scholarly journals Design, Simulation & Concept Verification of 4 × 4, 8 × 8 MIMO With ZF, MMSE and BF Detection Schemes

2017 ◽  
Vol 13 (1) ◽  
pp. 69-74
Author(s):  
Arun Kumar ◽  
Piyush Vardhan
Keyword(s):  
Signal Detection ◽  
Communication Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Base Station ◽  
Wireless Communication Systems ◽  
Detection Techniques ◽  
Low Snr ◽  
Detection Schemes ◽  
Suitable Technique

Abstract A conventional MIMO system is designed consisting of 4 antenna elements at both the receiver and transmitter ends. Different kinds of signal detection techniques, namely, zero forcing (ZF), minimum mean square error (MMSE) and beamforming (BF), are used at the receiver end for signal detection. The performance of the system is analyzed by calculating BER vs SNR for each of the above techniques separately. The present work has been thoroughly analyzed and implemented using MATLAB. On the basis of the results obtained, it is summarized that as the values of SNR increase, BER decreases for ZF and MMSE and it almost vanishes to zero even for low SNR values if BF is used. Although ZF and MMSE are suitable for designing a conventional MIMO system with 4 antenna elements, it becomes too difficult for a large number of antenna elements due to its complexity of calculating the inverse of a (N × N) matrix. Based on the results analyzed so far, it is concluded that beamforming (BF) is a suitable technique for designing a system that has a large number of antenna elements at the base station. A further improved system with enhanced performance regarding lower BER for even smaller values of SNR is designed in the present study, consisting of 8 antennas at the base station. The results obtained are enthusiasm-provoking and encouraging for further studies to develop a concept for next-generation wireless communication systems with an optimum design.

scholarly journals ISSOR Signal Detection for Energy Efficient and Low Complexity Large Scale MIMO System

2019 ◽  
Vol 9 (1S5) ◽  
pp. 327-334
Keyword(s):  
Signal Detection ◽  
Energy Efficient ◽  
Communication Systems ◽  
Large Scale ◽  
Mimo System ◽  
Low Complexity ◽  
High Energy ◽  
Base Station ◽  
User Equipment ◽  
Multiple User

Scalable version of multiuser MIMO called Large-scale MIMO is a one of the powerful technology in future wireless communication systems in which huge amount of BS (base station) antennas utilized to process multiple user equipment. Energy consumed is high with more antennas and also it leads to increase the signal detection complexity and overall circuit power consumption. Designing energy efficient and low complexity MIMO system is considered as a challenging issue. This paper presents the ISSOR signal detection for energy efficient and low complexity large scale MIMO system. VA-GSM (Variable Antenna Generalized spatial modulation) is used in which the number of active antenna transmissions are varied for every transmission in the large scale MIMO. In transmitter side, Eigen value based approach is used for antenna selection. Then, improved symmetric successive over relaxation (ISSOR) approach is proposed for low complexity signal detection in receiver side. The number of user equipment, transmit power, as well as the amount of antennas at the base station, are considered as the optimal system parameters which are chosen for enhancing the efficiency of utilized energy in the system. The proposed scheme implemented in MATLAB software. The proposed scheme attained the high energy efficiency compared to other approaches. Moreover, the BER is utilized to estimate the performance of an offered algorithm and also compared to the previously determined algorithm of existing literatures.

scholarly journals Normalized Structured Compressed Sensing Based Signal Detection in Spatial Modulation 3D-MIMO Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Wei Ren ◽  
Guan Gui ◽  
Fei Li
Keyword(s):  
Compressed Sensing ◽  
Signal Detection ◽  
Communication Systems ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Iteration Process ◽  
High Energy ◽  
Spatial Modulation ◽  
3D Mimo

Signal detection is one of the fundamental problems in three-dimensional multiple-input multiple-output (3D-MIMO) wireless communication systems. This paper addresses a signal detection problem in 3D-MIMO system, in which spatial modulation (SM) transmission scheme is considered due to its advantages of low complexity and high-energy efficiency. SM based signal transmission typically results in the block-sparse structure in received signals. Hence, structured compressed sensing (SCS) based signal detection is proposed to exploit the inherent block sparsity information in the received signal for the uplink (UL). Moreover, normalization preprocessing is considered before iteration process with the purpose of preventing the noise from being overamplified by the column vector with inadequately large elements. Simulation results are provided to show the stable and reliable performance of the proposed algorithm under both Gaussian and non-Gaussian noise, in comparison with methods such as compressed sensing based detectors, minimum mean square error (MMSE), and zero forcing (ZF).

