Channel Coding and Clipping in OFDM for WiMAX using SDR
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Channel Coding and Clipping in OFDM for WiMAX using SDR

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Recent developments in broadband wireless ...

Recent developments in broadband wireless
technology heightened the need for WiMAX which assures
high-speed data services. Mobile WiMAX is grounded on
orthogonal frequency division multiplexing/orthogonal
frequency division multiplexing Access (OFDM/OFDMA)
technology which is an increasing important technique in
LTE systems. This paper describes the OFDM transceiver
implementation using software-defined radio system (SDR).
A SDR is a radio communication system where elements have
been generally implemented in hardware are rather
implemented by software on a personal computer. In this paper,
the software part is realized using GNU Radio and the
hardware part is implemented using USRP N210. OFDM poses
a problem of a Peak to Average Power Ratio (PAPR) or high
crest factor. To stave off this problem either High Power
Amplifiers (HPAs) with large dynamic range or PAPR reduction
techniques are used. The former scheme raises cost of the
system, while the latter induces redundancy or distortion.
This paper presents a novel architecture (which combines
channel coding and clipping) for the PAPR reduction and
analyzes various parameters which effects the performance
of OFDM such as power spectral density, the crest factor and
BER. Channel coding part is framed of three steps
randomization, Forward Error Correction (FEC) and
interleaving. In clipping, certain threshold limits the
amplitude of time domain samples. Without filtering, clipping
causes out-of-band radiation. The paper analyzes the out band
radiation value (at 2.395 GHz) and PAPR reduction with respect
to clipping threshold value. This scheme is preferred because
of its lower complexity and hence would be cheaper to
implement than conventional reduction techniques.
Experimental results prove that the clipping method reduced
PAPR significantly as the number of clip and filtering level is
increased.

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Channel Coding and Clipping in OFDM for WiMAX using SDR Channel Coding and Clipping in OFDM for WiMAX using SDR Document Transcript

  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 Channel Coding and Clipping in OFDM for WiMAX using SDR B. Siva Kumar Reddy 1 and B. Lakshmi 2 1 Department of Electronics and Communication Engineering, National Institute of Technology Warangal, Andhra Pradesh-506004, India. Email: bsivakumar100@gmail.com 2 Department of Electronics and Communication Engineering, National Institute of Technology Warangal, Andhra Pradesh-506004, India. Email: lkodali93@gmail.com tal Signal Processor (DSP) and Field Programmable Gate Array (FPGA) are used to build up the software radio elements. The fundamental architecture of SDR is shown in Fig. 1. It includes front-end, processing engine and application. The Radio Frequency (RF) front-end module digitizes the radio frequency data from antennas. After the baseband is digitized by front-end, the processing engine changes baseband data and date frames. The application side receives data frames at last. Abstract— Recent developments in broadband wireless technology heightened the need for WiMAX which assures high-speed data services. Mobile WiMAX is grounded on orthogonal frequency division multiplexing/orthogonal frequency division multiplexing Access (OFDM/OFDMA) technology which is an increasing important technique in LTE systems. This paper describes the OFDM transceiver implementation using software-defined radio system (SDR). A SDR is a radio communication system where elements have been generally implemented in hardware are rather implemented by software on a personal computer. In this paper, the software part is realized using GNU Radio and the hardware part is implemented using USRP N210. OFDM poses a problem of a Peak to Average Power Ratio (PAPR) or high crest factor. To stave off this problem either High Power Amplifiers (HPAs) with large dynamic range or PAPR reduction techniques are used. The former scheme raises cost of the system, while the latter induces redundancy or distortion. This paper presents a novel architecture (which combines channel coding and clipping) for the PAPR reduction and analyzes various parameters which effects the