International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 7, July 2015)

Compressive Sensing for OFDM Systems Based Channel Estimation under Long Delay Channels Shail Prakash Singh1, Rashmi Pandey2 1

M.Tech Scholar, 2Asst. Professor, VIT Bhopal There are various methods to channel estimation such as: with or without a need to parametric models, blind or pilot based methods, frequency and/or time domain analysis, adaptive or non adaptive techniques. Among these mentioned methods, channel estimation in OFDM systems is often done in frequency domain using pilot symbols or training data [2]. The least square and minimum meansquare error (MMSE) are conventional linear channel estimation techniques which are based on pilot arrangement. The LS method is less complicated and simple respect to other methods and consequently is used to channel estimation, but it has a serious drawback which is more sensitive to channel noise. MMSE estimator has better performance than LS method but suffers from a high computational complexity because it requires knowledge of the channel statistics and the signal-to-noise ratio (SNR) [3]. Some different methods have been developed to reduce the complexity and improve the performance of the MMSE estimation such as modified MMSE and singular value decomposition (SVD) [4-5]. 1n 2006 Noh et al. proposed a method to decomposing the covariance matrix to the simple and low order sub matrix so that they can decrease the complexity of MMSE method [6]. Hsieh used a comb type pilot arrangement and second order interpolation method to channel estimation [7]. Coleri et al. compared the results of many interpolation techniques to channel estimation with Rayleigh fading such as linear, second order, cubic, low pass filtering and spline interpolation methods The recently introduced principle and methodology of compressed sensing (CS) allows the efficient reconstruction of sparse signals from a very limited number of measurements (samples) [1, 2]. CS has gained a fast-growing interest in applied mathematics. In this paper, we apply CS to pilotbased channel estimation in highly mo-bile environments. We consider pulse-shaping multicarrier (MC) systems, which include orthogonal frequency-division multiplexing (OFDM) as a special case [3]. Conventional methods for channel estimation (e.g., [4]) are not able to exploit the inherent sparsity of the transmission channel that is due to the sparse distribution of scat-terers in space.

Abstract— Time-domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) has advantages in spectral efficiency and synchronization. However, its iterative interference cancellation algorithm will suffer from performance loss especially under severely fading channels with long delays and has difficulty supporting high-order modulations like 256 QAM, which may not accommodate the emerging ultra-high definition television service. To solve this problem, a channel estimation method for OFDM under the framework of compressive sensing (CS) is proposed in this paper. Firstly, by exploiting the signal structure of recently proposed time-frequency training OFDM scheme, the auxiliary channel information is obtained. Secondly, we propose the auxiliary information based subspace pursuit (A-SP) algorithm to utilize a very small amount of frequency domain pilots embedded in the OFDM block for the exact channel estimation. Moreover, the obtained auxiliary channel information is adopted to reduce the complexity of the classical SP algorithm. Simulation results demonstrate that the CS-based OFDM outperforms the conventional dual pseudo noise padded OFDM and CS-based TDS-OFDM schemes in both static and mobile environments, especially when the channel length is close to or even larger than the guard interval length, where the conventional schemes fail to work completely. Keywords— Channel estimation (CE), QAM-256, Compressive sensing(CS), long delays, TS-OFDM

I. INTRODUCTION OFDM is a signaling technique that has been applied widely in wireless communication systems due to its ability to maintain effective transmission and highly efficient bandwidth utilization in the presence of various channel impairments which one of them is frequency selective fading. In OFDM systems the available spectrum are divided into many orthogonal sub-channels, which are instantaneously used to data transmission. Also, in this technique the inter-symbol interference (ISI) which is induced due to frequency selective channels can be reduced by adding the cyclic prefix (CP) [1]. In OFDM systems, channel estimation is necessary to obtain the channel state information (CSI), reducing the bit error rate and also to achieve a distortion less output data.

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International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 7, July 2015) As we will demonstrate, CS provides a constructive way for exploiting this sparsity in order to reduce the number of pi-lots and, hence, increase spectral efficiency. Radio transmission has allowed people to communicate without any physical connection for more than hundred years. When Marconi managed to demonstrate a technique for wireless telegraphy, more than a century ago, it was a major breakthrough and the start of a completely new industry. May be one could not call it a mobile wireless system, but there was no wire! Today, the progress in the semiconductor technology has made it possible, not to forgot affordable, for millions of people to communicate on the move all around the world. The Mobile Communication Systems are often categorized as different generations depending on the services offered. The first generation comprises the analog frequency division multiple access (FDMA) systems such as the NMT and AMPS (Advanced Mobile Phone Services). The second generation consists of the first digital mobile communication systems such as the time division multiple access (TDMA) based GSM (Global System for Mobile Communication), D-AMPS (Digital AMPS), PDC and code division multiple access (CDMA) based systems such as IS-95. These systems mainly offer speech communication, but also data communication limited to rather low transmission rates. The third generation started operations on 1st October 2002 in Japan. During the past few years, there has been an explosion in wireless technology. This growth has opened a new dimension to future wireless communications whose ultimate goal is to provide universal personal and multimedia communication without regard to mobility or location with high data rates. To achieve such an objective, the next generation personal communication networks will need to be support a wide range of services which will include high quality voice, data, facsimile, still pictures and streaming video. These future services are likely to include applications which require high transmission rates of several Mega bits per seconds (Mbps). In the current and future mobile communications systems, data transmission at high bit rates is essential for many services such as video, high quality audio and mobile integrated service digital network. When the data is transmitted at high bit rates, over mobile radio channels, the channel impulse response can extend over many symbol periods, which leads to inter symbol interference (ISI). Orthogonal Frequency Division Multiplexing (OFDM) is one of the promising candidates to mitigate the ISI.