scholarly journals Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1564
Author(s):  
Hebiao Wu ◽  
Bin Shen ◽  
Shufeng Zhao ◽  
Peng Gong
Keyword(s):  
Signal Detection ◽  
Output Signal ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Matrix Inversion ◽  
Iteration Algorithm

For multi-user uplink massive multiple input multiple output (MIMO) systems, minimum mean square error (MMSE) criterion-based linear signal detection algorithm achieves nearly optimal performance, on condition that the number of antennas at the base station is asymptotically large. However, it involves prohibitively high complexity in matrix inversion when the number of users is getting large. A low-complexity soft-output signal detection algorithm based on improved Kaczmarz method is proposed in this paper, which circumvents the matrix inversion operation and thus reduces the complexity by an order of magnitude. Meanwhile, an optimal relaxation parameter is introduced to further accelerate the convergence speed of the proposed algorithm and two approximate methods of calculating the log-likelihood ratios (LLRs) for channel decoding are obtained as well. Analysis and simulations verify that the proposed algorithm outperforms various typical low-complexity signal detection algorithms. The proposed algorithm converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations.

scholarly journals Design, Analysis of 4×4 and 8×8 MIMO System with ZF, MMSE and BF Techniques

2017 ◽  
Vol 17 (2) ◽  
pp. 16-19 ◽  
Author(s):  
Arun Kumar ◽  
Piyush Vardhan ◽  
Manisha Gupta
Keyword(s):  
Signal Detection ◽  
Mimo System ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Digital Signal ◽  
Base Station ◽  
Beam Forming ◽  
High Signal ◽  
Zero Forcing ◽  
Signal Processors

AbstractThis work focuses on studying signal detection using three different equalization techniques, namely: Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Beam Forming (BF), for a 4×4 MIMO-system. Results show that ZF equalization is the simplest technique for signal detection, However, Beam Forming (BF) gives better Bit Error Rate (BER) performances at high Signal to Noise Ratio (SNR) values with some complexity in design. For more antennas at the base station, it is too complex to design the weight matrix for ZF, however, it is suitable for BF with the help of good quality digital signal processors. Performance of MIMO-system, with 8 antennas at the base station using BF equalization, is analysed to get BER values at different SNR. Results show a considerable improvement in BER for 8 antennas at the base station.

scholarly journals Investigation of Ideal Number User Terminals with Spectrum Efficiency in Next Generation Wireless Communication Systems

2021 ◽  
Vol 38 (1) ◽  
pp. 115-126
Author(s):  
Osman Dikmen ◽  
Selman Kulaç
Keyword(s):  
Wireless Communication ◽  
Communication Systems ◽  
Mimo System ◽  
Base Station ◽  
Spectrum Efficiency ◽  
Design Parameters ◽  
Wireless Communication Systems ◽  
Next Generation ◽  
Ideal Number ◽  
The Ideal

Suppose that a multi-user multiple-input multiple-output (MIMO) system is developed from scratch to equally envelop a defined region with optimal spectrum efficiency (SE) in next generation wireless communication systems such as sixth-generation (6G) and beyond networks. What are the ideal number of user terminals U, number of base stations antennas, and used pilot reuse factor? The purpose of this paper is to address this specific issue. Three interference levels are specified for this. Based on these interference levels, signal-to-interference-and-noise ratios (SINRs) are extracted. Closed-form spectrum efficiency equations are thus obtained. As a function of the base station (BS) antenna number, simulations are carried out considering multiple pilot reuse factors and diverse processing schemes such as Maximum Ratio Combining (MRC) and Zero-Forcing (ZF). From the results, it is understood that U varies according to the processing schemes. Therefore, evaluating the results considering the fixed number of users K will not give an accurate result in determining the design parameters for the next generation communication systems. In general, these results are useful statements that spectrum efficiency is maximized when the ideal number of users U is used in multi-cell systems.

scholarly journals Physical-Layer Security Improvement with Reconfigurable Intelligent Surfaces for 6G Wireless Communication Systems

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1439
Author(s):  
Janghyuk Youn ◽  
Woong Son ◽  
Bang Chul Jung
Keyword(s):  
Wireless Communication ◽  
Physical Layer Security ◽  
Communication Systems ◽  
Low Cost ◽  
Physical Layer ◽  
Base Station ◽  
Wireless Communication Systems ◽  
Secrecy Rate ◽  
Pilot Signal ◽  
Time Division

