View of A REVIEW ON MULTIPLE-INPUT MULTIPLE-OUTPUT OFDM WITH INDEX MODULATION

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ACCENT JOURNAL OF ECONOMICS ECOLOGY & ENGINEERING

Vol.03, Issue 05, May 2018, Available Online: www.ajeee.co.in/index.php/AJEEE

Paper Id /Ajeee-1302

A REVIEW ON MULTIPLE-INPUT MULTIPLE-OUTPUT OFDM WITH INDEX MODULATION

1AMY ALICE KUJUR

1M. Tech scholar BTIRT

2RAJEEV SARASWAT

2Assistant Prof.BTIRT

Abstract:- The major requirements in the wireless communication system are to increase the speed, range and reliability of the system by using a Multi User and Multi Carrier Modulation scheme like MIMO-OFDM. The MIMO-OFDM is designed for high speed data rate, higher spectral efficiency and lower latency by using beam forming and multiplexing techniques therefore it is used in Long Term Evolution-Advanced(LTE-A) systems. Multiple Input Multiple Output (MIMO) uses the multiple antennas at the transmitter and receiver. A MIMO antenna adapts itself to pick a user signal, in any direction without the user intervention. OFDM is a popular method for high data wireless transmission. OFDM may be combined with antenna arrays at the transmitter and receiver to increase the diversity gain and /or to enhance the system capacity in a time-variant and frequency selective channels resulting in a MIMO configuration.

Key Term:-OFDM, spatial modulation (SM), MIMO systems, maximum-likelihood detection.

INTRODUCTION

Multiple Input Multiple Output (MIMO)is a radio communication technology is used in many new technologies in these days.

Wi-Fi, LTE (Long Term Evolution) and many other radio and wireless technologies are using the concept of MIMO to provide an increased link capacity, spectral efficiency and data rate.

Even now there are many MIMO wireless routers in the market, and as this radio communications technology is becoming more widespread and popular. The MIMO routers and other concepts of wireless MIMO are elaborated in [1]. MIMO is effectively a radio antenna technology as shown in fig(1). It uses multiple antennas at the transmitter and receiver to enable a variety of signal paths to carry the data, choosing separate paths for each antenna to enable multiple signal paths between the transmitter and the receiver. The variety of paths available occurs as a result of the number of objects that appear to the side or even in the direct path between the transmitter and receiver. Previously these multiple paths only served to introduce interference.

By using MIMO, these additional paths can be used to increase the capacity of a link. To take advantage of this in a MIMO wireless system, the transmitted data must be encoded using what is termed as the space-time code to allow the receiver to extract the fundamental transmitted data from the

received signals. The space-time code optimizes the Signal to Noise (SNR) ratio, and the codes used define the performance gain that can be achieved and obviously the more gain that is achieved, the more processing power is required [2].

LITERATURE SURVEY

Beixiong Zheng et al.[1] “Multiple-Input Multiple-Output OFDM with Index Modulation: Low-Complexity Detector Design”,in this paper proposed two lowcomplexity detectors derived from the SMC theory for the MIMO-OFDMIM system. The firstproposed subblock-wise detector draws samples at the subblock level, exhibiting near-optimal performance for the MIMO OFDMIMsystem. The second proposed subcarrier-wise detector draws samples at the subcarrier level,

exhibiting substantially

reducedcomplexity with a marginal performance loss. An effective legality examination method has been also developed to couple with thesubcarrier wise detector. Computer simulation and numerical results have validated the outstanding performance and the lowcomplexity of both proposed detectors.

Ertu˘grulBas¸ar et al.[2] “Multiple-Input Multiple-Output OFDM with Index Modulation”, A novel scheme called MIMOOFDMwith index modulation has been proposed as an alternative multicarrier transmission technique for 5G networks. It has beenshown via extensive computer simulations that the

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proposed scheme can provide significant BER performance improvements overclassical MIMO-OFDM for several different configurations.

The following points remain unsolved in this study:

i) performanceanalysis,

ii) the selection of optimal N and K values,

iii) diversity techniques for MIMO- OFDM-IM, and

iv) Implementationscenarios for high mobility.