performance of OFDM such as power spectral density, the crest factor and BER. Channel coding part is framed of three steps randomization, Forward Error Correction (FEC) and interleaving. In clipping, certain threshold limits the amplitude of time domain samples. Without filtering, clipping causes out-of-band radiation. The paper analyzes the out band radiation value (at 2.395 GHz) and PAPR reduction with respect to clipping threshold value. This scheme is preferred because of its lower complexity and hence would be cheaper to implement than conventional reduction techniques. Experimental results prove that the clipping method reduced PAPR significantly as the number of clip and filtering level is increased. Figure 1: Fundamental architecture of Software Defined Radio (SDR) In recent years, there has been an increasing interest in WiMAX (Worldwide Interoperability for Microwave Access) [2] technology that provides performance similar to Wi-Fi (IEEE 802.11) networks with the coverage and QoS (quality of service) of mobile networks. WiMAX can provide broadband wireless access (BWA) up to 50 km for fixed stations (called as Fixed WiMAX (IEEE 802.16d)), and 5-15 km for mobile stations (called as Mobile WiMAX (IEEE 802.16e-2005)). This BWA technology is based on Orthogonal Frequency Division Multiplex (OFDM) technology [3] and considers the radio frequency range up to 2-11 GHz and 1066 GHz. This provides strong performance in multipath and non-line-of-sight (NLOS) environments. Mobile WiMAX extends the OFDM PHY layer to support efficient multipleaccess (known as scalable OFDMA (Orthogonal Frequency Division Multiple Access)) [3]. Scalability is carried out by altering the FFT size from 128 to 512, 1024, and 2048 to support channel bandwidths of 1.25 MHz, 5 MHz, 10 MHz and 20 MHz respectively. In a single carrier communication system, to avoid intersymbol interference (ISI), the symbol period must be maintained greater than the delay time. Having long symbol periods means low data rate and communication inefficiency because data rate is inversely proportional to symbol period. Index Terms—BER, Clipping, Coding, OFDM, OFDMA, SDR, WIMAX. I. INTRODUCTION One of the most significant current discussions in the communications is Software Defined Radio (SDR) [1]. SDR is pertained to as a digitally programmable platform that can be programmed to realize multiple wireless standards (GSM, WCDMA, Wi-Fi, WiMAX, etc). SDR has potential to realize the structure of the device with high mobility, reconfigurability and flexibility. In SDR, General-Purpose Processor (GPP), Digi © 2013 ACEEE DOI: 01.IJRTET.9.1.526 66
  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 OFDM is a multicarrier multiplexing digital communication scheme to solve both issues, where data is transmitted through several parallel frequency subchannels at a lower rate. OFDM has become one of the most important building block in the area of modern broadband wireless networks for the following reasons: i) tolerance to multipath propagation and frequency selective fading ii) high spectral efficiency and iii) impulse noise rejection. However, a major problem with this kind of application is high Peak to Average Power ratio (PAPR). To reduce PAPR ratio, Channel coding [4] and clipping [5] have been considered. Recently, researchers have shown an increased interest in Channel coding [4] which plays a vital role in the performance of OFDM system. The role of channel coding in conjunctive with frequency and time interleaving is to furnish a link between bits transmitted on separated carriers of the signal spectrum, in such a way that the data expressed by faded carriers can be rebuilt in the receiver. Clipping is a nonlinear process [5]. Thus, it must be executed in a controlled manner to prevent any signal distortion. The results of clipping are in-band distortion and out-of-hand distortion. In-band distortion or the degradation in the wanted signal strength happens since clipping modifies the signal artificially. Clipping an over sampled signal induces lesser effect of distortion to the signal within the original band. This is because oversampling shortens the effect of clipping noise in the required signal by spreading them in a wider bandwidth. By acting clipping on an oversampled signals also resulted in a lesser peak regrowth. The out-of-band radiation can be reduced by performing frequency domain filtering [6]. This filtering results in