Bit error rate minimisation using SLM technique in TFT-OFDM for mobile large-scale MIMO systems

Multiple Input Multiple Output (MIMO) low complexity receiver which utilizes the compressive sensing detection for Spatial Modulation in large scale MIMO system in order to reduce the system complexity. In conventional MIMO system; huge amount of antennas is used at both ends to exploit the multipath propagation. This system maximizes the throughput performance and data rates are increased but only at the cost of high hardware complexity and increased power-consumption. Spatial Modulation Matching Pursuit (SMMP) is the proposed enhanced CS technique used for the improvement of detection performance. Hence, this paper reviews recent research findings concerning normalized Compressive Sensing (CS) detection algorithm, used for Spatial Modulation (SM) in massive MIMO, to lowers the signal processing complexity, which in result improves the energy efficiency of system against that of conventional MIMO system.This strategy is achieved by involving additional structures and sparsity in which a single transmitter antenna or a subset of it is turned on at each case to transmit a certain data. The subset of antenna which is turned on for transmission depends on approaching data bits. Therefore, the total increase in the spectral efficiency of the system is given as base-two logarithm of whole antennas at the transmitter. It reduces the signal processing load at base station and doesn’t depend upon any synchronization between transmitters. The Spatial Modulation Matching Pursuit used prevents the Inter Channel Interference (ICI) of the system which in result improves the Bit Error Rate (BER) performance than the typical MIMO system.

Multiple input multiple output (MIMO) systems can be designed for two operational modes: to improve bit error rate (BER) or to increase capacity without consuming additional power or bandwidth. In this paper, MIMO space-time-frequency (STF) conjugate two-path transmission orthogonal frequency division multiplexing (OFDM) systems with precoders are presented to combat inter-carrier interference and to adaptively switch between these two modes in mobile fading channels. First, the STF architecture is developed to form a 2 × 1 STF-OFDM system. Second, a conjugate cancellation (CC) two-path transmission scheme is integrated with the STF-OFDM system to form a new 2 × 1 STFCC-OFDM system. This system improves BER without expanding power or bandwidth in comparing with the CC scheme. Third, Walsh–Hadamard (WH) transform is employed as the precoder to form the 2 × 1 WHSTFCC-OFDM system. Finally, a 2 × 2 WHSTFCC-OFDM architecture is designed. It can be used to improve BER or switch to two 2 × 1 WHSTFCC-OFDM systems to increase capacity as needed. Simulations indicate that the 2 × 1 WHSTFCC-OFDM system has the best BER, the STFCC-OFDM system, and the STF-OFDM system follow in order. Similarly, the BER of the 2 × 2 WHSTFCC-OFDM system outperforms the 2 × 1 WHSTFCC-OFDM, and the 2 × 2 STFCC-OFDM system follow in order. All these STFCC- and WHSTFCC-OFDM schemes are simple and backward compatible with the existing OFDM system. They may serve as baseband building blocks in OFDM transceivers and can be adaptively switched between 2 × 1 and 2 × 2 architectures as required for the fourth generation and the future planned fifth generation MIMO systems. This adaptive MIMO system can also be applied to the regular or bad weather environment in the disaster conditions for increasing capacity or enhancing the reliability of the communication system.

