Performance Improvement of OFDM-IDMA with Modified SISO

Volume-2, Issue-2, March-April, 2014, pp. 26-33, IASTER 2014 www.iaster.com, Online: 2347-6109, Print: 2348-0017 Performance Improvement of OFDM-IDMA with Modified SISO A. Alagulakshmi PG Scholar, M.E. Communication Systems, Regional Centre of Anna University, Madurai, India V. Arun Assistant Professor, Department of ECE, Regional Centre of Anna University, Madurai, India ABSTRACT In this paper a revised SNR updating formula is proposed for OFDM-IDMA systems in Rayleigh fading channels. IDMA is a multi- user scheme in which chip interleavers are the only means of user separation. The receiver involves a chip-by-chip iterative multi-user detection. In this paper, we propose a multi-user system combining OFDM and IDMA in the mobile radio environment for the uplink. The OFDM-IDMA performance in terms of bit error rate and complexity is compared with that of IDMA with an Intersymbol Interference Cancellation technique, for quasi-static Rayleigh fading multipath channels. Our results show that the IDMA with Intersymbol Interference Cancellation exploits path diversity in an optimal manner when ISI and MAI are perfectly cancelled. Thus, it promises a good performance compared with the OFDM-IDMA when a priori information is perfectly estimated. However, we observe that during the iterative process, the OFDM-IDMA outperforms the IDMA with ISI Cancellation when user numbers increase. Indeed, the increase in the number of users requires the independent processing of MAI and ISI that is carried out in the OFDM- IDMA. Moreover, this study shows that the complexity of IDMA with the ISI Cancellation receiver is about L times that of the OFDM- IDMA, where L is the number of paths. The BER performance of IDMA based systems can be predicted by SNR evolution which tracks the average symbol SNR at each iteration and provides a faster solution than brute-force simulations. As the desired SNR in the evolution procedure is hard to obtain, approximate SNR updating formula has been widely adopted in the literature. Keywords: OFDM IDMA, Modified SISO, Rayleigh Fading. I. INTRODUCTION The use of the orthogonal frequency division multiplexing(ofdm) technique is currently an active field of research in the area of communication and has been used to develop wireless local area network (WLAN) systems, for example the IEEE 802.11a/g standards. New standardisation processes already foresee the application of OFDM in future WLAN and ultra- wide-band (UWB) systems. The concept underlying such a system is to modulate a number of mutually orthogonal sub-carriers with the input data. This enables the realization of high-speed transmission systems. However, the entire system performance depends on maintaining the orthogonality of the sub-carriers and failing to maintain this property results in detrimental effects for example inter- carrier interference (ICI) and inter-symbol interference (ISI) during signal reception. In a real system, the orthogonality property of the subcarriers can be disturbed during the RF up- and down-conversion and by the characteristics of the transmission channel. The key challenge faced by future wireless communication systems is to provide high-data-rate wireless access at high quality of service (QoS).Combined with the facts that spectrum is a scarce resource 26

and propagation conditions are hostile due to fading (caused by destructive addition of multipath components) and interference from other users, this requirement calls for means to radically increase spectral efficiency and to improve link reliability. Multiple-input multiple-output (MIMO) wireless technology seems to meet these demands by offering increased spectral efficiency through spatial multiplexing gain, and improved link reliability due to antenna diversity gain. Even though there is still a large number of open research problems in the area of MIMO wireless, both from a theoretical perspective and a hardware implementation perspective, the technology has reached a stage where it can be considered ready for use in practical systems. II. OFDM The use of the orthogonal frequency division multiplexing(ofdm) technique is currently an active field of research in the area of communication and has been used to develop wireless local area network (WLAN) systems, for example the IEEE 802.11a/g standards. New standardization processes already foresee the application of OFDM in future WLAN and ultra- wide-band (UWB) systems. The concept underlying such a system is to modulate a number of mutually orthogonal subcarriers with the input data. This enables the realization of high-speed transmission systems. However, the entire system performance depends on maintaining the orthogonality of the sub- carriers and failing to maintain this property results in detrimental effects for example inter-carrier interference (ICI) and inter-symbol interference (ISI) during signal reception. In a real system, the orthogonality property of the sub-carriers can be disturbed during the RF up- and down-conversion and by the characteristics of the transmission channel. The key challenge faced by future wireless communication systems is to provide high-data-rate wireless access at high quality of service (QoS).Combined with the facts that spectrum is a scarce resource and propagation conditions are hostile due to fading (caused by destructive addition of multipath components) and interference from other users, this requirement calls for means to radically increase spectral efficiency and to improve link reliability. Multiple-input multiple-output (MIMO) wireless technology seems to meet these demands by offering increased spectral efficiency through spatial multiplexing gain, and improved link reliability due to antenna diversity gain. Even though there is still a large number of open research problems in the area of MIMO wireless, both from a theoretical perspective and a hardware implementation perspective, the technology has reached a stage where it can be considered ready for use in practical systems. A. Existing Methods The channel capacity for a MIMO system is increased as the number of antennas is increased, proportional to the smaller of the number of transmit antennas and the number of receive antennas. This is known as the multiplexing gain. The entire MIMO SVD link can be approximated by the average of the SER of Nakagami-m channels. This leads to characterize the eigen channels of N N MIMO channels with N larger than 14. It is also shown that 75% of the total mean power gain of the MIMO SVD channel. 27