a lesser peak regrowth and also completely decimates the out-of-band radiation thus allowing the original unclipped signal to be retrieved. This paper will focus on the description of the proposed novel architecture is shown in Fig. 2, which combines Channel coding and Clipping techniques for PAPR reduction for WiMAX. software development toolkit that offers signal processing blocks to implement Software Defined Radios (SDR). The USRP [8] will digitize the incoming data from the air and passing it to the GNU Radio through the USB or Ethernet interface. GNU Radio will further process (demodulating and filtering) the signal until the signal is translated to a stream of data or packet. In GNU Radio, all signal processing is done through flow graphs, which consists of blocks. A block does transforming, decoding, filtering, adding signals, hardware access or many others. Data passes between blocks in various formats, complex or real integers, floats or basically any kind of data type user can define. Every flow graph demands at least one sink and source. In GNU Radio, signal processing blocks are written in C++ and they are connected by using Python. SWIG (Simplified Wrapper and Interface Generator) is used as an interface compiler between C++ and Python language [7]. GRC is a signal flow chart generator tool in GNU Radio. Signal flow chart is built through the GUI tool and also follow-up the source code to function this flow. Each block has a relative parameter XML file, GRC will automatically identify the block’s definition when it is executing. In other words, GRC has the automatic recognition error ability. Figure 2: Novel Architecture composes of channel coding and clipping IV. OFDM TRNSEIVER MODEL The rest of the paper is structured as follows. Section II and III introduce the software and hardware platform realizations for for SDR respectively. In Section IV, the system model is presented by focussing the attention on OFDM PHY layer used in WiMAX standords. Section V examine the effect of clipping and channel coding on PAPR reduction. In Section VI, numerical results evaluating impacts of various parameters on PAPR, in-band and out-of band distortion, BER. Some literature survey also has done here. Finally, the paper has concluded in Section VI. OFDM is one of the most widely used technique in LTE (Long Term Evaluation) system. In OFDM, spectrally coincided sub-carriers can be used and since they are orthogonal, they do not interfere with each other. This causes OFDM a bandwidth efficient modulation scheme [3]. OFDM is a technique as shown in Fig. 3, where the input data is converted to parallel bits and mapped according to predefined standard. Inverse Fast Fourier Transform (IFFT) is a part to convert signal from frequency domain to time domain. After IFFT the parallel data is again converted to serial data. Before it gets converted from digital to analog data, Cyclic prefix is also added. The input data should be prepared preserving specific standard. In the IFFT mapping, the total subcarriers in frequency domain are converted to time domain. In order to preserve the orthogonally of OFDM signal, preamble bits are II. GNU RADIO COMPANION Recent developments in the field of SDR have led to a renewed interest in GNU Radio [7], which is a free and opensource 67 © 2013 ACEEE DOI: 01.IJRTET.9.1.526 III. UNIVERSAL SOFTWARE RADIO PERIPHERAL USRP is a flexible hardware platform for the development of SDRs [8]. Any USRP board consists of a motherboard and daughterboard. In this paper, a network series USRP N210 is suggested, because of its high-bandwidth, high-dynamic range processing capability. This board includes a Xilinx Spartan 3A-DSP 3400 FPGA, 100 MS/s dual ADC (Analog to Digital Converter), 400 MS/s dual DAC (Digital to Analog Converter) and Gigabit Ethernet connectivity to stream data to and from host processors. The USRP N210 can stream up to 50 MS/s to and from host applications. The FPGA (Field Programmable Gate Array) also offers the potential to process up to 100 MS/s in both transmit and receive directions. The USRP N210 operates from DC to 6 GHz and an expansion port allows using in MIMO configuration.
