TY - JOUR
T1 - Optimizing Weighted-Sum Energy Efficiency in Downlink and Uplink NOMA Systems
AU - Zamani, Mohammad Reza
AU - Eslami, Mohsen
AU - Khorramizadeh, Mostafa
AU - Zamani, Hojatollah
AU - Ding, Zhiguo
N1 - Publisher Copyright:
© 1967-2012 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - In this paper, weighted sum energy efficiency (WSEE) in uplink and downlink of a multi-user non-orthogonal multiple access (NOMA) system is considered. we adopt a more realistic power consumption model where signal processing power is modeled as a linear function of transmit power. Rather than the well-known network-centric global energy efficiency (GEE) metric, which is a pseudo-concave (PC) function, the weighted sum energy efficiency metric is considered, which is not PC in general. To find the optimum user power allocation Dinkelbach-like algorithm is adopted, by which each individual fractional EE function is converted to a parametric function where under some conditions on the weights falls into a class of convex optimization problems and it is solved in the dual domain. The dual variables are updated using a sub-gradient and cutting plane-based algorithm, which here ellipsoid method is used. Since the optimum solution restricts user weights, a low complexity suboptimum algorithm that does not consider any condition on user's weights is proposed. The problem is non-convex in general; hence, epigraph form followed by successive convex approximation (SCA) is used to deal with that problem. Results demonstrate that with the user-oriented metric, one can provide different priorities to users, and by choosing proper weights entail fairness among users.
AB - In this paper, weighted sum energy efficiency (WSEE) in uplink and downlink of a multi-user non-orthogonal multiple access (NOMA) system is considered. we adopt a more realistic power consumption model where signal processing power is modeled as a linear function of transmit power. Rather than the well-known network-centric global energy efficiency (GEE) metric, which is a pseudo-concave (PC) function, the weighted sum energy efficiency metric is considered, which is not PC in general. To find the optimum user power allocation Dinkelbach-like algorithm is adopted, by which each individual fractional EE function is converted to a parametric function where under some conditions on the weights falls into a class of convex optimization problems and it is solved in the dual domain. The dual variables are updated using a sub-gradient and cutting plane-based algorithm, which here ellipsoid method is used. Since the optimum solution restricts user weights, a low complexity suboptimum algorithm that does not consider any condition on user's weights is proposed. The problem is non-convex in general; hence, epigraph form followed by successive convex approximation (SCA) is used to deal with that problem. Results demonstrate that with the user-oriented metric, one can provide different priorities to users, and by choosing proper weights entail fairness among users.
KW - Dinkelbach-like
KW - Non-orthogonal multiple access (NOMA)
KW - power consumption model (PCM)
KW - successive convex approximation (SCA)
KW - weighted sum energy efficinecy (WSEE)
UR - http://www.scopus.com/inward/record.url?scp=85095695917&partnerID=8YFLogxK
U2 - 10.1109/TVT.2020.3007716
DO - 10.1109/TVT.2020.3007716
M3 - Article
AN - SCOPUS:85095695917
SN - 0018-9545
VL - 69
SP - 11112
EP - 11127
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 10
M1 - 9136888
ER -