Energy Efficiency and Optimal Power Allocation in Virtual-MIMO Systems

2012 ◽  
Author(s):  
Jing Jiang ◽  
Mehrdad Dianati ◽  
Muhammad Ali Imran ◽  
Yan Chen
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Mimo Systems ◽  
Optimal Power Allocation ◽  
Virtual Mimo ◽  
Optimal Power

scholarly journals User Clustering and Power Allocation for Energy Efficiency Maximization in Downlink Non-Orthogonal Multiple Access Systems

2021 ◽  
Vol 11 (2) ◽  
pp. 716
Author(s):  
Ruibiao Chen ◽  
Fangxing Shu ◽  
Kai Lei ◽  
Jianping Wang ◽  
Liangjie Zhang
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Multiple Access ◽  
Spectrum Efficiency ◽  
Lagrangian Multiplier ◽  
Efficiency Gain ◽  
Optimal Power Allocation ◽  
Optimal Power ◽  
User Clustering ◽  
Cluster Dynamic

Non-orthogonal multiple access (NOMA) has been considered a promising technique for the fifth generation (5G) mobile communication networks because of its high spectrum efficiency. In NOMA, by using successive interference cancellation (SIC) techniques at the receivers, multiple users with different channel gain can be multiplexed together in the same subchannel for concurrent transmission in the same spectrum. The simultaneously multiple transmission achieves high system throughput in NOMA. However, it also leads to more energy consumption, limiting its application in many energy-constrained scenarios. As a result, the enhancement of energy efficiency becomes a critical issue in NOMA systems. This paper focuses on efficient user clustering strategy and power allocation design of downlink NOMA systems. The energy efficiency maximization of downlink NOMA systems is formulated as an NP-hard optimization problem under maximum transmission power, minimum data transmission rate requirement, and SIC requirement. For the approximate solution with much lower complexity, we first exploit a quick suboptimal clustering method to assign each user to a subchannel. Given the user clustering result, the optimal power allocation problem is solved in two steps. By employing the Lagrangian multiplier method with Karush–Kuhn–Tucker optimality conditions, the optimal power allocation is calculated for each subchannel. In addition, then, an inter-cluster dynamic programming model is further developed to achieve the overall maximum energy efficiency. The theoretical analysis and simulations show that the proposed schemes achieve a significant energy efficiency gain compared with existing methods.

scholarly journals Novel Resource Allocation Techniques for Downlink Non-Orthogonal Multiple Access Systems

2020 ◽  
Vol 10 (17) ◽  
pp. 5892 ◽  
Author(s):  
Zuhura J. Ali ◽  
Nor K. Noordin ◽  
Aduwati Sali ◽  
Fazirulhisyam Hashim ◽  
Mohammed Balfaqih
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Power Allocation ◽  
Multiple Access ◽  
High Capacity ◽  
Kkt Conditions ◽  
Optimal Power Allocation ◽  
User Pairing ◽  
Optimal Power ◽  
Sum Rate

Non-orthogonal multiple access (NOMA) plays an important role in achieving high capacity for fifth-generation (5G) networks. Efficient resource allocation is vital for NOMA system performance to maximize the sum rate and energy efficiency. In this context, this paper proposes optimal solutions for user pairing and power allocation to maximize the system sum rate and energy efficiency performance. We identify the power allocation problem as a nonconvex constrained problem for energy efficiency maximization. The closed-form solutions are derived using Karush–Kuhn–Tucker (KKT) conditions for maximizing the system sum rate and the Dinkelbach (DKL) algorithm for maximizing system energy efficiency. Moreover, the Hungarian (HNG) algorithm is utilized for pairing two users with different channel condition circumstances. The results show that with 20 users, the sum rate of the proposed NOMA with optimal power allocation using KKT conditions and HNG (NOMA-PKKT-HNG) is 6.7% higher than that of NOMA with difference of convex programming (NOMA-DC). The energy efficiency with optimal power allocation using DKL and HNG (NOMA-PDKL-HNG) is 66% higher than when using NOMA-DC.

Optimal Power Allocation for Maximizing Energy Efficiency in DAS-Based IoT Network

2020 ◽  
pp. 1-7
Author(s):  
Zaki Masood ◽  
Hosung Park ◽  
Han Seung Jang ◽  
Sunyong Yoo ◽  
Sokhee P. Jung ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Optimal Power Allocation ◽  
Optimal Power

Optimal power allocation for homogeneous and heterogeneous CA-MIMO systems

2013 ◽  
Vol 56 (2) ◽  
pp. 1-14 ◽  
Author(s):  
QiMei Cui ◽  
PeiChuan Kang ◽  
XueQing Huang ◽  
Mikko Valkama ◽  
Jarno Niemela
Keyword(s):  
Power Allocation ◽  
Mimo Systems ◽  
Optimal Power Allocation ◽  
Optimal Power
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