  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 added. Also the cyclic prefix enables synchronization as the bits are used to detect the beginning and end of each frame and it appends the OFDM symbols one after another. At the receiver side, do reverse processes to demodulate the received sequences of data bits. (3) E[|Sn|2] is average power of transmitted symbol. Oversampling is necessary to get right values of PAPR and it can be performed by plodding IFFT source data with zeros. The time domain signal is normally oversampled by factor of four or greater. The channel encoder includes three stages: data scrambling, convolution coding, and data interleaving [4]. The data scrambler uses generator polynomial S(x) = x7 + x4 + 1 with “all ones” (1111111) as the initial state. The 127-bit binary sequence is employed repeatedly to be XORed with the data bit sequence. The output of the scrambler is shipped to a rate 1/2, K = 7 convolutional encoder with generator polynomials g0 = 1338 (1011011) and g1 = 1718 (1111001) the encoded data bits are then handed to an interleaver with the block size representing to the number of bits in a single OFDM symbol. The interleaver is defined by a two-step permutation. The first permutation insures that the adjacent coded bits are mapped onto nonadjacent subcarriers, while the second permutation insures that the adjacent coded bits are mapped alternately onto less and more significant bits of the constellation and, thereby, long runs of low reliability (LSB) bits are avoided. If the code rate is k/n, then k bits per second input to the convolutional encoder and the output is n bits per second. QAM64 data symbols are passed through an inverse fast Fourier transform (IFFT) module to realize the OFDM modulation. If the digital OFDM signals are clipped instantly, the resulting clipping noise will be fall in-band and may not be reduced by filtering. Data symbols are sent through an inverse fast Fourier transform (IFFT) module to realize the OFDM modulation. In addition, the complex-valued baseband OFDM signal is regulated up to a carrier frequency equal to 1/4 of the sampling frequency to descend the implementation complexity. Then, the real-valued bandpass samples x, are clipped at an amplitude A as follows [6]: Figure 3: OFDM Transciever block diagram OFDM symbol consists of N subcarriers which have constant spacing Δf. Bandwidth of the signal is B= Δf.N and symbol time T=1/ Δf. This conducts to sum of N sinsoids in the time domain, that have exactly an integer number of cycles in the intervel T. Each subcarrier is regulated by complex value Xm,n , where m refers symbol index and n subcarrier index. M-th OFDM symbol can be defined as [5]: (1) where gn(t) = exp(j2πnΔft), for 0 d” t d”T and gn(t) = 0, for other t. Time domain signal is defined as sum of symbols [5]: (2) The complex value Xm,n based on partial modulation (Usually M-PSK or M-QAM is used). (4) V. CHANNEL CODING AND CLIPPING The novel architecture combines the use of channel coding and Clipping method as shown in Fig. 2. These channel codes improve the bit error rate performance by appending redundant bits in the conveyed bit stream that are used by the receiver to correct errors introduced by the channel [4]. OFDM contains of lots of independent modulated subcarriers (without considering coding). That causes to problem with peak to average power ratio. If N subcarriers are in phase with same symbols regulated on all subcarriers, the peak power is N times average power. For sampled signal, PAPR can be defined [9]: © 2013 ACEEE DOI: 01.IJRTET.9.1.526 In the following discussion, we will use a normalized clipping level, which we call the clipping ratio (CR = A/α, where α is the rms level of the OFDM signal). It is easy to show that, for an OFDM signal with N subchannels, α = baseband signal α = N for a N / 2 and for a bandpass signal. In the following discussion, we will use a normalized clipping level, which we call the clipping ratio (CR = A/α, where α is the rms level of the OFDM signal). A CR of 1.4 denotes that the clipping level is about 3 dB higher than the rms level. Filtering after clipping is required to reduce the out-of-band 68
