TY - GEN
T1 - Downlink Power Allocation in SCMA with Finite-Alphabet Constraints
AU - Cui, Jingjing
AU - Fan, Pingzhi
AU - Lei, Xianfu
AU - Ma, Zheng
AU - Ding, Zhiguo
N1 - Funding Information:
ACKNOWLEDGMENT The authors would like to thank the Huawei HIRP Flagship Project (No.YB201504), the National Science and Technology Major Project (No.2016ZX03001018-002) and the National Natural Science Foundation of China (No. 61501382). The authors would also like to thank the open research fund of National Mobile Communications Research Laboratory, Southeast University (No. 2017D15), Sichuan International Science & Technology Cooperation and Exchange Project (2017HH0035), Fundamental Research Funds for the Central Universities (No. 2682015RC20 & 2682016CY22).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/14
Y1 - 2017/11/14
N2 - The power allocation for multi-user sparse code multiple access (SCMA) downlink systems with finite- alphabet constraints is investigated. An explicit expression for the achievable rate for downlink SCMA systems with finite-alphabet inputs is derived, which is applicable to arbitrary number of users. Moreover, a novel power allocation scheme that can ensure users' fairness for multi-user SCMA downlink systems is proposed. In an effort to solve the formulated non-convex optimization problem, a low- complexity polynomial algorithm is proposed, which yields an optimal solution. Simulation results demonstrate that the proposed power allocation algorithm is capable of enhancing the performance significantly compared to the equal power allocation scheme.
AB - The power allocation for multi-user sparse code multiple access (SCMA) downlink systems with finite- alphabet constraints is investigated. An explicit expression for the achievable rate for downlink SCMA systems with finite-alphabet inputs is derived, which is applicable to arbitrary number of users. Moreover, a novel power allocation scheme that can ensure users' fairness for multi-user SCMA downlink systems is proposed. In an effort to solve the formulated non-convex optimization problem, a low- complexity polynomial algorithm is proposed, which yields an optimal solution. Simulation results demonstrate that the proposed power allocation algorithm is capable of enhancing the performance significantly compared to the equal power allocation scheme.
UR - http://www.scopus.com/inward/record.url?scp=85040574366&partnerID=8YFLogxK
U2 - 10.1109/VTCSpring.2017.8108679
DO - 10.1109/VTCSpring.2017.8108679
M3 - Conference contribution
AN - SCOPUS:85040574366
T3 - IEEE Vehicular Technology Conference
BT - 2017 IEEE 85th Vehicular Technology Conference, VTC Spring 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 85th IEEE Vehicular Technology Conference, VTC Spring 2017
Y2 - 4 June 2017 through 7 June 2017
ER -