Ertugrul Basar et al.[3] “On Multiple- Input Multiple-Output OFDM with Index Modulation for Next Generation WirelessNetworks”, In this study, the recently proposed MIMO-OFDM-IM scheme has been investigated for next generation 5G wirelessnetworks. For the MIMO-OFDM-IM scheme, new detector types such as ML, near-ML, simple MMSE, MMSE-LLR-OSICdetectors have been proposed and their ABEP have been theoretically examined. It has been shown via extensive computersimulations that MIMO-OFDM-IM scheme provides an interesting trade-off between complexity, spectral efficiency and errorperformance compared to classical MIMO-OFDM scheme and it can be considered as a possible candidate for 5G wirelessnetworks.

The main features of MIMO-OFDM-IM can be summarized as follows:

i) better BER performance,

ii) flexible systemdesign with variable number of active OFDM subcarriers and

iii) better compatibility to higher MIMO setups. However, interesting topics such as diversity methods, generalized OFDM-IM cases, high mobility implementation and transmit antenna indicesselection still remain to be investigated for the MIMO-OFDM-IM scheme.

Ertu˘grulBas¸ar et al.[4] “Performance of Multiple-Input Multiple-Output OFDM with Index Modulation”, In this paper,proposed ML and near-ML detectors for the recently introduced MIMO-OFDM-IM scheme to improve its error performancecompared to MMSE based detection. The ABEP upper bound of the MIMO-OFDM-IM scheme with ML

detection has beenderived and it has been shown that the derived theoretical upper bound can be used as an efficient tool to predict the BERperformance of the MIMO- OFDMIM scheme. It has been shown via computer simulations that MIMO- FDM- IM scheme canprovide significant improvements in BER performance over classical MIMO-OFDM using different

type of detectors and

MIMOconfigurations.

Beixiong Zheng et al.[5] “Low-Complexity ML Detector and Performance Analysis for OFDM With In-Phase/QuadratureIndex Modulation”, In this letter, we've planned a low-complexity detector supported the milliliter criterion, that dispenses with apriori data of the noise variance and also the potential realizations of the active subcarrier indices. Supported the framework ofOFDM-I/Q-IM using the planned milliliter detector, the straight line ABEP and also the actual coding gain achieved by OFDMI/Q-IM are derived, that absolutely matches the simulation results. Moreover, the exact coding gain including the spectralefficiency price has provided a clear plan of a basic trade-off between the system performance and also the spectral efficiency ofOFDM-I/Q-IM by the adjustment of the quantity of active subcarriers.Sheng Wu et al.[6] “Low- Complexity Iterative Detection for Large- Scale Multiuser MIMO-OFDM Systems UsingApproximate Message Passing”, For the detection of large-scale multiuser MIMO-OFDM systems, we have proposed a range oflow-complexity approximate message passing algorithms that can offer desirable tradeoff between performance and complexity. Itis verified through extensive simulations that our proposed approximate message passing algorithms can achieve near optimalperformance with low complexity. Compared with existing turbo detection algorithms, the proposed schemes can achieve or evenoutperform the performance of some complex algorithms, such as the iterative decoding based on STS-SD and MMSESIC. Inaddition, the number of iterations required to achieve near- optimal performance is small and does not increase with the systemdimension.

OFDM SYSTEM

Orthogonal frequency division multiplexing (OFDM) [8] is a multi-carrier modulation technique which has high

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spectral efficiency and higher data rates.

The performance of OFDM system is better than over frequency selective fading channel. To ensure linear amplification of a signal with a large PAPR, the amplifier has to be operated with a large input back off (IBO), which means that the mean power has to be chosen sufficiently low, leading to a very low efficiency of the amplifier. If the IBO is chosen too small, the signal will be distorted.

The main drawback of OFDM is the high peak-to-average power ratio (PAPR)which is reduce the power efficiency of a HPA (High Power Amplifier).OFDM is a special form of multi carrier modulation and painful Inter Symbol Interference (ISI) by multiplexing the data on orthogonal property. OFDM can be combined with MIMO to increase the system capacity and performances many techniques to deal with the PAPR problem. The techniques amplitude clipping, clipping and filtering, coding, tone reservation, tone injection, active constellation extension, partial transmit sequence, selected mapping, and interleaving.

