Download Elastic Traffic Rate Optimization via NOMA Protocols
Journal article, 2019

Non-orthogonal multiple access (NOMA) is a promising scheme for the fifth generation (5G) of mobile communication systems. In this scheme, transmission to multiple users is performed on the same subchannel using superposition coding and successive interference cancellation. In this paper, we focus on a multi-cell network with two, namely, elastic and streaming, users' data traffic models. We exploit the NOMA scheme in order to maximize the download elastic traffic rate at cells, without degrading the download streaming traffic rates. Since elastic traffic rates at different cells are interactive, we maximize the total elastic traffic rates assuming either perfect or partial channel state information available at each base station subject to a target rate for streaming users. Because of the interference due to NOMA as well as the interference among different cells, subchannel assignment and power allocation affect the system performance significantly. For this reason, we propose an iterative algorithm to jointly solve the subchannel assignment and the power allocation problem via the Hungarian algorithm and successive convex approximation, respectively. Finally, our simulation results show the efficiency of the proposed algorithm.

Author

Farzad Eslami

Sharif University of Technology

Mohammad Robat Mili

Sharif University of Technology

Fatemeh Mokhtari

Sharif University of Technology

F. Ashtiani

Sharif University of Technology

Behrooz Makki

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

M. Mirmohseni

Sharif University of Technology

Masoumeh Nasiri-Kenari

Sharif University of Technology

Tommy Svensson

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN)

Vol. 68 1 713-727

Areas of Advance

Information and Communication Technology

Subject Categories

Telecommunications

Communication Systems

Signal Processing

DOI

10.1109/TVT.2018.2885001

More information

Latest update

5/21/2019