Relax online resource allocation algorithms for D2D communication

被引:8
作者
Hossen, Md Sakhawat [1 ]
Hassan, Md Yeakub [1 ]
Hussain, Faisal [1 ]
Choudhury, Salimur [2 ]
Alam, Muhammad Mahbub [1 ]
机构
[1] IUT, Dept Comp Sci & Engn, Dhaka, Bangladesh
[2] Lakehead Univ, Dept Comp Sci, Thunder Bay, ON, Canada
关键词
cellular UEs; D2D pairs; LTE; relax online algorithm; resource allocation;
D O I
10.1002/dac.3555
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Maximizing the system sumrate by sharing the resource blocks among the cellular user equipments and the D2D (device to device) pairs while maintaining the quality of service is an important research question in a D2D communication underlaying cellular networks. The problem can be optimally solved in offline by using the weighted bipartite matching algorithm. However, in long-term evolutionand beyond (4G and 5G) systems, scheduling algorithms should be very efficient where the optimal algorithm is quite complex to implement. Hence, a low complexity algorithm that returns almost the optimal solution can be an alternative to this research problem. In this paper, we propose 2 less complex stable matching-based relax online algorithms those exhibit very close to the optimal solution. Our proposed algorithms deal with fixed number of cellular user equipments and a variable number of D2D pairs those arrive in the system online. Unlike online matching algorithms, we consider that an assignment can be revoked if it improves the objective function (total system sumrate). However, we want to minimize the number of revocation (ie, the number of changes in the assignments) as a large number of changes can be expensive for the networks too. We consider various offline algorithms proposed for the same research problem as relaxed online algorithms. Through extensive simulations, we find that our proposed algorithms outperform all of the algorithms in terms of the number of changes in assignment between 2 successive allocations while maintaining the total system sumrate very close to the optimal algorithm.
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页数:19
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