Study Of Multiple Antenna Systems: Capacity, Diversity Gain And Spatial Multiplexing (original) (raw)
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Realization of MIMO Channel Model for Spatial Diversity with Capacity and SNR Multiplexing Gains
International Journal of Computer Information Systems and Industrial Management Applications, 2020
Multiple input multiple output (MIMO) system transmission is a popular diversity technique to improve the reliability of a communication system where transmitter, communication channel and receiver are the important elements. Data transmission reliability can be ensured when the bit error rate is very low. Normally, multiple antenna elements are used at both the transmitting and receiving section in MIMO Systems. MIMO system utilizes antenna diversity or spatial diversity coding system in wireless channels because wireless channels severely suffer from multipath fading in which the transmitted signal is reflected along various multiple paths before reaching to the destination or receiving section. Overwhelmingly, diversity coding drives multiple copies through multiple transmitting antennas (if one of the transmitting antenna becomes unsuccessful to receive, other antennas are used in order to decode the data) for improving the reliability of the data reception. In this paper, the MIMO channel model has been illustrated. Moreover, the vector for transmitting signal has been considered by implementing least square minimization as well as linear minimum mean square estimation. Parallel transmission of MIMO system has also been implemented where both the real part and imaginary part of the original, detected and the corresponding received data sequence has been described graphically. One of the important qualities of MIMO is a substantial increase in the capacity of communication channel that immediately translates to comparatively higher signal throughputs. The MIMO communication channels have a limited higher capacity considering the distortions for various deterministic channel recognitions and SNR. The MIMO channel average capacity is achieved more than 80% for dissimilar levels of impairments in transceiver when the value of kappa (Level of impairments in transmitter hardware) reduces from 0.02 to 0.005. The finite-SNR multiplexing gain (Proportion of MIMO system capacity to SISO system capacity) has been observed for deterministic and uncorrelated Rayleigh fading channels correspondingly. The core difference is in the high SNR level. It may occur for two reasons: (a) there is a quicker convergence to the limits under transceiver impairments (b) deterministic channels that are built on digital architectural plans or topographical maps of the propagation environment acquire an asymptotic gain superior than multiplexing gain when the number of transmitting antenna is greater than the number of receiving antenna.
Evaluating Multiple Antenna Diversity Techniques for Transmission over Fading Channels
Diversity is a powerful technique to mitigate fading, hence multiple antenna diversity which includes; multiple devices, spatial diversity, cooperative diversity which uses multiple-element transmitter arrays enhance performance greatly in modern wireless communication networks. Appropriate combining at the receiver realizes diversity gain. major interest in this write up is the MIMO {Multiple-input and Multiple-output} antenna method, it is one of the best forms of smart antenna technology and Dynamic control processes for reducing fading over channels by multiple antenna diversity techniques
Study the Performance of Capacity for SISO, SIMO, MISO and MIMO in Wireless Communication
Journal of Network and Information Security, 2020
Due to the rapid development of the wireless communication system, it is highly required a reliable system which can provide higher channel capacity and higher data transmission rates for the users. These are obtained by the Multiple Input Multiple Output (MIMO) systems because the MIMO systems allow the spatial diversity and spatial multiplexing technique due to its multiple antennas at both transmitter and receiver side. The aim of this paper is to discuss and show the capacity performance between SISO, SIMO, MISO and MIMO systems. In this paper, we will mainly be focused on the MIMO system due to its higher capacity and higher data transmission rates properties. For these properties of the MIMO systems, it will be perfectly suitable for modern communication technology.
A new approach to diversity and multiplexing gains for wideband MIMO channels
IEEE Transactions on Wireless Communications, 2007
In this paper, a new approach to improving reliability and bandwidth efficiency in communications over frequencyselective channels using multiple antennas is proposed. In the heart of the new approach is a novel space-time orthogonal frequency division multiplexing (OFDM) scheme. The proposed space-time OFDM modulator translates a multiple-input multiple-output (MIMO) channel into a single-input multipleoutput (SIMO) channel without the loss of system freedom (the available diversity gain). This translation simplifies code design as compared to that in the conventional MIMO OFDM approach. Instead of more complicated space-time codes, codes that are designed for single-input fading channels can be used with the proposed space-time modulation. For bandwidth-efficient applications, a channel multiplexing scheme is developed to work with the space-time modulator. Unlike the conventional spatial multiplexing schemes, an arbitrary number of data streams can be created and each layer occupies all the transmit antennas all the time. As a result, all the available degrees of freedom are preserved for each layer and a full range of optimal tradeoffs between data rate and reliability is possible. Several examples are given to demonstrate the advantages of the proposed approach over the conventional MIMO OFDM approach.
Channel Capacity Improvement of MIMO Communication Systems using Different Techniques
Tikrit Journal of Engineering Sciences
The modern communication systems require high data, and this rate cannot be achieved in Single input-Single out put (SISO) systems. This prosperity can be gained by improving the channel capacity using systems for Multiple Input-Multiple output (MIMO). In this paper the parameters effecting channel capacity are studied, these include (antennas numbers, antennas distribution, and Signal to Noise Ratio (SNR)) using multiplexing, diversity and beamforming techniques. The results showed that the channel capacity for multiplexing technique increased semi-linearly with antennas number when the antennas at transmitter side and receiver side are equal. While the increase in capacity became less when the antennas distribution is different. Increasing the antennas ate the receiver side gives better capacity than increasing the antennas ate the transmitter side. The multiplexing techniques give the best performance from diversity techniques and beamforming when (SNR) greater than (10 dB). While the beamforming technique gives the best performance for (SNR) less than (10 dB).