The free space optical (FSO) communication system has attracted many researchers from different countries, owning to its advantages such as high security, high speed and anti-interference. Among all kinds of the channels of the FSO communication system, the atmosphere channel is very difficult to deal with for two typical disadvantages at least. The one is the scintillation of the optical carrier intensity caused by the atmosphere turbulence and the other is the multipath effect by the optical scattering. A lot of studies have shown that the MIMO (Multiple Input Multiple Output) technology can overcome the scintillation of the optical carrier through the atmosphere effectively. So the background of this paper is a MIMO system which includes multiple optical transmitting antennas and multiple optical receiving antennas. A number of particles such as hazes, water droplets and aerosols exit in the atmosphere widely. When optical carrier meets these particles, the scattering phenomenon is inevitable, which leads to the multipath effect. As a result, a optical pulse transmitted by the optical transmitter becomes wider, to some extent, when it gets to the optical receiver due to the multipath effect. If the information transmission rate is quite low, there is less relationship between the multipath effect and the bit error rate (BER) of the communication system. Once the information transmission rate increases to a high level, the multipath effect will produce the problem called inter symbol inference (ISI) seriously and the bit error rate will increase severely. In order to take the advantage of the FSO communication system, the inter symbol inference problem must be solved. So it is necessary to use the channel equalization technology. This paper aims at deciding a equalizer and designing suitable equalization algorithm for a MIMO free space optical communication system to overcome the serious problem of bit error rate. The reliability and the efficiency of communication are two important indexes. For a MIMO communication system, there are two typical equalization methods. The first method, every receiving antenna has an independent equalizer without the information derived from the other receiving antennas. The second, the information derived from all of the receiving antennas mixes with each other, according to some definite rules, which is called space-time equalization. The former is discussed in this paper. The equalization algorithm concludes training mode and non training mode. The training mode needs training codes transmitted by the transmitter during the whole communication process and this mode reduces the communication efficiency more or less. In order to improve the communication efficiency, the blind equalization algorithm, a non training mode, is used to solve the parameter of the equalizer. In this paper, firstly, the atmosphere channel is described focusing on the scintillation and multipath effect of the optical carrier. Then, the structure of a equalizer of MIMO free space optical communication system is introduced. In the next part of this paper, the principle of the blind equalization algorithm is introduced. In addition, the simulation results are showed. In the end of this paper, the conclusions and the future work are discussed.

– This paper analyses the performance of Multiple Input Multiple Output (MIMO) wireless communication system by combining it with an efficient algorithm Diagonal Reduction (DR). DR is a powerful tool to achieve more efficiently a high performance with less complexity. This paper proposes a DR algorithm in order to reduce its complexity named Greedy Diagonal Reduction (GDR) algorithm which gives reduced complexity with efficient performance at the receiver using the MATLAB communication tool box version 7.0 as a simulation tool. From the simulation results of various reduction algorithms it is observed that, DR can reduce the number of iterations using size reduction operations. Proposed DR algorithm gives identical Bit Error Rate (BER) performance with LLL algorithms when applied to Successive Interference cancellation (SIC) decoding. Greedy DR reduces the computational complexity in Multiple Input Multiple Output systems by improving the efficiency in terms of size reduction operations. Sphere Decoding (SD) technique gives better BER performance on comparing with Successive Interference cancellation decoding technique.

Large‐scale multiple‐input multiple‐output (MIMO) system is considered one of promising technologies to realise next‐generation wireless communication system (5G). So far, channel estimation problem is a big obstacle to develop large‐scale MIMO system design due to high computational complexity and curse of dimensionality, which are caused by the long delay spread as well as a large number of antennas. Hence, devising any low‐complexity channel estimation method could promote the successful development of the large‐scale MIMO system. Due to the fact that, large‐scale MIMO channels often exhibit sparse or/and cluster‐sparse structure, in this study, the authors propose an effective low‐complexity large‐scale MIMO channel estimation method by using affine combination of sparse adaptive filtering filters. First, problem formulation and standard affine combination of adaptive least mean square (LMS) filters are introduced. Then they propose an effective affine combination method with two sparse LMS filters and design an approximate optimum affine combiner according to stochastic gradient search method. Later, to verify the proposed algorithm for large‐scale MIMO channel estimation, both theoretical analysis and numerical simulations are provided to confirm effectiveness of the proposed algorithm which can achieve better estimation performance than the traditional methods.

The demand for higher data rate and better quality of service (QoS) in wireless communications was growing fast in the past few years. Obtaining these requirements becomes challenging for wireless communication systems due to the problems of channel multi-path fading, higher power and bandwidth limitations. One of the most promising solutions to this problem is Multiple Input Multiple Output (MIMO) system. This paper proposed a combined spatial multiplexing MIMO scheme with beamforming for high data rate wireless communication. The proposed transmission scheme combines the benefits of both techniques and the system was able to transmit parallel data streams as well as providing beamforming gain. Actually, these diverse techniques, share the same requirement of multiple antenna elements, but differ in the antenna element spacing necessary for the different schemes to work. Thus, smart antenna array was proposed as a possible solution and was adopted at the both transmitter and the receiver. The hybrid technique provides higher spectral efficiency and improve better Bit error rate (BER) of the system than the conventional MIMO, spatial multiplexing and beamforming techniques under the same simulation environment.