In an OFDM signal the bandwidth is divided into many narrow sub channels which are transmitted in parallel. Each sub channel is typically chosen narrow enough to eliminate the effect of delay spread. By combining OFDM with Turbo Coding and antenna diversity, the link budget and dispersive-fading limitations of the cellular mobile radio environment can be overcome and the effects of cochannel interference can be reduced. II. MODULE a. ML Estimation of Time and Frequency Offset in OFDM Systems Orthogonal frequency-division multiplexing (OFDM) systems have recently gained increased interest. OFDM is used in the European digital broadcast radio system and is being investigated for other wireless applications such as digital broadcast television and mobile communication systems, as well as for broadband digital communication on existing copper networks. We address two problems in the design of OFDM receivers. One problem is the unknown OFDM symbol arrival time. Sensitivity to a time offset is higher in multicarrier systems than in single-carrier systems and has been discussed in and. A second problem is the mismatch of the oscillators in the transmitter and receiver. The demodulation of a signal with an offset in the carrier frequency can cause a high bit error rate and may degrade the performance of a symbol synchronizer. b. The OFDM system model The complex data symbols are modulated by means of an inverse discrete Fourier transform (IDFT) on N parallel subcarriers. The resulting OFDM symbol is serially transmitted over a discrete-time channel, whose impulse response we assume is shorter than L samples. At the receiver, the data are retrieved by means of a discrete Fourier transform(DFT) An accepted means of avoiding inter symbol interference (ISI) and preserving orthogonality between subcarriers is to copy the last L samples of the body of the OFDM symbol (N samples long) and append them as a preamble | the cyclic prefix | to form the complete OFDM symbol. The effective length of the OFDM symbol as transmitted is this cyclic prefix plus the body (L+N samples long). The insertion of a cyclic prefix can be shown to result in an equivalent parallel orthogonal channel structure that allows for simple channel estimation and equalization . In spite of the loss of transmission power and bandwidth associated with the cyclic prefix, these properties generally motivate its use. 194

International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 7, July 2015) This allows for high data throughput in a minimum of Radio Frequency (RF) spectrum and supports extreme multipath issues existing in obstructed or partially obstructed non-line-of-sight environments. Similar to conventional OFDM, in CS-OFDM, the modulated symbols are processed block-by-block. Assume that there are N=LM modulated symbols in one block. Different from conventional OFDM, CS-OFDM further divides the length N block into Vector Block (VB), where each VB has size M. Instead of doing IFFT of size N as in conventional OFDM, CS-OFDM does component wise vector IFFT of size over the VBs. The IFFT size is reduced from N to L by M times. This IFFT size reduction also reduces the PAPR.it has the merit of Low PAPR and Cost reduction for transceiver architecture.

Fig:1 OFDM system modal

Without a frequency offset, the frequency response of each sub channel is zero at all other subcarrier frequencies, i.e., the sub channels do not interfere with one other. The effect of a frequency offset is a loss of orthogonality between the tones. The resulting inter carrier interference (ICI) has been investigated. The effective signal-to-noise ratio (SNR) due to both additive noise and ICI is shown to be lower bounded by

CHANNEL

PNPN GENERATOR In channel Estimation sequence is added wit

Each OFDM Subcarriers. (TFT BASED ON A-SP) Fig:2 Sequence

Using TFT we construct the channel parameters and estimate for transmission signal to receiver.

c. Channel Estimation Based On Block-Type Pilot Arrangement In block-type pilot based channel estimation, OFDM channel estimation symbols are transmitted periodically, in which all sub-carriers are used as pilots. If the channel is constant during the block, there will be no channel estimation error since the pilots are sent at all carriers. The estimation can be performed by using either LSE or MMSE [23], [34]. If inter symbol interference is eliminated by the guard interval, we write (3.7) in matrix notation:

IV. RESULT The Complexity Order of A-SP for SARFT-8 channel 1.539269e+01. The Complexity Order of A-SP for IYUVB channel 1.584223e+01. The Complexity Order of SP 1.471766e+01

III. METHOD Compressive Sensing Orthogonal Frequency Division Multiplexing (CS-OFDM), developed by Cisco, is an open standard for broadband wireless Internet services. CSOFDM increases subscriber coverage for high-speed, highreliability Internet, packet local and long distance telephony services and Virtual Private Network (VPN) access. CSOFDM also lowers the cost of provisioning and deploying infrastructure for a wireless network, and utilizes multipath signals to enhance or recreate transmitted signals, dramatically increasing overall system performance and scalability for service providers.

Fig:3 Performance of MSE vs SNR for itu-vb

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International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 7, July 2015)

Fig:7 BEC for 256QAM of SARFT-8

Fig:4 Performance of MSE vs SNR for SARF-8

Fig:5 BEC for 256QAM of itu-vb Fig:8 BEC for 16QAM of SARFT-8

V. CONCLUSION In this paper proposed We have proposed a CS-based CE method for TFT-OFDM in this paper. The MSE performance of this method outperforms the conventional schemes and is close to the CRLB by simultaneously exploiting the time-domain PN sequence and frequencydomain pilots. Simulation results show that the proposed scheme has a good BER performance in both static and mobile scenarios and can well support the 256 QAM, especially when the maximum channel delay spread is fairly close to or even larger than the GI length. Fig:6 BEC for 16QAM of itu-vb

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