Efficient resource management for sum capacity maximization in 5G NOMA systems

A Ali, A Baig, GM Awan, WU Khan, Z Ali… - Applied System …, 2019 - mdpi.com
A Ali, A Baig, GM Awan, WU Khan, Z Ali, GAS Sidhu
Applied System Innovation, 2019mdpi.com
The modern cellular technologies are expected to provide high data rates and massive
connectivity in fifth generation (5G) systems; however, this may be impossible through
traditional radio access techniques. Recently, non-orthogonal multiple access (NOMA) has
emerged as one of the promising cellular techniques for modern cellular communications
with its ability to provide access for multiple users to the network over the same system
resources. This paper studies resource management problem for downlink transmission of …
The modern cellular technologies are expected to provide high data rates and massive connectivity in fifth generation (5G) systems; however, this may be impossible through traditional radio access techniques. Recently, non-orthogonal multiple access (NOMA) has emerged as one of the promising cellular techniques for modern cellular communications with its ability to provide access for multiple users to the network over the same system resources. This paper studies resource management problem for downlink transmission of multiuser NOMA system. Our objective is to optimize both frequency and power resources for sum capacity maximization while taking into account each user minimum capacity requirement. Firstly, the problem of resource management decouples into two subproblems, that is, efficient sub-channel assignment and optimal power allocation, respectively. Secondly, for given power at base station, we design two sub-optimal algorithms for sub-channel assignment based on user channel condition and user minimum capacity requirement, respectively. Lastly, for any given sub-channel assignment, the problem first transforms into standard convex optimization problem and then we employ duality theory. To evaluate our proposed NOMA scheme, the enhanced version of existing NOMA optimization scheme is also presented as a benchmark. Results demonstrate that the proposed NOMA resource management scheme outperforms the benchmark NOMA optimization scheme in terms of sum capacity.
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