  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 clipping noise. Filtering after clipping is required to reduce the out-of-band clipping noise [5]. TABLE I. SNR I N D B WITH AND WITHOUT ENCODER FOR QPSK SNR (in dB) AWGN VI. EXPERIMENTAL RESULTS SUI-1 SUI-2 With Encoder 5 5 5 Without Encoder WiMAX confirms a various modulation and Forward Error Correction (FEC) coding schemes and grants the scheme per a user based on channel conditions accordingly. This causes to Adaptive modulation and coding [10] which is an effective mechanism to maximize throughput, fairness and BER performance in a continuously time-varying channel. Figs 4, 5 and 6 present the effectiveness of encoding on AWGN, SUI-1 and SUI-2 channel models. Simulation results show the advantage of convolutional coding and for the QPSK digital modulation scheme [11]. The Table 1 depicts the BER under QPSK modulation technique over AWGN, SUI-1 and SUI-2 fading channel with encoder for a SNR value of 5dB but in the case of without encoder is found SNR value of 9dB, 10dB and 8dB respectively [11]. As shown in Fig. 7, the BER performance has been improved for coded signal (due to channel coding) than uncoded signal [12]. 9 10 8 Figure. 7. BER performance for coded and uncoded signal [12] One of the simple and effective PAPR reduction techniques is clipping, which cancels the signal components that outperform some unchanging amplitude called clip level [5]. However, clipping affords distortion power, which called clipping noise, and elaborates the transmitted signal spectrum, which causes interfering. The technique of iterative clipping and filtering reduces the PAPR without spectrum expansion. However, the iterative signal carries long time and it will gain the computational complexity of an OFDM transmitter. But without performing interpolation before clipping causes it out-of-band. To avoid out-of band, signal should be clipped after interpolation. However, this induces significant peak re-growth. So, it can employ iterative clipping and frequency domain filtering to avoid peak regrowth. Fig. 8 depicts the power spectral density (PSD) of the Mobile WiMAX MC-OFDMA-256-QAM clipped signal. The in-band signal attenuation as well as the out-of band induced by clipping is apparent. In Normal OFDMA the outof band noise emission power is only 30 dB lower than the signal power. But With hard clipping ratio CR= 0.5 and after applying the filtering, it is observed that the spectral sidelobes after filtering are at least 25 dB lower than the signal mainlobe [13]. Fig. 9 shows the effect of clipping level on PAPR reduction. As clipping level increases, the PAPR reduction increases [14]. The discussed above two techniques ([11], [12] and [13]) are combined to get both the advantages in terms of BER and PAPR reduction in novel approach. The experimental setup has a USRP N210 platform and a General Purpose Processor (laptop) is shown in Fig. 10. The required OFDM parameters for WiMAX specifications have been shown in Table 2. The flow graph of novel architecture is Source—>Scrambling— >Convolutional Coding—>Interleaving—>OFDM block— >Rail Clipping—>Multiply Const—>Channel Model—>Sink, shown in Fig. 11. OFDM modulator modulates an OFDM Figure 4. BER performance under AWGN channel for QPSK [11] Figure 5. BER performance under SUI 1 channel for QPSK Figure 6. BER performance under SUI 2 channel for QPSK © 2013 ACEEE DOI: 01.IJRTET.9.1.526 69
  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 Figure 10. Experimental setup for the development of Software Defined Radio (SDR) TABLE II. EXPERIMENTAL PARAMETERS DEFINED Parameters FFT size (NFFT) Occupied Tones Sampling rate Center Frequency Figure 8. PSD of Normal-OFDMA and MC-OFDMA for WiMAX2 5 6QAM Convolutional Code Cyclic Prefix length Values 1024 840 10.66667M 2.48 GHz 1/2 184 Useful symbol duration 91.43 µs Carrier spacing (1/Tu) 10.94 KHz Guard time (Tg=(1/4)* Tu) OFDM symbol duration Mapping Schemes From the experimental results, it can be observed that OFDM signal is has higher PAPR (Shown in Figs. 12 and 13) and after applying the proposed method, PAPR has been reduced significantly (Shown in Figs. 14 and 15). The amplitude clipping is simple method with minimal computing complexity. The clipping is followed by filtering to reduce out of band power. Figs 16, 17, 18 and 19 show the average 64QAM-OFDM signals with Clipping Thresholds (CT) 0.2, 0.6, 3 and 5 respectively. It can be concluded that the difference between out-of band and in-band radiation has been increased as clipping level increased. So, the selection of clipping threshold value is carefully taken. The clipping is the easiest technique to reduce the power by setting a maximum level for the transmitted signal [5]. Though, this technique has several disadvantages: i) The performance of BER could be affected negatively due to the in-band distortion caused by the clipping. ii) Also out-of-band radiation usually appears with clipping technique that