In this paper, we propose a multi-user orthogonal frequency-division multiplexing (OFDM) transmission scheme with partial channel reusing between users, suitable for multiple-input multiple-output (MIMO) systems with not-so-large antenna arrays. The spectrum efficiency is improved at the price of adding multiuser interference (MUI) which can be overcome by the multiplexing gain of MIMO. In addition, we propose to employ the spread spectrum OFDM (SS-OFDM) modulation with the Walsh-Hadamard (WH) codebook for such a multi-user system to further mitigate the MUI. The bit error rate (BER) performance of the proposed scheme in the additive white Gaussian noise (AWGN) channels is derived analytically and then verified through Monte-Carlo simulations. Moreover, the proposed SS-OFDM system with partial bandwidth reuse is compared with the OFDM-based solution in a moderate-scale MIMO system with equal gain combining (EGC) precoding. It is shown that the proposed SS-OFDM MIMO system outperforms the classical OFDM approach in frequency-selective fading channels when the number of transmit antennas remains moderate.

Spatial correlation is a crucial impairment for practical Multiple Input Multiple Output (MIMO) wireless communication systems. It is important to consider spatial correlation between antennas in actual communication scenario at both sides, i.e. transmit and receive side. Furthermore, we have considered nonorthogonal full rate STBC in MIMO systems equipped with four transmit antennas and four receive antennas in a quasi-static Rayleigh fading channel. In this paper, Bit Error Rate (BER) performance of full rate non-orthogonal Space Time Block code (STBC) is obtained using simulations in MIMO wireless communication systems. Spatial correlation is assumed between antennas at both the transmitter and the receiver sides. For this analysis, we have considered various transmit antenna spacing values of d t = 0.1π, 0.2π, and 0.4π keeping fixed d r = 0.1π and various receive antenna spacing values of d r = 0.1π, 0.2π, and 0.4π keeping fixed d t = 0.1π. The obtained results show that the transmitting diversity is more serious than the receiving diversity in the spatially correlated antenna environment for the specified signal-to-noise ratio. This study will be useful for actual wireless communication implementation where spatial correlation antennas are present in the practical environment of the MIMO wireless communication system.

Mobile communication companies at present are looking for a 4G technology that aims at better reliability. This aim can be achieved by using Multiple Inputs Multiple Outputs (MIMO) system which is difficult to implement for the mobile terminals due to the limitations of the complexity, size and cost. So, these companies have been looking for a system which emulates a MIMO system. The cooperative relaying system has been proposed as a solution to be used to take the advantages of MIMO. The cooperative relaying system enables single antenna mobiles in a multi user environment to share their antennas and generate a virtual multiple antenna transmitters. In this paper, we investigate a single relay system that aims for a reliable communication. The main goal of this paper is to study the feasibility of the proposed single relay cooperative transmission in the mobile environment, and evaluate it with respect to the direct link transmission. Both systems are presented and a comparison in terms of bit error rate (BER) reveals that the single relay system performs better. The proposed single relay system needs an efficient coding technique to improve the performance in terms of reliability. Therefore, STBC as a coding technique is used, and the results proved that this technique decreases the BER.

Multiple transmit-receive antenna based wireless communication system is a well investigated area in the literature. However, within the scope of author’s knowledge there are few analytical frameworks which facilitate communication system design engineers to select the required transmit-receive antenna combination for a given quality of service (QoS) in terms of Bit Error Rate (BER) or Symbol Error Rate (SER). Most of such frameworks for Multiple-Input Multiple-Output (MIMO) wireless systems in the existing literature are lacking tightness between theoretical approximation and actual simulation results. The aim of investigation in this study is to provide theoretical expectation of receiver performance with MIMO wireless communication system within a given channel. In this study, new analytical performance bound frameworks with tighter lower bounds have been presented for different receivers for MIMO systems. On the basis of the presented analytical framework, a simulation platform has been established. The channel state information as well as expected quality of service is assumed to be known for simplicity. Rayleigh fading channel has been considered within simulation platform. Simulation results show that the proposed frameworks provide degree of tightness up to 100 times at Signal to Noise Ratio (SNR) 20 dB for (2x2) MIMO system in comparison to the existing frameworks. Few other MIMO antenna combinations have been considered in the evaluation process of the proposed framework.

