Rayleigh fading channel estimation using MMSE estimator for MIMO-CDMA system

Kazemzad, Mahmood; Asad, Syed Muhammad; Saeed, Omer Bin; Moinuddin, Muhammad; Zerguine, Azzedine

doi:10.1109/iccspa.2015.7081282

Cited by 5 publications

(4 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is known as multiple access interference (MAI) which causes performance degradation over the system [5]. To overcome this problem, some optimal and sub-optimal strategies of multiuser detections (MUDs) have been proposed for MC-CDMA systems; like the linear detection receivers, the interference canceller (IC), decision feedback detection (DFD) and the multistage detector [6,7,8].…”

Section: Introductionmentioning

confidence: 99%

Multiuser Detection with Decision-Feedback Detectors and PIC in MC-CDMA System

et al. 2018

View full text Add to dashboard Cite

In this paper we propose an iterative parallel decision feedback (P-DF) receivers associated with parallel interference cancellation (PIC) for multicarrier code division multiple access (MC-CDMA) systems in a Rayleigh fading channel (cost 207). First the most widely detection techniques, minimum mean-squared error MMSE, Maximum Likelihood ML and PIC were investigated in order to compare their performances in terms of Bit Error Rate (BER) with parallel feedback detection P-DFD. A MMSE DF detector that employs parallel decision-feedback (MMSE-P-DFD) is considered and shows almost the same BER performance with MMSE and ML, which present a better result than the other techniques. In a second time, an iterative proposed method based on the multi-stage techniques P-DFD (parallel DFD with two stages) and PIC was exploited to improve the performance of the system.

show abstract

Section: Introductionmentioning

confidence: 99%

Multiuser Detection with Decision-Feedback Detectors and PIC in MC-CDMA System

et al. 2018

View full text Add to dashboard Cite

show abstract

“…is the PDF of the sum of Rayleigh fading random variables given in (23). Inserting both PDFs in (39), the integral results in…”

Section: Design Of Mmse Channel Estimator For Rayleigh Fading In Mimomentioning

confidence: 99%

“…As a result, the random variable S can be formulated as S = α 2 where α is the sum of N independent Rayleigh random variables whose PDF is given in (23). Eventually, this provides the following PDF of…”

Section: Outage Probabilitymentioning

confidence: 99%

“…Consequently, explicit closed-form expressions for both the PDFs of MAI and MAI plus noise were derived for a Rayleigh fading channel. Recently in [22], the approach of [16] was used to analyze the MAI in MIMO-CDMA systems which was later used in [23] to design minimum mean-square-error (MMSE) estimate of fading channels in the presence of MIMO systems. Although, the work in [22] has provided the derivation for the MAI statistics and the work in [23] has provided MMSE estimator design based on this statistics, but there can be many other interesting applications of the derived MAI statistics in practical scenarios which these work failed to provide.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiple access interference in MIMO-CDMA systems under Rayleigh fading: statistical characterization and applications

Kazemzad

Asad

Moinuddin

et al. 2016

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

A major limiting factor in the performance of multiple-input-multiple-output (MIMO) code division multiple access (CDMA) systems is multiple access interference (MAI) which can reduce the system's capacity and increase its bit error rate (BER). Thus, a statistical characterization of the MAI is vital in analyzing the performance of such systems. Since the statistical analysis of MAI in MIMO-CDMA systems is quite involved, especially when these systems are fading, existing works in the literature, such as successive interference cancellation (SIC) or parallel interference cancellation (PIC), employ suboptimal approaches to detect the subscriber without involving the need for MAI statistics. The knowledge of both MAI and noise statistics plays a vital role in various applications such as the design of an optimum receiver based on maximum likelihood (ML) detection, evaluation of the probability of bit error, calculation of the system's capacity, evaluation of the outage probability, estimation of the channel's impulse response using methods including the minimum mean-square-error (MMSE), the maximum likelihood(ML), and the maximum a posteriori probability (MAP) criterion. To the best of our knowledge, there is no existing work that explicitly evaluates the statistics of the MAI-plus-noise in MIMO fading channels. This constitutes the prime objective of our proposed study here. In this work, we derive the expressions for the probability density function (PDF) of MAI and MAI-plus-noise in MIMO-CDMA systems in the presence of both Rayleigh fading channels and additive white Gaussian noise. Moreover, we evaluate the probability of the bit error rate in the presence of optimum reception using a ML receiver. Our theoretical findings can provide a reliable basis for both system design and various performance analyses of such systems. Our simulation results show that the theoretical findings are very well substantiated.

show abstract

Channel estimation using hybrid optimizer based recurrent neural network long short term memory for MIMO communications in 5G network

Dash

Thampy

2023

SN Appl. Sci.

View full text Add to dashboard Cite

In the fifth-generation (5G) networks, multiple input multiple-output (MIMO) systems are further developed to enhance transmission reliability. However, channel estimation is one of the major challenges which needs focus for improved data transmission in MIMO. Although efficient estimation techniques have been recently proposed, estimation accuracy needs to be upgraded further. Hence, an optimized Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) network is presented in this paper for channel estimation. At first, history of channel responses of pilot block is collected or estimated using Least Square (LS) channel estimation method. Using these collected channel responses, the proposed RNN-LSTM is trained where weight parameters are chosen optimally using hybrid Particle Swarm Optimization (PSO)-Adam optimizer. Using the trained PSO-Adam optimizer based RNN-LSTM, the current channel response is predicted or estimated. The performance of the proposed channel estimation scheme is analysed by varying pilot sequence length and number of antennas to evaluate the metrics Bit Error Rate (BER) and Mean Square Error (MSE). Complexity analysis of the proposed scheme is compared with standard estimators like LS and Minimum Mean-Square Error (MMSE).

show abstract

Rayleigh fading channel estimation using MMSE estimator for MIMO-CDMA system

Cited by 5 publications

References 16 publications

Multiuser Detection with Decision-Feedback Detectors and PIC in MC-CDMA System

Multiuser Detection with Decision-Feedback Detectors and PIC in MC-CDMA System

Multiple access interference in MIMO-CDMA systems under Rayleigh fading: statistical characterization and applications

Channel estimation using hybrid optimizer based recurrent neural network long short term memory for MIMO communications in 5G network

Contact Info

Product

Resources

About