could disturb the adjacent channels. However, we can use filtering operation to decrease the appearance of the out-of-band radiation but the signal may exceed the maximum level of the clipping operation. On the other hand, the BER performance is worsen badly at it gets better when the CR get higher as shown in Fig. 20. It is clear that the performance of the BER get worse as the CR gets lower [15]. Figure 9. Clipping level effect on PAPR in OFDM [14] stream based on the configurability such as FFT length, occupied tones, and cyclic prefix length. This block creates OFDM symbols using specified modulation scheme (here in 64-QAM) shown in Fig. 11. The USRP N210 is connected as source and captured a signal at 2.46 GHz from the environment using VERT 2450 antenna and the processing has done using XCVR 2450 daughterboard in USRP. WiMAX PHY layer processing has done in GNU Radio [7], shown in Fig. 11. © 2013 ACEEE DOI: 01.IJRTET.9.1.526 11.43 µs 102.86 µs BPSK, 4QAM, 16QAM and 256QAM 70
  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 Figure 11. GNU Schematic for the implementation of Channel coding and clipping for mobile WiMAX TABLE III. OBTAINED RESULTS FOR MOBILE WIMAX WITH C HANNEL CODING AND C LIPPING USING SDR Clipping Threshold Value (CT) 5 3 2 1 0.8 0.6 0.4 0.2 Scope Sink Peak to peak Amp (in counts) -900 to +900 -850 to +850 -800 to +800 -500 to +500 -400 to +400 -300 to +300 -200 to +200 -100 to +100 Average Amp (in counts) -200 to +200 -200 to +200 -200 to +200 -200 to +200 -200 to +200 -200 to +200 -180 to +180 -100 to +100 FFT sink Peak to peak Amp Average Amp (in db) (in db) 4 to 32 16 to 28 5 to 32 19 to 26 5 to 31 18 to 26 5 to 29 18 to 24 10 to 28 16 to 23 5 to 24 16 to 23 5 to 21 15 to 20 -5 to 15 8 to 15 Table 3 shows (Where β = Out of band radiation at 2.395GHz, γ = Difference between out-of- band and in band radiation), as clipping threshold value (CT) decreases, out of band value is increased and the difference between in band radiation to out of band radiation is decreased. So it can be concluded that there is a tradeoff between clipping threshold and out of band radiation. In FFT sink peak to peak amplitude value and average amplitude values are increased as CT value increases. Out of band radiation value has been controlled by filtering [5]. Fig. 21 shows, particularly fast way of calculating auto-correlations [16]. Table 4 shows the comparison of various PAPR reduction techniques, each © 2013 ACEEE DOI: 01.IJRTET.9.1.526 PAPR β (in db) γ (in db) 20.25 18.06 16 6.25 4 2.25 1.11 1 -13 -10 -5 2 3 5 6 8 37 35 28 18 14 10 5 2 technique has its own advantages and disadvantages. A proper PAPR reduction technique selection is based on the application. Through our SDR platform consists of GNU Radio software [7] and USRP hardware device [8], we can dynamically adjust the central frequency of the digital data communication service and choose the unlicensed band as long as we want. Because GNU Radio provides high instantaneous and accurate spectrum sensing ability, we can efficiently utilize SDR to achieve digital data communication under the current limited spectrum resource. Due to simple complexity, clipping technique is preferred more. 71
  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 Figure 12. Without clipping, 64QAM-OFDM signal on Scope sink Figure 15. Peak to Peak OFDM signal at CT=0.8 on FFT sink Figure 13. Without clipping, 64QAM-OFDM signal on FFT sink Figure 16. Average OFDM signal at CT=0.2 for 64-QAM mod scheme Figure 14. Clipped signal at CT=0.6 on scope plot Figure 17. Average OFDM signal at CT=0.6 for 64-QAM mod scheme © 2013 ACEEE DOI: 01.IJRTET.9.1. 526 72
  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 Figure 21. Fast Autocorrelation for OFDM at CT=5 TABLE IV. C OMPARISON OF VARIOUS PAPR REDUCTION TECHNIQUES Reduction Technique Parameters Operation required at Transmitter (TX)/Receive r (RX) Figure 18. Average OFDM signal at CT=3 for 64-QAM mod scheme Decrease distortion Power Raise NO No Defeat Data rate No Yes No Yes Block Coding Yes No Yes Partial Transmit Sequence (PTS) Yes No Yes Interleavin g Yes No Yes Tone Reservation (TR) Tone Injection (TI) Yes Yes Yes Yes Yes No Clipping and Filtering Selective Mapping (SLM) Figure 19. Average OFDM signal at CT=5 for 64-QAM mod scheme TX: Clipping RX: None TX:M times IFFTs operation RX: Side information extraction, inverse SLM TX: Coding or table searching RX: Decoding or table searching TX: V times IFFTs operation RX: Side information extraction, inverse PTS TX: D times IFFTs operation, D1 times interleaving RX: Side information extraction, deinterleaving CONCLUSIONS Though, there is a major drawback for using OFDM, which is the high PAPR, recently OFDM became a compulsory in all LTE systems for higher data rates. This problem can be Figure 20. BER for clipped and unclipped signal [15] © 2013 ACEEE DOI: 01.IJRTET.9.1.526 73
