TY - JOUR
T1 - A minorization-maximization method for optimizing sum rate in the downlink of non-orthogonal multiple access systems
AU - Hanif, Muhammad Fainan
AU - Ding, Zhiguo
AU - Ratnarajah, Tharmalingam
AU - Karagiannidis, George K.
N1 - Funding Information:
The work of M. F. Hanif and Z. Ding was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/L025272/1. The work of T. Ratnarajah was supported by the UK EPSRC under grant number EP/L025299/1.
Publisher Copyright:
© 2015 IEEE.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - Non-orthogonal multiple access (NOMA) systems have the potential to deliver higher system throughput, compared with contemporary orthogonal multiple access techniques. For a linearly precoded multiple-input single-output (MISO) system, we study the downlink sum rate maximization problem, when the NOMA principle is applied. Being a non-convex and intractable optimization problem, we resort to approximate it with a minorization-maximization algorithm (MMA), which is a widely used tool in statistics. In each step of the MMA, we solve a second-order cone program, such that the feasibility set in each step contains that of the previous one, and is always guaranteed to be a subset of the feasibility set of the original problem. It should be noted that the algorithm takes a few iterations to converge. Furthermore, we study the conditions under which the achievable rates maximization can be further simplified to a low complexity design problem, and we compute the probability of occurrence of this event. Numerical examples are conducted to show a comparison of the proposed approach against conventional multiple access systems.
AB - Non-orthogonal multiple access (NOMA) systems have the potential to deliver higher system throughput, compared with contemporary orthogonal multiple access techniques. For a linearly precoded multiple-input single-output (MISO) system, we study the downlink sum rate maximization problem, when the NOMA principle is applied. Being a non-convex and intractable optimization problem, we resort to approximate it with a minorization-maximization algorithm (MMA), which is a widely used tool in statistics. In each step of the MMA, we solve a second-order cone program, such that the feasibility set in each step contains that of the previous one, and is always guaranteed to be a subset of the feasibility set of the original problem. It should be noted that the algorithm takes a few iterations to converge. Furthermore, we study the conditions under which the achievable rates maximization can be further simplified to a low complexity design problem, and we compute the probability of occurrence of this event. Numerical examples are conducted to show a comparison of the proposed approach against conventional multiple access systems.
KW - Complexity
KW - connectivity
KW - convex optimization
KW - latency
KW - non-orthogonal multiple access
KW - orthogonal multiple access
KW - spectral efficiency
KW - zero forcing
UR - http://www.scopus.com/inward/record.url?scp=85009343986&partnerID=8YFLogxK
U2 - 10.1109/TSP.2015.2480042
DO - 10.1109/TSP.2015.2480042
M3 - Article
AN - SCOPUS:85009343986
SN - 1053-587X
VL - 64
SP - 76
EP - 88
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 1
M1 - 7277111
ER -