Resource allocation techniques for downlink Non-Orthogonal Multiple Access-Based 5G wireless systems

The expected usage growth of smart devices in the wireless cellular system and many connected devices with other new, improved technological advancement has resulted in the high data rate demands and spectrum scarcity problems. Hence, efficient resource allocation techniques are required to improve spectrum utilization and address the high data rate demands for future wireless communication networks. Non-Orthogonal Multiple Access (NOMA) is one of the most promising multiple access technology for fifth-generation (5G) and future advancement due to its significant role in achieving high spectral efficiency and energy efficiency together with supporting large number of connectivity required for massive machine-type communication (mMTC). This thesis’s main objective is to solve the downlink NOMA systems’ resource allocation problems for improving the system sum rate and energy efficiency. The study addressed the optimization of resources in a single-cell and heterogeneous transmission systems using convex optimization techniques. First, the downlink NOMA-based single-cell systems’ resource allocation problems are addressed. The closed-form solutions are derived using Karush-Kuhn-Tucker (KKT) conditions to maximize the system sum rate and the Dinkelbach (DKL) algorithm to maximize system energy efficiency. Moreover, the Hungarian (HNG) algorithm is utilized for pairing two users into the sub-channel. For 10 users, 2 W Base Station (BS) power, the system sum rate of the proposed NOMA with optimal power allocation using KKT conditions and HNG (NOMA-PKKT-HNG) achieves a higher sum rate by 20.02 %, 40.09 %, and 50.32 % than NOMA with a Difference of Convex programming (NOMA-DC), NOMA with Fractional Transmitting Power Allocation (NOMA-FTPA), and conventional Orthogonal Frequency Division Multiple Access (OFDMA) techniques respectively. Besides, with 20 users at the BS, the system energy efficiency presented an optimal power allocation using DKL and HNG (NOMA-PDKL-HNG) with greater performance than those from NOMA-DC, NOMA-FTPA and OFDMA by 40 %, 59 %, and 86 % respectively. Second, the downlink NOMA’s resource allocation problems in a heterogeneous network (NOMA-HetNets) are investigated. The results show that the femtocell user’s minimum energy efficiency by applying NOMA with power allocation method using Sequential Convex Programming and user pairing based on Greedy Algorithm (NOMA-SCP-GA) is higher by 38.22 %, 58.84 %, and 76.39 % compared to NOMA-DC, NOMA-FTPA, and OFDMA methods respectively. The obtained results from both NOMA scenarios confirm that the proposed NOMA-PKKT-HNG, NOMA-PDKL-HNG, and NOMA-SCP-GA methods are promising approaches for the 5G capability demands.

Text FK 2021 92 UPMIR.pdf Download (1MB)

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