B. Problem Statement Interleave division multiple access is one of the most suitable candidate for future wireless communications because of its power efficiency and low decoding complexity. We will discuss the complexity issues of IDMA in this work. In multiple access techniques multiple access interference (MAI) introduced by other users poses a serious problem and complex multi user detectors (MUD) that jointly decode all user s data are used at the receiver. But, the use of MUD increases the complexity of the decoding, for example as in the case of CDMA. Previous work has suggested that by using turbo-type MUD to remove the MAI, the decoding complexity of IDMA is independent of the number of users, whereas in other types of codes the decoding complexity is dependent on the number of users. Also, mutipath fading increases the decoding complexity. In such cases, OFDM along with IDMA solves the problem decoding complexity with multipath fading. This is called as OFDM-IDMA. But, still when the number of users is more the computational complexity at the receiver is more. We observe that decoding complexity of OFDM-IDMA is linear in the number of users sharing a particular subcarrier rather than the number of users of the system. Here, the key idea is each idea is every user is assigned a a channel only on a prescribed subcarrier called Grouped-OFDM IDMA. In G-OFDM IDMA, users and subcarriers are divided into a number of groups and each user group s data is only transmitted on the corresponding group of subcarriers. The work also shows that this design is capable of reducing the complexity but still preserves the bit error probability (BEP) and bandwidth efficiency of conventional OFDM IDMA. III. PROPOSED SYSTEM Discrete-time channel model with pulse shaping. A. MIMO OFDM Figure - 1 MIMO-OFDM is a multi-carrier system where data bits are encoded to multiple sub-carriers, while being sent simultaneously. This results in the optimal usage of bandwidth. A set of orthogonal sub-carriers together forms a MIMO-OFDM symbol. To avoid ISI due to multi-path, successive MIMO- OFDM symbols are separated by guard band. This makes the MIMO-OFDM system resistant to multi- path effects. Although MIMO-OFDM in theory has been in existence for a long time, recent developments in DSP and VLSI technologies have made it a feasible option. Many wired and wireless standards like DVBT, DAB, xdsl and 802.11a have adopted MIMO-OFDM. 28

