Diverse Resource Allocation Techniques in D2D Networks
Rishabh Chakraborty1, Rohit Agarwal2, Srishti Mallick3, K. Saravanan4
1Rishabh Chakraborty, Department of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
2Rohit Agarwal, Department of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
3Srishti Mallick, Department of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
4Saravanan K, Professor, Department of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
Manuscript received on May 03, 2020. | Revised Manuscript received on May 13, 2020. | Manuscript published on June 10, 2020. | PP: 299-304 | Volume-9 Issue-8, June 2020. | Retrieval Number: 100.1/ijitee.H6344069820 | DOI: 10.35940/ijitee.H6344.069820
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: D2D communication is going to be the upcoming technology which is going to change the era of wireless networks due to its flexibility. Due to the limited availability of Spectral resources, the co-channel interference is increasing. Co- channel interference occurs when number of User Equipment (UEs) share the same frequency block or commonly known as Resource Block (RB). Many researchers have ideated different Resource Allocation (RA) algorithms using modern optimisation methods like Fuzzy Logic, Game theory, Graph colouring and clustering. RA helps to provide proper channel to UEs and thus ensures proper utilisation of spectrum which is limited. With proper RA, the overall interferences can be mitigated easily and therefore it enhances the parameters such as QoS (Quality of Service), SNR, Throughput, power consumption, etc which are used to check the quality of the wireless network. In this paper review of these various RA methods, literature and deep analysis for clustering algorithm is carried out for different values of RBs and comparison Data Rates for various values of Bandwidth. A modified Spectral clustering method is propounded which will handle the number of clusters formation on the basis of requirements. The proposed RA technique is going to deal with the interferences step by step using modified Greedy algorithm and minimise the interference value until it can’t be further minimised. Data Rate is calculated using Shannon’s Theorem from the SINR values obtained.
Keywords: Clustering, Co-channel interference, D2D, Data Rate, RA, SNR and spectrum.
Scope of the Article: Clustering