MIMO channels: optimizing throughput and reducing outage by increasing multiplexing gain
TELKOMNIKA Telecommunication Computing Electronics and Control, 2020
The two main aims of deploying multiple input multiple out (MIMO) are to achieve spatial diversity (improves channel reliability) and spatial multiplexing (increase data throughput). Achieving both in a given system is impossible for now, and a trade-off has to be reached as they may be conflicting objectives. The basic concept of multiplexing: divide (multiplex) transmit a data stream several branches and transmit via several (independent) channels. In this paper, we focused mainly on achieving spatial multiplexing by modeling the channel using the diagonal Bell Labs space time scheme (D-BLAST) and the vertical Bell Labs space time architecture (V-BLAST) Matlab simulations results were a lso given to further compare the advantages of spatial multiplexing. Keywords: Diversity MIMO Multiplexing Reliability Spatial Throughput This is an open access article under the CC BY-SA license. 1. INTRODUCTION The need for and data rates and a high quality of service (QoS). Over the years, the ubiquity offered by wireless communication has made it the more preferred means over wired; hence, there has been an increase in research on how to improve the modulation schemes used over the air interface. Multiple input multiple output (MIMO) offers desirable properties that meet most of the requirement stated above. By using multiple output multiple input (MIMO) systems, diversity gain mitigates fading, increases coverage and improves QoS. Multiplexing gain increases capacity and spectral efficiency with no additional power or bandwidth expenditure [1]. The core idea under the MIMO systems is the ability to turn multi-path propagation, which is typically an obstacle in conventional wireless communication, into a benefit for users [2]. With MIMO, the capacity of a communication system increases linearly with the number of antennas, thereby achieving an increase in spectral efficiency, without requiring more resources in terms of bandwidth and power [3-5]. From Figure 1 shows that MIMO technology has two main objectives which it aims to achieve: high spatial multiplexing gain and high spatial diversity. To attain spatial multiplexing, the system is made to carry multiple data stream over one frequency, simultaneously-form multiple independent links (on same channel) between transmitter and receiver to communicate at higher data rates. In low SNR environment, spatial diversity techniques are applied to mitigate fading and the performance gain is typically expressed as diversity gain (in dB) [6]; for higher SNR facilitates the use of spatial multiplexing (SM), i.e., the transmission of parallel data streams, and information theoretic capacity in bits per second per Hertz (bits/s/Hz) is the performance measure of choice [7]. Spatial diversity works on the principle of transmission
On Diversity and Multiplexing Gain of Multiple Antenna Systems with Transmitter Channel Information
allerton conference on communication, control, and computing, 2004
We quantify the multiplexing-diversity tradeoff of a multiple-input multiple-output (MIMO) system, when the channel state information (CSI) is known perfectly at the receiver and partially at the transmitter. The partial knowledge of CSI at the transmitter consists of the quantized value of one of the eigenvalues and perfect knowledge of eigenvectors of the channel matrix. The key result is that while multiplexing gain cannot be increased beyond minimum number of transmit and receive antennas, diversity order for each multiplexing gain can be substantially increased by using only a few bits of feedback at the transmitter. For example, with 1 bit of feedback in a 2 × 3 system, for multiplexing gains of 0, 1, and 2, diversity gains of 42, 6, and 2 can be achieved, respectively. Thus, while the tradeoff between diversity advantage and multiplexing gain is still present, its behavior is significantly changed by channel knowledge at the transmitter. The major reason for this different tradeoff can be attributed to addition of long-term power control, which allows the transmitter to switch between modes for reducing outage and increasing throughput based on signal to noise ratio along different eigenvalues.
International Journal of Research, 2018
This paper indicates that antenna diversity method for the wireless multiple antenna system. In wireless communication fading accumulate in the channel is major apprehension .So the antenna diversity is used to mitigate the the effect of fading over the channel at the relatively less cost. The most commonly antenna diversity technique is space time block code (STBC) provides transmit diversity and maximum ratio combining (MRC) provides receiver diversity in wireless technology is case of multiple-input multiple-output (MIMO) systems. The most commonly employed antenna diversity is Maximal Ratio Receiver Combining (MRRC) in which several uncorrelated replica of the signals with weight values are combined at the receiver in order to achieve improved reconstructed signals. This paper presenting Maximal Ratio Receiver Combining (MRRC) receiver diversity technique to mitigate the effect of Rayleigh fading channel. The simulation result are based on BER performance for systems with sin...
Eswar Publications, 2024
This paper has presented capacity analysis of multiple antenna wireless system under different array and channel configurations. In this study, the dimension of conventional multiple input multiple output (MIMO) system was extended to large scale MIMO. The capacity of MIMO system was considered over spatially correlated Rayleigh channel. The parameters of interests used for the system analysis are the channel capacity (measured in terms of data transfer rate) in bit per second/ hertz (bps/Hz), signal to noise ratio (SNR) in dB, spacing between the antennas, and the number of antenna elements. A MATLAB model was developed for the system for the purpose of simulation analysis to examine channel capacity performances under different antenna arrangement and channel configurations. Simulation results revealed that the capacity of the system increases as the number of antennas at both transmit and receive ends increases. Generally, the uncorrelated channel provided better capacity than correlated channel in all cases. However, the capacity of the correlated channel offers more practical results than uncorrelated channel.