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International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 4



  An Improved Self Cancellation Scheme to Reduce Non-Linearity in OFDM
                                 Spectrum
                                   Kunal mann1, Rakesh kumar2, Poonam3


Abstract-- As the wireless communication system has                   Application, and/or network”. The concept of Cognitive
evolved tremendously, leading to the need for high                    emerges from Software defined Radios as Cognitive radio is
performance and much higher capacity for the multiuser                a “step ahead” of SDR technology. Cognitive radio can be
communication systems but within the constraints of limited           summarized through following definitions:
spectrum and limited bandwidth. The main function of                  Definition 1: A radio or system that senses its operational
OFDM is to convert a frequency selective channel into a               electromagnetic environment and can dynamically and
collection of frequency- Flat sub channels with partially             autonomously adjust its radio operating parameters to
overlapping spectra. The differentiating factor of this               modify system operation, such as maximize throughput,
scheme is the orthogonality provided to the subcarriers that          mitigate interference, facilitate interoperability, access
provided synchronisation and helps in avoiding ISI .An                secondary markets.
OFDM signal consists of a number of closely spaced                    Definition 2: A cognitive radio is an adaptive, multi-
modulated carriers.                                                   dimensionally aware, autonomous radio system that learns
                                                                      from its experiences to reason, plan, and decide future
I. Introduction                                                       actions to meet user needs.
Cognitive radio is:” A radio which is capable of sensing its
operational environment and can adjust its parameters                 Depending upon the type of parameters taken into
according to the environment dynamically and behave                   consideration while transmission or reception, there can be
accordingly.”The most significant objectives for which                various types of cognitive radios:
cognitive radio networks were introduced are:                        Full Cognitive Radio: In this CR, each and every parameter
                                                                      which is observable by a wireless network is taken into
i.     To utilise the spectrum efficiently.                           account.
 ii.    To make highly reliable communication networks
                                                                     Spectrum Sensing Cognitive Radio: In this CR, only
        available wherever and whenever needed
                                                                      Radio Frequency spectrum is taken into account.
As it is known that there is rapid deployment of wireless            Licensed Band Cognitive Radio: In this, along with
devices, as a result the demand of wireless radio spectrum is         unlicensed bands, CR can use bands assigned to licensed
also increasing rapidly. But fixed spectrum assignment                users.
policy is proving a bottleneck in efficient utilisation of           Unlicensed Band Cognitive Radio: In this, CR can use
spectrum. Cognitive radio networks helps in eliminating               only unlicensed bands of radio frequency spectrum.
inefficient usage of limited spectrum by using various
dynamic spectrum access techniques, through which,                    III Problem Defination
unlicensed users called Secondary users, are allowed to               The main aim of this paper is to optimize the Parallel
temporarily use the unused portion of licensed spectrum.              Cooperative sensing technique and to simulate efficient
The licensed users are called Primary users. In cognitive             results for better spectrum utilization .For this scheme a
radio networks, secondary users dynamically access the                spectrum would be generated to analyze the effect of
spectrum in opportunistic fashion, without interfering with           various parameters like noise, throughput etc on the overall
the primary users.                                                    efficiency. A parallel scheme would be used for carrying out
                                                                      the signal transmission.
Ii Literature Survey                                                  Cognitive Radio System
Technically, Cognitive Radio is a kind of two way radio that
can automatically change its transmission or reception
parameters in such a way that the entire wireless
communication network communicates efficiently, while
avoiding interference between licensed or unlicensed users.
The definition of Cognitive radio can be “a cognitive radio
is a software radio whose control processes leverage
situational knowledge and intelligent processing to work for
achieving the goals related to the needs of the user,                               Figure Cognitive Radio System

Issn 2250-3005(online)                                          August| 2012                                   Page 1084
International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 4


                                                                                                                                                              th
The RF architecture of a CR system consists of a “sensing
                                                                             signals transmitted on sub-carriers other than the k sub-
antenna” to continuously monitor the wireless channels and
                                                                             carrier. The complex coefficients are given by
to look for unused frequency bands (holes) and a
“reconfigurable transmit/receive antenna” to perform the
required communication within those unused frequency
channels. “Spectrum Sensing” and “Spectrum Decision”
modules are required to determine the unused frequency
bands and assign the appropriate frequency to the secondary
users. Based on the output of these modules the “Switch                            To analyze the effect of ICI on the received signal, we
Controller” will communicate with the switch activation                          consider a system with N=16 carriers. The frequency offset
circuit in order to change the physical/electrical structure of                   values used are 0.2 and 0.4, and l is taken as 0, that is, we
the reconfigurable antenna.                                                        are analyzing the signal received at the sub-carrier with
                                                                                 index 0. The complex ICI coefficients S(l-k) are plotted for
Analysis of Inter-Carrier Interference                                                         all sub-carrier indices in figure.
The main disadvantage of OFDM, however, is its                                                        1
                                                                                                                                                = 0.2
susceptibility to small differences in frequency at the                                              0.9
                                                                                                                                                = 0.4

transmitter and receiver, normally referred to as frequency                                          0.8


offset. This frequency offset can be caused by Doppler shift                                         0.7


due to relative motion between the transmitter and receiver,                                         0.6