  • Long Paper Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013 reduced by using channel coding and clipping as a power reduction technique. We proposed and implemented a reconfigurable SDR platform by combing USRP N210 and GNU Radio. The selected technique allows for us with a good range in performance to reduce PAPR problem. The paper concludes that as SNR increases, BER will decreases. And higher order PSK requires a larger SNR to minimize BER. QAM constitutes of amplitude as well as phase, but QPSK only have phase, so QAM is widely used instead QPSK . The obtained results prove that PAPR reduces more at lower CR and there is a tradeoff between the clipping threshold value (CT) and out-of-band radiation. This out-of-band radiation can be controlled by frequency domain filtering. The results show how clipping and filtering affect the BER of an OFDM signal and it is clear that the BER is increased after this process. Filter is used to decrease the distortion that result from clipping. This research will extend in directions Firstly, PAPR reduction concepts will be expanded for distortion less transmission and identifying the best alternatives in terms of performance increase Secondly, PAPR reduction technique will be develop for low data rate loss and efficient use of channel. [5] Albdran, Saleh and Alshammari, Ahmed and Matin, Mohammad, “Clipping and Filtering Technique for reducing PAPR in OFDM”, IOSR Journal of Engineering (IOSRJEN), vol2, pp 91-97, 2012. [6] Li, Xiaodong and Cimini Jr, Leonard J, “Effects of clipping and filtering on the performance of OFDM,” Communications Letters, IEEE, pages 131—133, vol 2, 1998. [7] GNU Radio Trac, http://gnuradio.org/trac/wiki. [8] Matt Ettus, Universal software radio peripheral. http:// www.ettus.com. [9] J.Mitola, “Analysis and comparison of clipping techniques for OFDM Peak-to-Average Power Ratio reduction,” Digital Signal Processing, 2009 16th International Conference on, pages 1— 6, 2009. [10] Reddy, B Siva Kumar and Lakshmi, B,” Adaptive Modulation and Coding in COFDM for WiMAX Using LMS Channel Estimator,”2013. [11] Sekar, Venkatesh and Palanisamy, V and Baskaran, K,” Performance Analysis of IEEE 802.16 d using Forward Error Correction,” Journal of Computer Science,vol 7, num 3, pp 431—433, 2011. [12] Kaiser, Stefan,” OFDM code-division multiplexing in fading channels,” Communications, IEEE Transactions on, vol 50, num 8, pp 1266—1273, 2002. [13] Al-kebsi, Ibrahim Ismail and Ismail, Mahamod and Jumari, Kasmiran and Rahman, TA,” Mobile WiMaX performance improvement using a novel algorithm with a new form of adaptive modulation,” IJCSNS International Journal of Computer Science and Network Security, vol 9, num 2, 76— 82, 2009. [14] Rana, MM and Naseer, A and Hussain, S and Siddiq, Shahid and Ali, Aasim and Malik,” Clipping Based PAPR Reduction Method for LTE OFDMA Systems,” IEEE IJECS-IJENS,vol 10, num 05, 2000. [15] Albdran, Saleh and Alshammari, Ahmed and Matin, Mohammad,” Clipping and Filtering Technique for reducing PAPR in OFDM,”2012. [16] Ren, Yu, “Analysis and Implementation of Reinforcement Learning on a GNU Radio Cognitive Radio Platform,” IEEE National Telesystems Conference, 2010. REFERENCES [1] J.Mitola, “Software radios-survey, critical evaluation and future directions,” IEEE National Telesystems Conference, pages 13/15-13/23, 19-20 May 1992. [2] Bo Li; Yang Qin; Chor Ping Low; Choon Lim Gwee; , “A Surveyon Mobile WiMAX [Wireless Broadband Access],” Communications Magazine, IEEE , vol.45, no.12, pp.70-75, December 2007. [3] Chen, H.M. and Chen, W.C. and Chung, C.D. “Spectrally precoded OFDM and OFDMA with cyclic pre x and unconstrained guard ratios,” Wireless Communications, IEEE Transactions on, vol 10, no. 5, pp. 416-1427, 2011. [4] Sonagi, Rupa and Chaudhary, Shubhangi and Patil, AJ “Performance Analysis of an OFDM system using Channel Coding Techniques,” IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET 2012)}, page 7, 2012. © 2013 ACEEE DOI: 01.IJRTET.9.1.526 74