[Paper Review] Joint User Association and Resource Allocation Optimization for Ultra Reliable Low Latency HetNets

Mohammad Yousefvand, Narayan B. Mandayam|arXiv (Cornell University)|Sep 18, 2018

Advanced MIMO Systems Optimization17 references4 citations

TL;DR

This paper proposes a relaxed heuristic method (RHM) for joint user association and resource allocation in ultra-reliable low-latency communication (URLLC) heterogeneous networks (HetNets), reducing time complexity and improving energy and spectral efficiency. By decoupling user association from convex resource allocation and using ADMM for optimization, the method reduces cellular base station (CBS) spectrum access delay by 93% and energy consumption by 33% while maintaining full service rates.

ABSTRACT

Ensuring ultra-reliable and low latency communications (URLLC) is necessary for enabling delay critical applications in 5G HetNets. We propose a joint user to BS association and resource optimization method that is attractive for URLLC in HetNets with Cellular Base Stations (CBSs) and Small Cell Base Stations (SBSs), while also reducing energy and bandwidth consumption. In our scheme, CBSs share portions of the available spectrum with SBSs, and they in exchange, provide data service to the users in their coverage area. We first show that the CBSs optimal resource allocation (ORA) problem is NP-hard and computationally intractable for large number of users. Then, to reduce its time complexity, we propose a relaxed heuristic method (RHM) which breaks down the original ORA problem into a heuristic user association (HUA) algorithm and a convex resource allocation (CRA) optimization problem. Simulation results show that the proposed heuristic method decreases the time complexity of finding the optimal solution for CBS's significantly, thereby benefiting URLLC. It also helps the CBSs to save energy by offloading users to SBSs. In our simulations, the spectrum access delay for cellular users is reduced by 93\% and the energy consumption is reduced by 33\%, while maintaining the full service rate.

Motivation & Objective

• To address the high time complexity of optimal resource allocation (ORA) in URLLC-enabled HetNets with cellular and small cell base stations.
• To reduce energy and bandwidth consumption at CBSs by enabling offloading of users to SBSs through spectrum sharing.
• To minimize spectrum access delay for delay-critical URLLC applications while maintaining full service rates.
• To develop a scalable, low-complexity solution for large-scale HetNets where the ORA problem is NP-hard.
• To design a heuristic framework that decomposes the non-convex ORA problem into tractable subproblems for efficient computation.

Proposed method

• The ORA problem is formulated as a non-convex, NP-hard combinatorial optimization involving user association, bandwidth, and power allocation.
• A relaxed heuristic method (RHM) decomposes the ORA problem into a heuristic user association (HUA) algorithm and a convex resource allocation (CRA) problem.
• The HUA algorithm assigns users to CBSs or SBSs based on channel gain and service requirements, minimizing CBS resource usage.
• The CRA problem minimizes CBS power consumption under minimum data rate and bandwidth constraints, reformulated as a convex optimization problem.
• The ADMM algorithm is applied to solve the CRA problem iteratively, reducing time complexity and accelerating convergence.
• The method leverages spectrum sharing, where CBSs grant portions of their licensed spectrum to SBSs in exchange for offloading user traffic.

Experimental results

Research questions

• RQ1 How can joint user association and resource allocation be optimized to minimize time complexity in URLLC-enabled HetNets?
• RQ2 What is the computational complexity of the optimal resource allocation (ORA) problem in HetNets with CBSs and SBSs?
• RQ3 Can a heuristic decomposition approach significantly reduce the time complexity of ORA while preserving performance?
• RQ4 To what extent can CBS energy and bandwidth consumption be reduced through intelligent user offloading to SBSs?
• RQ5 How effective is the ADMM-based solution in accelerating convergence for the convex resource allocation subproblem?

Key findings

• The ORA problem is proven to be NP-hard by reduction to the zero-one knapsack problem, confirming its computational intractability for large-scale networks.
• The proposed RHM reduces the time complexity of finding the optimal solution for CBS resource allocation by significantly accelerating computation.
• Spectrum access delay for cellular users is reduced by 93% due to efficient user offloading and faster resource allocation.
• CBS energy consumption is reduced by 33% through offloading users to SBSs and minimizing transmit power on retained users.
• The method maintains full service rates for all users while achieving high spectral and energy efficiency.
• The ADMM-based solution effectively accelerates convergence in the convex resource allocation phase, enhancing scalability for large networks.