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Joint uplink and downlink delay‐aware resource allocation in C‐RAN
Author(s) -
Tohidi Masumehsadat,
Bakhshi Hamidreza,
Parsaeefard Saeedeh
Publication year - 2020
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.3778
Subject(s) - telecommunications link , computer science , resource allocation , geometric programming , throughput , radio access network , optimization problem , baseband , computer network , transmitter power output , remote radio head , convex optimization , mathematical optimization , algorithm , base station , regular polygon , wireless , mathematics , telecommunications , transmitter , mobile station , channel (broadcasting) , geometry , bandwidth (computing) , machine learning
This work considers two‐way communication between each pair of users with highly delay‐aware applications. We formulate a joint uplink and downlink resource allocation problem in a cloud radio access network. Assuming average end‐to‐end (E2E) delay of each user pair and practical limitation such as maximum transmit power, we maximize the total throughput of all pair of users in the cloud radio access network. In this setup, we consider that each user can be connected to at most one remote radio head and a limited capacity fronthaul link between each remote radio head and baseband unit. To present the resource allocation problem in a more tractable manner, we replace the E2E delay limitation with its equivalent throughput‐based formulation. Due to inherent NP‐hard and nonconvex nature of the proposed problem, we apply successive convex approximation to reach a two‐step iterative algorithm where, in each step, a specific set of optimization variable derived while other variables are fixed. The problem of each step is transformed into the standard geometric programming via the arithmetic‐geometric mean approximation. Simulation results reveal that our proposed joint uplink‐downlink resource allocation algorithm outperforms a case that uplink and downlink resources are allocated separately in terms of total throughput and outage probability of E2E delay, ie, a chance that E2E delay does not hold.