scholarly journals Joint Optimization of Molecular Resource Allocation and Relay Positioning in Diffusive Nanonetworks

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 67681-67687 ◽  
Author(s):  
Satish K. Tiwari ◽  
Tadi Ravi Teja Reddy ◽  
Prabhat K. Upadhyay ◽  
Daniel Benevides Da Costa
Keyword(s):  
Resource Allocation ◽  
Joint Optimization ◽  
Relay Positioning

scholarly journals Resource Allocation for Energy Efficient User Association in User-Centric Ultra-Dense Networks Integrating NOMA and Beamforming

2020 ◽  
Author(s):  
Long Zhang ◽  
Guobin Zhang ◽  
Xiaofang Zhao ◽  
Yali Li ◽  
Chuntian Huang ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Large Scale ◽  
Mixed Integer ◽  
Joint Optimization ◽  
User Association ◽  
Dual Decomposition ◽  
Dense Networks ◽  
Wireless Backhaul ◽  
User Centric

A coupling of wireless access via non-orthogonal multiple access and wireless backhaul via beamforming is a promising way for downlink user-centric ultra-dense networks (UDNs) to improve system performance. However, ultra-dense deployment of radio access points in macrocell and user-centric view of network design in UDNs raise important concerns about resource allocation and user association, among which notably is energy efficiency (EE) balance. To overcome this challenge, we develop a framework to investigate the resource allocation problem for energy efficient user association in such a scenario. The joint optimization framework aiming at the system EE maximization is formulated as a large-scale non-convex mixed-integer nonlinear programming problem, which is NP-hard to solve directly with lower complexity. Alternatively, taking advantages of sum-of-ratios decoupling and successive convex approximation methods, we transform the original problem into a series of convex optimization subproblems. Then we solve each subproblem through Lagrangian dual decomposition, and design an iterative algorithm in a distributed way that realizes the joint optimization of power allocation, sub-channel assignment, and user association simultaneously. Simulation results demonstrate the effectiveness and practicality of our proposed framework, which achieves the rapid convergence speed and ensures a beneficial improvement of system-wide EE.<br>

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