                                                                                          |S(l-k)|
                                                                                                     0.5
or by differences between the frequencies of the local
                                                                                                     0.4
oscillators at the transmitter and receiver. In this project, the
                                                                                                     0.3
frequency offset is modeled as a multiplicative factor                                               0.2
introduced in the channel, as shown in Figure: shows.                                                0.1

                                                                                                      0
                                                                                                           0   5                        10               15
                                                                                                                   Subcarrier Index k


                                                                                                  Figure ICI Coefficients for N=16
                                                                             Carriers
                                                                             This figure shows that for a larger ε, the weight of the
                                                                             desired signal component, S(0), decreases, while the weights
                                                                             of the ICI components increases. The authors also notice
            Figure : Frequency Offset Model                                  that the adjacent carrier has the maximum contribution to
The received signal is given by,                                             the ICI. This fact is used in the ICI self-cancellation
                                     j 2n                                  technique described.
                y ( n)  x ( n) e       N
                                                w(n)                        IV CONCLUSION
Where ε is the normalized frequency offset, and is given by                  In this project, the performance of OFDM systems in the
∆fNTs. ∆f is the frequency difference between the                            presence of frequency offset between the transmitter and the
transmitted and received carrier frequencies and Ts is the                   receiver has been studied in terms of the Carrier-to-
sub-carrier symbol period. w(n) is the AWGN introduced in                    Interference ratio (CIR) and the bit error rate (BER)
the channel. The effect of this frequency offset on the                      performance. Inter-carrier interference (ICI), which results
received symbol stream can be understood by considering                      from the frequency offset, degrades the performance of the
                                        th                                   OFDM system.
the received symbol Y(k) on the k sub-carrier.                               One method is explored in this project for mitigation of the
                                   N 1

                                   X (l )S (l  k )  n
                                                                             ICI i.e. ICI self-cancellation (SC). By using this method the
      Y (k )  X (k ) S (0)                                 k               BER is improved in comparison to simple OFDM system.
                                l  0 ,l  k



      k  0,1..........N  1

Where N is the total number of sub-carriers, X(k) is the
transmitted symbol (M-ary phase-shift keying (M-PSK), for
                   th
example) for the k sub-carrier, is the FFT of w(n), and S(l-
k) are the complex coefficients for the ICI components in
                                                                             .
the received signal. The ICI components are the interfering

Issn 2250-3005(online)                                                August| 2012                                                           Page 1085
International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 4



 References
 [1]    www.mprg.org/people/gametheory/files/chapter%201.
        pdf.
 [2]    Beibei Wang and K. J. Ray Liu , “Advances in
        Cognitive Radio Networks: A Survey”, IEEE
        JOURNAL OF SELECTED TOPICS IN SIGNAL
        PROCESSING, VOL. 5, NO. 1, FEBRUARY 2011.
 [3]    http://en.wikipedia.org/wiki/Cognitive_radio.
 [4]    Federal Communications Commission, “Notice of
        proposed rule making and order: Facilitating
        opportunities for flexible, efficient, and reliable
        spectrum use employing cognitive radio technologies,”
        ET Docket No. 03-108, Feb. 2005.
 [5]    www.wirelessinnovation.org/assets/documents/tut-
        cognitive_radio.pdf.
 [6]    Sugata Sanyal , Rohit Bhadauria and Chittabrata
        Ghosh, “Secure Communication in Cognitive
        RadioNetworks”, 2009 International Conference on
        Computers and Devices for Communication.
 [7]    Luca Bixio, Marina Ottonello, Mirco Raffetto, Carlo
        S. Regazzoni ,“ A comparison between stand-alone
        and distributed architectures for spectrum hole
        detection”,IEEE,2010.
 [8]    Q. Zhao and B. M. Sadler, “A survey of dynamic
        spectrum access,”IEEE Sig. Proc. Mag., vol. 24, pp.
        79–89, May 2007.
 [9]    S. Srinivasa and S. A. Jafar, “The throughput potential
        of cognitive radio: a theoretical perspective,” IEEE
        Comm. Mag., vol. 45, pp. 73–79, May 2007.
 [10]   Citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.9
        1.567.
 [11]   Rajni Dubey and Sanjeev Sharma ,“ Distributed
        Shared Spectrum Techniques for Cognitive Wireless
        Radio Networks”, 2010 International Conference on
        Computational Intelligence and Communication
        Networks.
 [12]   Ines AISSA, Mounir FRIKHA and Sami TABBANE
        ,“ Dynamic Spectrum Hole Management in Cognitive
        Radio”,IEEE,2011.