This paper first lists various approaches to implement a MIMO-OFDM system. It then describes the VLSI implementation of MIMO- OFDM in details. Specifically the 802.11a MIMO-OFDM system has been considered in this paper. However, the same considerations would be helpful in implementing any MIMO- OFDM system in VLSI. MIMO-OFDM is a multi-carrier system where data bits are encoded to multiple sub-carriers. Unlike single carrier systems, all the frequencies are sent simultaneously in time. MIMO-OFDM offers several advantages over single carrier system like better multi-path effect immunity, simpler channel equalization and relaxed timing acquisition constraints. But it is more susceptible to local frequency offset and radio front-end non-linearity. The frequencies used in MIMO-OFDM system are orthogonal. Neighboring frequencies with overlapping spectrum can therefore be used. This property is shown in the figure where f1, f2 and f3 orthogonal. This results inefficient usage of BW. The MIMO-OFDM is therefore able to provide higher data rate for the same BW MIMO- OFDM is fast gaining popularity in broadband standards and high speed wireless LAN. Orthogonal Frequency Division Multiplexing (O FDM) is one of the most promising physical layer technologies for high data rate wireless communications due to its robustness to frequency selective fading, high spectral effciency, and low computational complexity. OFDM can be used in conjunction with a Multiple-Input Multiple-Output (MIMO) transceiver to increase the diversity gain and/or the system capacity by exploiting spatial domain. Because the OFDM system effectively provides numerous parallel narrowband channels, MIMO-OFDM is considered a key technology in emerging high-data rate systems such as 4G, IEEE 802.16, and IEEE 802.11n. Fig 2. MIMO-OFDM Block Diagram MIMO communication uses multiple antennas at both the transmitter and receiver to exploit the spatial domain for spatial multiplexing and/or spatial diversity. Spatial multiplexing has been generally used to increase the capacity of a MIMO link by transmitting independent data streams in the same time slot and frequency band simultaneously from each transmit antenna, and differentiating multiple data streams at the receiver using channel information about each propagation path. In contrast to spatial multiplexing, the purpose of spatial diversity is to increase the diversity order of a MIMO link to mitigate fading by coding a signal across space and time so that a receiver could receive the replicas of the signal and combine those received signals constructively to achieve a diversity gain. Figure 3 MIMO-OFDM systems, channel state information (CSI) is essential at the receiver in order to coherently detect the received signal and to perform diversity combining or spatial interference 29

suppression. The channel is very important to the performance of diversity schemes, and more variable channels give more diversity. Thus, in order to attain accurate CSI at the receiver, pilot-symbol-aided or decision- directed channel estimation must be used to track the variations of the frequency selective fading channel. Among the various resources in MIMO multicarrier systems the power assignment is related to the accuracy of the channel estimation. Pilot symbols facilitate channel estimation, but in addition to consuming bandwidth, they reduce the transmitted energy for data symbols per OFDM symbol under a fixed total transmit power condition. This suggests a tradeoff between the system capacity and the accuracy of the channel estimation in MIMO-OFDM systems according to the power allocation when the total transmits power is fixed. Figure 4 B. MIMO-OFDM Transceiver Each sub-carrier in an MIMO-OFDM system is modulated in amplitude and phase by the data bits. Depending on the kind of modulation technique that is being used, one or more bits are used to modulate each sub-carrier. Modulation techniques typically used are BPSK, QPSK, 16QAM, 64QAM etc. The process of combining different sub-carriers to form a composite time-domain signal is achieved using Fast Fourier transform. Different coding schemes like block coding; convolution coding or both are used to achieve better performance in low SNR conditions. Interleaving is done which involves signing adjacent data bits to non-adjacent bits to avoid burst errors under highly selective fading. Block diagram of a MIMO- OFDM transceiver is shown below. Figure 5 The FFT processor is the most speed critical part in the multi-carrier orthogonal frequency division multiplexing (OFDM) communication system. In these systems, low power is usually one of the major concerns. This project propose a memory-based recursive FFT design in CPLD for the low power base-band OFDM transmitter and receiver for WiMax (wireless metropolitan area network) application. It is implemented by radix-8 FFT. As results, the power consumption will be reduced by 28% compared to radix- 4 FFT. The proposed architecture has three advantages: (1) fewer butterfly iterations to reduce power consumption, (2) pipeline of radix-8 butterfly to speed up clock frequency, (3) even distribution of memory access to make the best utilization efficiency of SRAM ports. Figure 6 30

IV. SIMULATION Plot of snr v/s ber for an ofdm system with ls/base/prop estimator based receivers Figure 7 Plot of SNR v/s AVG MSE for an OFDM system with ls/base/prop estimator based receivers Figure 8 Plot of SNR v/s symbol error rate for an OFDM system with ls/base/prop estimator based receivers V. CONCLUSIONS Figure 9 The BER performance of IDMA based systems can be predicted by SNR evolution which tracks the average symbol SNR at each iteration and provides a faster solution than brute-force simulations. As the desired SNR in the evolution procedure is hard to obtain, approximate SNR updating formula has been widely adopted in the literature. 31

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