Power Control and Resource Allocation for Performance Optimization in D2D Underlaid Massive MIMO System
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Date
2022-09
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Addis Ababa University
Abstract
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.
Description
Keywords
Device-to-Device (D2D), massive MIMO communication, interference management, channel assignment, power control