Issn 2250-3005(online)                                            August| 2012                                Page 1086

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Reducing Non-Linearity in OFDM Spectrum Using an Improved Self Cancellation Scheme

  • 1. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 4 An Improved Self Cancellation Scheme to Reduce Non-Linearity in OFDM Spectrum Kunal mann1, Rakesh kumar2, Poonam3 Abstract-- As the wireless communication system has Application, and/or network”. The concept of Cognitive evolved tremendously, leading to the need for high emerges from Software defined Radios as Cognitive radio is performance and much higher capacity for the multiuser a “step ahead” of SDR technology. Cognitive radio can be communication systems but within the constraints of limited summarized through following definitions: spectrum and limited bandwidth. The main function of Definition 1: A radio or system that senses its operational OFDM is to convert a frequency selective channel into a electromagnetic environment and can dynamically and collection of frequency- Flat sub channels with partially autonomously adjust its radio operating parameters to overlapping spectra. The differentiating factor of this modify system operation, such as maximize throughput, scheme is the orthogonality provided to the subcarriers that mitigate interference, facilitate interoperability, access provided synchronisation and helps in avoiding ISI .An secondary markets. OFDM signal consists of a number of closely spaced Definition 2: A cognitive radio is an adaptive, multi- modulated carriers. dimensionally aware, autonomous radio system that learns from its experiences to reason, plan, and decide future I. Introduction actions to meet user needs. Cognitive radio is:” A radio which is capable of sensing its operational environment and can adjust its parameters Depending upon the type of parameters taken into according to the environment dynamically and behave consideration while transmission or reception, there can be accordingly.”The most significant objectives for which various types of cognitive radios: cognitive radio networks were introduced are:  Full Cognitive Radio: In this CR, each and every parameter which is observable by a wireless network is taken into i. To utilise the spectrum efficiently. account. ii. To make highly reliable communication networks  Spectrum Sensing Cognitive Radio: In this CR, only available wherever and whenever needed Radio Frequency spectrum is taken into account. As it is known that there is rapid deployment of wireless  Licensed Band Cognitive Radio: In this, along with devices, as a result the demand of wireless radio spectrum is unlicensed bands, CR can use bands assigned to licensed also increasing rapidly. But fixed spectrum assignment users. policy is proving a bottleneck in efficient utilisation of  Unlicensed Band Cognitive Radio: In this, CR can use spectrum. Cognitive radio networks helps in eliminating only unlicensed bands of radio frequency spectrum. inefficient usage of limited spectrum by using various dynamic spectrum access techniques, through which, III Problem Defination unlicensed users called Secondary users, are allowed to The main aim of this paper is to optimize the Parallel temporarily use the unused portion of licensed spectrum. Cooperative sensing technique and to simulate efficient The licensed users are called Primary users. In cognitive results for better spectrum utilization .For this scheme a radio networks, secondary users dynamically access the spectrum would be generated to analyze the effect of spectrum in opportunistic fashion, without interfering with various parameters like noise, throughput etc on the overall the primary users. efficiency. A parallel scheme would be used for carrying out the signal transmission. Ii Literature Survey Cognitive Radio System Technically, Cognitive Radio is a kind of two way radio that can automatically change its transmission or reception parameters in such a way that the entire wireless communication network communicates efficiently, while avoiding interference between licensed or unlicensed users. The definition of Cognitive radio can be “a cognitive radio is a software radio whose control processes leverage situational knowledge and intelligent processing to work for achieving the goals related to the needs of the user, Figure Cognitive Radio System Issn 2250-3005(online) August| 2012 Page 1084
