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Reduction Of Papr Using Multi-Carrier Filtering Techniques In 5G Communication System

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Description

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ABSTRACT

In this project, multi-access channel (MAC) protocol based on distributed auction algorithm where each link runs distributive in order to maximize the accumulated sum of QoS. The algorithm is based on a carrier sensing multiple access (CSMA) implementation of the distributed auction algorithm. It does not require any exchange of information between users. Users need only to observe a single channel at a time and sense if there is a transmission on that channel, without decoding the transmissions or identifying the transmitting users. We compare the performance of the proposed algorithm with the state-of-the-art scheme using simulations of realistic long term evolution (LTE) channels. It is noted that the algorithm exploits the CSMA mechanism to bypass the need for an auctioneer and by doing that, implements the auction algorithm distributive. For this purpose, links compute a continuous back-off time that is decreasing with their bit. The highest bit for a particular channel is simply the first link which accesses this channel. However, in contrast we assume all links can sense the channel that they choose, and all links will agree on which link is the highest bidder for their channel.

EXISTING SYSTEM

  • Resource allocation for underlay cognitive radio networks
  • Channel assignment schemes for cellular mobile
  • Stable matching for channel access control in cognitive radio systems
  • Iterative scheduling algorithms

PROPOSED SYSTEM

  • In proposed system, the main objective of the algorithm is based on a carrier sensing multiple access (CSMA) implementation of the distributed auction algorithm. It does not require any exchange of information between users. Users need only to observe a single channel at a time and sense if there is a transmission on that channel, without decoding the transmissions or identifying the transmitting users.

APPLICATIONS

  • The millimeter-wave supports wide bandwidth, and the short wavelength of it enables the miniaturization of antennas. Therefore, millimeter-wave based mobile communication systems can be equipped with more antennas in the same space as long-term evolution (LTE) base stations. However, short wavelengths can cause high path loss and low signal to noise radio (SNR).

SOFTWARE REQUIRED

MATLAB 2018 and above

REFERENCE

[1] I. Katzela and M. Naghshineh, ?Channel assignment schemes for cellular mobile telecommunication systems: A comprehensive survey,? IEEE Communications Surveys Tutorials, vol. 3, no. 2, pp. 10?31, Second 2000.

[2] M. E. Tanab and W. Hamouda, ?Resource allocation for underlay cognitive radio networks: A survey,? IEEE Communications Surveys & Tutorials, vol. 19, no. 2, pp. 1249?1276, Secondquarter 2017.

[3] H. Kwon, S. Kim, and B. G. Lee, ?Opportunistic multi-channel CSMA protocol for OFDMA systems,? IEEE Transactions on Wireless Communications, vol. 9, no. 5, pp. 1552?1557, May 2010.

[4] Y. Yaffe, A. Leshem, and E. Zehavi, ?Stable matching for channel access control in cognitive radio systems,? in 2010 2nd International Workshop on Cognitive Information Processing, June 2010, pp. 470?475.

[5] A. Leshem, E. Zehavi, and Y. Yaffe, ?Multichannel opportunistic carrier sensing for stable channel access control in cognitive radio systems,? IEEE Journal on Selected Areas in Communications, vol. 30, no. 1, pp. 82?95, January 2012.

[6] O. Naparstek and A. Leshem, ?Bounds on the expected optimal channel assignment in rayleigh channels,? in 2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), June 2012, pp. 294?298.

[7] D. P. Bertsekas, ?The auction algorithm: A distributed relaxation method for the assignment problem,? Annals of Operations Research, vol. 14, no. 1, pp. 105?123, Dec 1988. [Online]. Available: https://doi.org/10.1007/BF02186476

[8] K. Yang, N. Prasad, and X. Wang, ?An auction approach to resource allocation in uplink OFDMA systems,? IEEE Transactions on Signal Processing, vol. 57, no. 11, pp. 4482?4496, Nov 2009.

[9] M. Bayati, B. Prabhakar, D. Shah, and M. Sharma, ?Iterative scheduling algorithms,? in IEEE INFOCOM 2007 – 26th IEEE International Conference on Computer Communications, May 2007, pp. 445?453.

[10] M. Bayati, D. Shah, and M. Sharma, ?Max-product for maximum weight matching: Convergence, correctness, and LP duality,? IEEE Transactions on Information Theory, vol. 54, no. 3, pp. 1241?1251, March 2008.

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