

scholarly journals A Survey on Massive MIMO Systems in Presence of Channel and Hardware Impairments

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 164 ◽  
Author(s):  
Zahra Mokhtari ◽  
Maryam Sabbaghian ◽  
Rui Dinis
Keyword(s):  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo Systems ◽  
Low Cost ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Aging Effects ◽  
Hardware Impairments ◽  
Single Carrier ◽  
Input Multiple Output

Massive multiple input multiple output (MIMO) technology is one of the promising technologies for fifth generation (5G) cellular communications. In this technology, each cell has a base station (BS) with a large number of antennas, allowing the simultaneous use of the same resources (e.g., frequency and/or time slots) by multiple users of a cell. Therefore, massive MIMO systems can bring very high spectral and power efficiencies. However, this technology faces some important issues that need to be addressed. One of these issues is the performance degradation due to hardware impairments, since low-cost RF chains need to be employed. Another issue is the channel estimation and channel aging effects, especially in fast mobility environments. In this paper we will perform a comprehensive study on these two issues considering two of the most promising candidate waveforms for massive MIMO systems: Orthogonal frequency division multiplexing (OFDM) and single-carrier frequency domain processing (SC-FDP). The studies and the results show that hardware impairments and inaccurate channel knowledge can degrade the performance of massive MIMO systems extensively. However, using suitable low complex estimation and compensation techniques and also selecting a suitable waveform can reduce these effects.

scholarly journals Joint Optimization of Precoder and Decoder in Multiuser MIMO Systems

2012 ◽  
Vol 2 (1-2) ◽  
Author(s):  
M. Raja ◽  
Ha H. Nguyen ◽  
P. Muthuchidambaranathan
Keyword(s):  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Joint Optimization ◽  
Phase Shift Keying ◽  
Multiuser Mimo ◽  
Multiple Input ◽  
Shift Keying ◽  
Input Multiple Output ◽  
Binary Phase Shift Keying

This paper considers the joint optimization of precoder and decoder for both uplink and downlink transmissions in multiuser multiple-input, multiple-output (MU-MIMO) systems. Focusing on the scenario when an improper constellation such as binary phase shift-keying (BPSK) or M-ary amplitude shift-keying (M-ASK) is employed, novel joint linear precoders and decoders are proposed to minimize the total mean squared error (TMSE) of the symbol estimation. The superiority of the proposed transceivers over the previously-proposed designs is thoroughly verified by simulation results.

scholarly journals Studying and Modeling the Performance of the TCM-STBC Systems in the Rayleigh Channel

2021 ◽  
Vol 1 ◽  
pp. 1-7
Author(s):  
Mohammed Sofiane Bendelhoum ◽  
Mohamed Rida Lahcene ◽  
Fayssal Menezla ◽  
Abderraouf Elarbi
Keyword(s):  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Block Code ◽  
Space Time ◽  
Performance Comparison ◽  
Coded Modulation ◽  
Rayleigh Channel ◽  
Input Multiple Output ◽  
Matrix Codes

Multiple-input multiple-output (MIMO) systems will play an important role in future generations of wireless networks. Space-time block code (STBC) and space-time trellis code (STTC) are two techniques that may be used in multi-antenna radio systems. This paper aims, most importantly, to study the performance of STBC systems at different vallues of such parameters as spectral efficiency, matrix codes and constellations. A performance comparison between STBC and STTC schemes is performed. In order to show the efficiency of the system’s ability to communicate with uncoded and coded transmission structures over AWGN and Rayleigh channels, the trellis-coded modulation (TCM) is introduced. The results obtained show that the proposed TCM-STBC system model, using one and two receiving antennas, improves the performance of Rayleigh channel communication systems at 9.5 dB and 11.5 dB for a BER of 10−5

scholarly journals Computation of System Performance of MIMO Technique in Communication Channel using V-BLAST Method

2019 ◽  
Vol 8 (2) ◽  
pp. 898-901
Keyword(s):  
Performance Improvement ◽  
Error Rate ◽  
Communication Channel ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Block Codes ◽  
Space Time ◽  
System A ◽  
Multiple Input ◽  
Input Multiple Output

In order to improvement both system performances and data rate Multiple Input Multiple Output techniques play an important role in transmission system. A number of techniques are used to do the needful work for performance improvement in MIMO systems belongs to different block codes, apart from that BLAST architecture are used Such as Diagonal Bell laboratories layered space-time (D-BLAST), Vertical Bell Labs Space-Time Architecture (V-BLAST) method. This work defines the performance improvement using V-BLAST technique in Multiple Input Multiple Output detector. Here we discuss the concept of Multiple Input Multiple Output with BLAST architecture. Depends upon the Bit Error Rate and Frame Error Rate, the comparison is made with the existing methods.

scholarly journals MIMO Detectors Under Correlated Channels

2016 ◽  
Vol 37 (1) ◽  
pp. 3
Author(s):  
Bruno Felipe Costa ◽  
Alex Miyamoto Mussi ◽  
Taufik Abrão
Keyword(s):  
Maximum Likelihood ◽  
Interference Cancellation ◽  
Mean Squared Error ◽  
Multiple Input Multiple Output ◽  
Successive Interference Cancellation ◽  
Correlated Channels ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Multiple Input ◽  
Input Multiple Output

Este artigo analisa o desempenho de detectores com múltiplas antenas transmissoras e múltiplas antenas receptoras (MIMO – multiple-input multiple-output) em canais com desvanecimento correlacionados. Dois esquemas de detecção MIMO denominados erro quadrático médio mínimo (MMSE – minimum mean squared error) – com ou sem a etapa de cancelamento de interferência sucessiva ordenado (OSIC – ordered successive interference cancellation) – e técnica de redução treliça (LR – lattice reduction) são analisados e comparados com o limite de detecção de máxima verossimilhança (ML – maximum likelihood) em cenários específicos de interesse: (a) com incremento da eficiência espectral através do aumento do número de antenas. (b) quando há aumento nos índices de correlação de desvanecimento do canal. Neste contexto, o desempenho do detector ótimo ML-MIMO é utilizado como referência visando caracterizar o comportamento da taxa de erro de bit (BER) destes detectores MIMO e quão próximo esses estão do desempenho ML-MIMO.

scholarly journals FDD Channel Estimation Via Covariance Estimation in Wideband Massive MIMO Systems

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 930
Author(s):  
José P. González-Coma ◽  
Pedro Suárez-Casal ◽  
Paula M. Castro ◽  
Luis Castedo
Keyword(s):  
Channel Estimation ◽  
Covariance Matrix ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Channel Structure ◽  
Spatial Covariance ◽  
Large Bandwidth ◽  
Minimum Mean Squared Error ◽  
Large Channel

A method for channel estimation in wideband massive Multiple-Input Multiple-Output systems using hybrid digital analog architectures is developed. The proposed method is useful for Frequency-Division Duplex at either sub-6 GHz or millimeter wave frequency bands and takes into account the beam squint effect caused by the large bandwidth of the signals. To circumvent the estimation of large channel vectors, the posed algorithm relies on the slow time variation of the channel spatial covariance matrix, thus allowing for the utilization of very short training sequences. This is possibledue to the exploitation of the channel structure. After identifying the channel covariance matrix, the channel is estimated on the basis of the recovered information. To that end, we propose a novel method that relies on estimating the tap delays and the gains as sociated with each path. As a consequence, the proposed channel estimator achieves low computational complexity and significantly reduces the training overhead. Moreover, our numerical simulations show better performance results compared to the minimum mean-squared error solution.

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