The SLM techniques achieve PAPR reductions but the power increase, bit error rate increase and computational complexity increase. Optimal bit loading and subcarrier allocation problems for multiuser OFDM have been formulated in, specifically minimization of the overall transmit power under data constraint, and maximization of the data rate under power constraint. These are non-linear optimization problems which can be broadly divided into two categories:

Margin Adaptive (MA) and Rate Adaptive (RA) optimization.

It is difficult to solve these problems unless the integer variables are relaxed to allow real numbers. These classical algorithms are computationally intensive due to the nature of non-linear optimization.

However, OFDM systems have the undesirable feature of a large Peak to Average Power Ratio (PAPR) of the transmitted signals. Consequently to prevent the spectral growth of the OFDM signal, the transmit amplifier must operate in its linear regions. Therefore, power amplifiers with a large linear region are required for OFDM systems, but such amplifiers will continue to be a major cost component of OFDM systems.

Consequently, reducing the PAPR is pivotal to reducing the expense of OFDM systems. However, the increase in bandwidth is an impractical method, and an alternate solution is to adopt some spectral efficient techniques like MIMO systems [21]. The key advantage of employing multiple antennas is to get reliable performance through diversity and the achievable higher data rate through spatial multiplexing.

MIMO SYSTEM

Digital communication using Multiple- Input Multiple-Output (MIMO) systems is one in all the most important technical breakthroughs in modem communication.

MIMO systems are simply outlined because the systems containing multiple transmitter antennas and multiple receiver antennas. Communication theories show that MIMO systems will offer a probably very high capability that, in several cases, grows some linear with the quantity of antennas. Recently, MIMO systems have already been implemented in wireless communication systems, particularly in wireless LANs (Local area Networks). Completely different structures of MIMO systems have additionally been planned by industrial organizations within the Third Generation Partnership Project (3GPP) standardizations, as well as the structures planned.

The core plans below the MIMO systems are that the ability to show multi- path propagation, that is usually an obstacle in typical wireless communication, into a profit for users.

The main feature of MIMO systems is space-time process. Space-time Codes (STCs) are the codes designed for the utilization in MIMO systems. Space-Time Codes (STCs) are the codes designed for the use in MIMO systems. In STCs, signals are coded in both temporal and spatial domains. Among different types of STCs, orthogonal Space-Time Block Codes (STBCs) possess a number of advantages over other types of STCs.

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Fig.1: MIMO System PROBLEM FORMULATION

MIMO system has three technical advantages, such as Beam forming technology, Spatial Diversity based on space-time coding and spatial multiplexing. Space-time coding can be used to achieve high diversity gains of MIMO systems. It can reduce the symbol error probability due to channel fading and noise by joint coding of the data stream. It can also increase the redundancy of signal by joint-coding, and gain a spatial diversity of signal in the receiver. We can take advantage of the additional diversity gain to improve the reliability of communication links. And we can improve data transfer rate and spectral efficiency by using higher order modulation under the same reliability of links. There is also a need of BER distribution with different comparison point and perform the comparison with the SNR.After studying and analyzing

several research works in the direction of MIMO-OFDM system, we can suggest some following points which can be improved or there is the need of betterment in the field.

The points are following:

1. High rate STBC systems have attracted a lot of interest since they are required to build high

throughput wireless

communication systems.

2. The techniques studied in this work can be applied to future research in this area. Research on high rate STBCs for MIMO systems with a large number of transmit and receive antennas, such as 4,8 or 16 transmit and receive antennas, is an active topic, since such systems can provide large diversity and multiplexing gain can be a good research area.

3. Hybrid framework is needed.

CONCLUSION

In this paper we survey several aspects for MIMO-OFDM. However, the performance of multiple antennas can be improved if channel state information obtained at the receiver is fed back to the transmitter. Exploiting partial channel knowledge at the transmitter, two simple channel adaptive transmission schemes, namely, channel adaptive code selection and channel adaptive transmit antenna selection can been used.