Capacity and Interference Aware Resource Allocations for Underlay Device-to-Device Communications

Abstract

Device to device (D2D) communication in underlay inband mode is the most beneficial as sharing the radio resources of existing cellular users with the D2D pairs increases the system capacity. The D2D pairs can communicate by reusing the appropriate RBs of the existing cellular network which increases system capacity and spectral efficiency. However, due to a bad design, sharing resources with the D2D pairs may introduce potential co-channel interference in the cellular network which can affect the primary users. This mode of personal communication is attracting more researchers from academia, standardization bodies, and industry for further insight in developing more efficient resource allocation schemes. In this dissertation, we work towards developing efficient resource allocation algorithms to minimize the system interference and maximize the system capacity to leverage the trade off between primary cellular user and the D2D user. Firstly, we address the research problem of minimizing interference while maintaining individual target sumrate. In One-to-One mode of sharing, it is assumed that one cellular UE is enough to meet the demand of a D2D. Our empirical studies show that in some scenarios, individual cellular UE might not be enough to meet the individual target sumrate constraint. To tackle this issue, we have also considered One-to-Many and Many-to-Many mode of sharing which is a relatively unexplored research domain for centralized approach. Most of the existing research works in centralized approach addressed this problem from the One-to-One point of view for avoiding complexity. In distributed approach, there are some solutions that tackle this issue in both One-to-Many and Many-to-Many paradigms. However, distributed approach requires significantly higher number of message passing than centralized approach which in turn lead to inefficient usage of existing resources. In essence, we tackle the research problem of interference minimization while considering individual target sumrate for One-to-One as well as One-to-Many and Many-to-Many mode of sharing. Secondly, we address the research question of system sumrate maximization while maintaining the quality of service (QoS). This problem can be optimally solved in offline mode by using the weighted bipartite matching algorithm. However, in Long Term Evolution (LTE) and 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 which returns almost the optimal solution can be an alternative to this research problem. In this thesis, we propose two less complex stable matching based relax online algorithms which exhibit very close to the optimal solution. Our proposed solutions deal with fixed number of cellular UEs and a variable number of D2D pairs that 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 (i.e., the number of changes in the assignments) as a large number of changes in successive assignment 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 two successive allocations while maintaining the total system sumrate very close to the optimal algorithm.