Recently, reconfigurable intelligent surfaces (RISs) have received much interest from both academia and industry due to their flexibility and cost-effectiveness in adjusting the phase and amplitude of wireless signals with low-cost passive reflecting elements. In particular, many RIS-aided techniques have been proposed to improve both data rate and energy efficiency for 6G wireless communication systems. In this paper, we propose a novel RIS-based channel randomization (RCR) technique for improving physical-layer security (PLS) for a time-division duplex (TDD) downlink cellular wire-tap network which consists of a single base station (BS) with multiple antennas, multiple legitimate pieces of user equipment (UE), multiple eavesdroppers (EVEs), and multiple RISs. We assume that only a line-of-sight (LOS) channel exists among the BS, the RISs, and the UE due to propagation characteristics of tera-hertz (THz) spectrum bands that may be used in 6G wireless communication systems. In the proposed technique, each RIS first pseudo-randomly generates multiple reflection matrices and utilizes them for both pilot signal duration (PSD) in uplink and data transmission duration (DTD) in downlink. Then, the BS estimates wireless channels of UE with reflection matrices of all RISs and selects the UE that has the best secrecy rate for each reflection matrix generated. It is shown herein that the proposed technique outperforms the conventional techniques in terms of achievable secrecy rates.

scholarly journals Three-Dimensional MIMO Channel Model with High-Mobility Wireless Communication Systems Using Leaky Coaxial Cable in Rectangular Tunnel

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kai Zhang ◽  
Fangqi Zhang ◽  
Guoxin Zheng ◽  
Lei Cang
Keyword(s):  
Wireless Communication ◽  
Communication Systems ◽  
Channel Model ◽  
Mimo System ◽  
Three Dimensional ◽  
High Mobility ◽  
Coaxial Cable ◽  
Mimo Channel ◽  
Wireless Communication Systems ◽  
Rectangular Tunnel

With the rapid development of high-mobility wireless communication systems, e.g., high-speed train (HST) and metro wireless communication systems, more and more attention has been paid to the wireless communication technology in tunnel-like scenarios. In this paper, we propose a three-dimensional (3D) nonstationary multiple-input multiple-output (MIMO) channel model with high-mobility wireless communication systems using leaky coaxial cable (LCX) inside a rectangular tunnel over the 1.8 GHz band. Taking into account single-bounce scattering under line-of-sight (LoS) and non-line-of-sight (NLoS) propagations condition, the analytical expressions of the channel impulse response (CIR) and temporal correlation function (T-CF) are derived. In the proposed channel model, it is assumed that a large number of scatterers are randomly distributed on the sidewall of the tunnel and the roof of the tunnel. We analyze the impact of various model parameters, including LCX spacing, time separation, movement velocity of Rx, and K-factor, on the T-CF of the MIMO channel model. For HST, the results of some further studies on the maximum speed of 360 km/h are given. By comparing the T-CF between the dipole MIMO system and the LCX-MIMO system, we can see that the performance of the LCX-MIMO system is better than that of the dipole MIMO system.

Blind Signal Detection Techniques for Spectrum Sensing in Satellite Communication

2017 ◽  
pp. 1-48
Author(s):  
Bilal Muhammad Khan ◽  
Rabia Bilal
Keyword(s):  
Correlation Function ◽  
Signal Detection ◽  
Communication Systems ◽  
Satellite Communication ◽  
Spectral Correlation ◽  
Detection Techniques ◽  
Blind Signal ◽  
Modulated Signals ◽  
Spectral Correlation Function ◽  
Frequency Axis

Modulated signals used in communication systems exhibits cyclic periodicity. This is primarily due to sinusoidal product modulators, repeating preambles, coding and multiplexing in modern communication. This property of signals can be analyzed using cyclostationary analysis. SCF (Spectral correlation function) of cyclic autocorrelation (CAF) has unique features for different modulated signals and noise. Different techniques are applied to SCF for extracting features on the basis of which decision of detecting a signal or noise is made. In this chapter, study and analysis of different modulated signals used in satellite communication is presented using SCF. Also comparison of several signal detection techniques is provided on the basis of utilizing unique feature exhibit by a normalized vector calculated on SCF along frequency axis. Moreover a signal detection technique is also proposed which identifies the presence of a signal or noise in the analyzed data within the defined threshold limits.

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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