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Rohollah Yousefpour

Rohollah Yousefpour

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty of Mathematical Sciences
Address:
Phone: 09113147287

Research

Title
Tier-Aware Joint Sub-channel and Power Allocation in Uplink OFDMA Heterogeneous Networks
Type
JournalPaper
Keywords
mixed-integer linear programming, subchannel and power allocation, polynomial-time complexity
Year
2018
Journal Transactions on Emerging Telecommunications Technologies
DOI
Researchers Hamed Rajabi ، Mehdi Rasti ، Hossien Pedram ، Rohollah Yousefpour

Abstract

We study the problem of tier-aware subchannel and power allocation in the uplink of a two-tier orthogonal frequency-division multiple access heterogeneous network. We formulate the joint subchannel and power allocation problem in the macro-tier as an optimization problem that is aware of the existence of the femto-tier and aims to maximize the sum of tolerable interference caused by femto-tier on its allocated subchannel(s) subject to the minimum data rate requirements of the macrocell user equipments (MUEs). The resource allocation problem for the macro-tier is an NP-hard mixed-integer nonlinear programming (MINLP) problem. To address it, we reformulate and transform it to a tractable mixed-integer linear programming (MILP) problem, which is optimally addressed with polynomial-time complexity. We formulate the joint subchannel and power allocation problem in the femto-tier as an optimization problem that is aware of the existence of the macro-tier and aims to maximize the sum rate of the femtocell user equipments subject to themaximum tolerable interference caused to the MUEs. To address this MINLP problem, we transform it to a MILP problem through a linear approximation, which is solved optimally by IBM CPLEX solver. In addition, we develop a distributed and efficient algorithm that addresses this optimization problem suboptimally with a lower computational complexity. Numerical results show that our proposed algorithms outperform the existing algorithms in terms of network sum rate.