Browsing by Author "Abi Abate"

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    Power Control and Resource Allocation for Performance Optimization in D2D Underlaid Massive MIMO System
    (Addis Ababa University, 2022-09) Abi Abate; Anna Förster (Prof.); Yihenew Wondie (PhD)
    The desire to support the ever-increasing demand for wireless broadband service and a broad range of Internet of Things (IoT) applications, where fourth-generation (4G) wireless networks are struggling to deliver, necessitates new fifth-generation (5G) network architecture. The emerging 5G network should employ multiple advanced networking solutions to overcome the challenges posed by dynamic service quality requirements. As a single technology cannot achieve the diverse set of 5G requirements, the challenges and benefits of integrating multiple technologies in one system are worth investigating. On the other hand, the need to communicate with low latency requires a fundamental shift from centralized resource management and interference coordination toward distributed approaches, where intelligent devices can rapidly make resource management decisions. In this thesis, we proposed a distributed resource management and interference coordination scheme to optimize network performance for the coexistence of two technologies that have been identified as competent candidates for achieving the challenging 5G system performance criteria, namely, massive multiple-input multiple-output (MIMO) and network-assisted device-to-device (D2D) communications. First, we formulated a two-tier heterogeneous network with two different user types. The first tier serves the cellular users in the uplink by a multi-antenna Base Station (BS). The second layer serves D2D users exploiting their proximity and transmitting simultaneously, with the uplink cellular user bypassing the multi-antenna BS. Then, we formulated the throughput and energy efficiency optimization problem as a nonlinear optimization problem. To realize a distributed solution, we modelled each optimization problem into a matching game and proposed a resource allocation scheme based on the concept of matching theory. The analysis reveals that the implementation of the proposed distributed resource assignment and interference coordination scheme can achieve more than 88% of the ASR and 85% of the EE performance of optimal result. Next, we proposed a three-stage distributed solution to enhance the sum rate and analyze the impact of joint channel assignment and power control. We model the channel assignment problem in the first stage as a matching game. During this stage, each D2D pair sends its preferred channel request to the BS; and the BS accept the most preferred request. In the second stage, we model the power allocation problem as a non-cooperative game. Each D2D pair optimizes its utility value according to its side link quality and interference channel gain to limit the D2D-to-cellular interference. Finally, in the third stage, the algorithm considers the peer effect, searching for blocking pairs until stable matching is established. The performances of proposed schemes are investigated as a function of the number of BS antennas and cellular and D2D users and compared with the random and optimal counterparts. The numerical results show that the joint optimization of channel assignment and power control can enhance the sum rate performance of channel assignment with binary power allocation scheme where D2D pairs are either turned on with full power or turned off completely by 16%. In general, the extra degrees of freedom resulting from having multiple antennas at BS is highly desirable in the design of future D2D-enabled massive MIMO networks, as many side link users can be multiplexed, and inter-user interference can be controlled.