This paper reports on investigations into the performance of a Multiple Input Multiple Output (MIMO) wireless communication system employing a uniform linear array (ULA) at the transmitter and either a uni-form linear array (ULA) or a uniform circular array (UCA) antenna at the receiver. The transmitter is as-sumed to be surrounded by scattering objects while the receiver is postulated to be free from scattering ob-jects. The Laplacian distribution of angle of arrival (AOA) of a signal reaching the receiver is postulated. The performance of bit error rate (BER), capacity and channel estimation for a MIMO system are evaluated for the two cases that the receiver is equipped with ULA or with UCA antennas.

Multiple-input multiple-output (MIMO) has been accepted as a promising technology for its potential to achieve low bit error rate (BER) by space time coding [1] or to achieve large capacity by multiplexing [2]. MIMO multiplexing has been widely adopted to realize high speed data communications. The capacity of MIMO systems in the point-to-point transmission without external interferences has been studied in [3, 4] to show that large capacity can be achieved in a rich scattering environment. In a cellular environment, the same frequency/frequencies can be used in neighboring cells. As a result, co-channel interference exists and the channel between the base-station (BS) and the mobile-station (MS) is changed from noise-limited channel to interference-limited channel. Recently, the capacity of MIMO systems in the cellular environment has attracted much interest. Uplink (transmission from MS to BS) capacity with variable-rate transmissions is studied in [5]. By modeling the co-channel interference as additive white Gaussian noise (AWGN), the uplink capacity is also studied in [6, 7]. On the other hand, from the users’ stand point, the downlink capacity may be more interesting. However, the results for the downlink capacity of cellular MIMO systems presented in the literature are mainly based on the simulation results. Very detailed simulation results for the downlink MIMO capacity in 3G FDD WCDMA cellular systems can be found in [8]. By assuming single-frequency-reuse (the frequency reuse factor (FRF) equals to 1), the capacity of downlink cellular MIMO systems is studied by simulations and the results are presented in [9, 10]. These results are given in terms of the number of antennas, the modulation schemes, the propagation parameters as well as the cell size. However, FRFs other than 1 are not considered. By taking various FRFs into consideration, a comparative study on the capacity of cellular MIMO systems is presented in [11]. A comprehensive comparison between the capacity of SISO, SIMO, STBC-MISO and MIMO systems in a cellular environment is made based on the simulation results. In general, fixed FRF has been considered in cellular systems. It is reported in [12] that a flexible FRF may help to improve the capacity for cellular single antenna (SISO) systems. However, flexible design of FRF for cellular MIMO systems is rarely available in the literature. In this chapter, the downlink capacity of cellular MIMO systems is theoretically analyzed in terms of both the ergodic and outage capacities. The theoretical results of the best and worst situation capacities suggest that the greatest capacities may be achieved by using FRF 1 or FRF 3 adaptively according to the situations. Therefore, a hybrid frequency reuse scheme is

The scaling up of antennae and terminals in large-scale multiple-input multiple-output (MIMO) systems helps increase the spectral efficiency at the penalty of prohibitive computational complexity. In conventional linear detection such as the minimum mean square error (MMSE) signal detection, the high complexity is mainly caused by solving the inversion of random matrix, especially in large-scale MIMO systems. In order to reduce the complexity of the matrix inversion, we proposed a low-complexity MMSE detection scheme based on symmetric successive over relaxation (SSOR) method, referred to as MSSD method. The proposed method exploits the channel hardening phenomenon, which means the off-diagonal terms of the HHH matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix H increases. In addition, we point out that the channel estimation scheme used in channel hardening-exploiting message passing receiver (CHEMP) is very suitable for the MSSD algorithm. For the considered large MIMO settings, simulation results show that the performance of the MSSD algorithm is very close to the classical MMSE detection algorithm with a small number of iterations.