  • 2. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 4 th The RF architecture of a CR system consists of a “sensing signals transmitted on sub-carriers other than the k sub- antenna” to continuously monitor the wireless channels and carrier. The complex coefficients are given by to look for unused frequency bands (holes) and a “reconfigurable transmit/receive antenna” to perform the required communication within those unused frequency channels. “Spectrum Sensing” and “Spectrum Decision” modules are required to determine the unused frequency bands and assign the appropriate frequency to the secondary users. Based on the output of these modules the “Switch To analyze the effect of ICI on the received signal, we Controller” will communicate with the switch activation consider a system with N=16 carriers. The frequency offset circuit in order to change the physical/electrical structure of values used are 0.2 and 0.4, and l is taken as 0, that is, we the reconfigurable antenna. are analyzing the signal received at the sub-carrier with index 0. The complex ICI coefficients S(l-k) are plotted for Analysis of Inter-Carrier Interference all sub-carrier indices in figure. The main disadvantage of OFDM, however, is its 1  = 0.2 susceptibility to small differences in frequency at the 0.9  = 0.4 transmitter and receiver, normally referred to as frequency 0.8 offset. This frequency offset can be caused by Doppler shift 0.7 due to relative motion between the transmitter and receiver, 0.6 |S(l-k)| 0.5 or by differences between the frequencies of the local 0.4 oscillators at the transmitter and receiver. In this project, the 0.3 frequency offset is modeled as a multiplicative factor 0.2 introduced in the channel, as shown in Figure: shows. 0.1 0 0 5 10 15 Subcarrier Index k Figure ICI Coefficients for N=16 Carriers This figure shows that for a larger ε, the weight of the desired signal component, S(0), decreases, while the weights of the ICI components increases. The authors also notice Figure : Frequency Offset Model that the adjacent carrier has the maximum contribution to The received signal is given by, the ICI. This fact is used in the ICI self-cancellation j 2n technique described. y ( n)  x ( n) e N  w(n) IV CONCLUSION Where ε is the normalized frequency offset, and is given by In this project, the performance of OFDM systems in the ∆fNTs. ∆f is the frequency difference between the presence of frequency offset between the transmitter and the transmitted and received carrier frequencies and Ts is the receiver has been studied in terms of the Carrier-to- sub-carrier symbol period. w(n) is the AWGN introduced in Interference ratio (CIR) and the bit error rate (BER) the channel. The effect of this frequency offset on the performance. Inter-carrier interference (ICI), which results received symbol stream can be understood by considering from the frequency offset, degrades the performance of the th OFDM system. the received symbol Y(k) on the k sub-carrier. One method is explored in this project for mitigation of the N 1  X (l )S (l  k )  n ICI i.e. ICI self-cancellation (SC). By using this method the Y (k )  X (k ) S (0)  k BER is improved in comparison to simple OFDM system. l  0 ,l  k k  0,1..........N  1 Where N is the total number of sub-carriers, X(k) is the transmitted symbol (M-ary phase-shift keying (M-PSK), for th example) for the k sub-carrier, is the FFT of w(n), and S(l- k) are the complex coefficients for the ICI components in . the received signal. The ICI components are the interfering Issn 2250-3005(online) August| 2012 Page 1085
  • 3. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 4 References [1] www.mprg.org/people/gametheory/files/chapter%201. pdf. [2] Beibei Wang and K. J. Ray Liu , “Advances in Cognitive Radio Networks: A Survey”, IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, VOL. 5, NO. 1, FEBRUARY 2011. [3] http://en.wikipedia.org/wiki/Cognitive_radio. [4] Federal Communications Commission, “Notice of proposed rule making and order: Facilitating opportunities for flexible, efficient, and reliable spectrum use employing cognitive radio technologies,” ET Docket No. 03-108, Feb. 2005. [5] www.wirelessinnovation.org/assets/documents/tut- cognitive_radio.pdf. [6] Sugata Sanyal , Rohit Bhadauria and Chittabrata Ghosh, “Secure Communication in Cognitive RadioNetworks”, 2009 International Conference on Computers and Devices for Communication. [7] Luca Bixio, Marina Ottonello, Mirco Raffetto, Carlo S. Regazzoni ,“ A comparison between stand-alone and distributed architectures for spectrum hole detection”,IEEE,2010. [8] Q. Zhao and B. M. Sadler, “A survey of dynamic spectrum access,”IEEE Sig. Proc. Mag., vol. 24, pp. 79–89, May 2007. [9] S. Srinivasa and S. A. Jafar, “The throughput potential of cognitive radio: a theoretical perspective,” IEEE Comm. Mag., vol. 45, pp. 73–79, May 2007. [10] Citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.9 1.567. [11] Rajni Dubey and Sanjeev Sharma ,“ Distributed Shared Spectrum Techniques for Cognitive Wireless Radio Networks”, 2010 International Conference on Computational Intelligence and Communication Networks. [12] Ines AISSA, Mounir FRIKHA and Sami TABBANE ,“ Dynamic Spectrum Hole Management in Cognitive Radio”,IEEE,2011. Issn 2250-3005(online) August| 2012 Page 1086