This chapter is attempted to provide a survey of the advanced concepts and related issues involved in Multiple Input Multiple Output (MIMO) systems. MIMO system technology has been considered as a really significant foundation on which to build the next and future generations of wireless networks. The chapter addresses advanced MIMO techniques such as polarization diversity and antenna selection. We gradually provide an overview of the MIMO features from basic to more advanced topics. The first sections of this chapter start by introducing the key aspects of theMIMO theory. TheMIMO systemmodel is first presented in a genericway. Then, we proceed to describe diversity schemes used in MIMO systems. MIMO technology could exploit several diversity techniques beyond the spatial diversity. These techniques essentially cover frequency diversity, time diversity and polarization diversity. We further provide the reader with a geometrically based models for MIMO systems. The virtue of this channel modeling is to adopt realisticmethods for modeling the spatio-temporal channel statistics from a physical wave-propagation viewpoint. Two classes for MIMO channel modeling will be described. These models involve the Geometry-based Stochastic ChannelModels (GSCM) and the Stochastic channel models. Besides the listedMIMO channel models already described, we derive and discuss capacity formulas for transmission over MIMO systems. The achieved MIMO capacities highlight the potential of spatial diversity for improving the spectral efficiency of MIMO channels. When Channel State Information (CSI) is available at both ends of the transmission link, the MIMO system capacity is optimally derived by using adaptive power allocation based on water-filling technique. The chapter continues by examining the combining techniques for multiple antenna systems. Combining techniques are motivated for MIMO systems since they enable the signal to noise ratio (SNR) maximization at the combiner output. The fundamental combing techniques are the Maximal Ratio Combining (MRC), the Selection Combining (SC) and the Equal Gain Combining(EGC). Once the combining techniques are analyzed, the reader is introduced to the beamforming processing as an optimal strategy for combining. The use of multiple antennas significantly improves the channel spectral efficiency. Nevertheless, this induces higher system complexity of the communication system and the communication system performance is effected due to correlation between antennas that need to be deployed at the same terminal. As such, the antenna selection algorithm for MIMO systems is presented. To elaborate on this point, we introduce Space time coding techniques for MIMO systems and we evaluate by simulation the performance of the communication system. Next, we emphasis on multi polarization techniques for MIMO systems. As a background, we presume that the reader has a thorough understanding of antenna theory. We recall the basic antenna theory and concepts that are used throughout the rest of the chapter. We rigorously introduce the 3D channel model over the Non-Line of Sight (NLOS) propagation channel for MIMO system with polarized antennas. We treat the depolarization phenomena and we study its effect on MIMO system capacity. The last section of the chapter provides a scenario for collaborative sensor nodes performing distributed MIMO system model which is devoted to sensor node localization in Wireless Sensor Networks. The localization algorithm is based on beamforming processing and was tested by simulation. Our chapter provides the reader by simulation examples for almost all the topics that have been treated for MIMO system development and key issues affecting achieved performance.

Euclidean distance optimized antenna selection (EDAS) has proven to be able to achieve high transmit diversity gains for spatial modulation (SM) multiple-input multiple-output (MIMO) systems, but the exhaustive search over all possible antenna subsets may result in an intractable search complexity, especially for large-scale MIMO (LS-MIMO) systems. In this paper, a novel EDAS-equivalent criterion, relaying on matrix dimension reduction, is proposed to reduce the search complexity. Based upon this criterion, for small-scale SM-MIMO systems, a pair of transmit antenna selection (TAS) schemes, namely, the tree search based antenna selection (TSAS), and the decremental antenna selection (D-AS) schemes, are developed. Specifically, the TSAS scheme works by iteratively splitting the original Euclidean distance (ED) matrix into submatrices with smaller dimensions. TSAS achieves the same bit error rate (BER) performance as that of the exhaustive search at the cost of exponential search complexity. To address this issue, D-AS is carried out by excluding one specific transmit antenna from all the possible candidates in each iteration based on the channel information. D-AS is able to offer a near-optimal BER performance with a further reduction in terms of the search complexity. Moreover, we extend the D-AS scheme to LS-SM-MIMO systems by sorting all the ED elements with the low-complexity heapsort algorithm. Our simulation results show that the proposed D-AS algorithm outperforms conventional TAS schemes conceived for LS-SM-MIMO systems.