Open AccessCooperative resource management and power allocation for multiuser OFDMA networks
Author(s) -
Yassin Mohamad,
Lahoud Samer,
Ibrahim Marc,
Khawam Kinda,
Mezher Dany,
Cousin Bernard
Publication year - 2017
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2017.0201
Subject(s) - computer science , resource allocation , throughput , computer network , cellular network , radio resource management , resource management (computing) , context (archaeology) , orthogonal frequency division multiple access , spectral efficiency , heterogeneous network , distributed computing , orthogonal frequency division multiplexing , telecommunications , wireless network , wireless , paleontology , channel (broadcasting) , biology
Mobile network operators are facing the challenge to increase network capacity and satisfy the growth in data traffic demands. In this context, long‐term evolution (LTE) networks, LTE‐advanced networks, and future mobile networks of the fifth generation seek to maximise spectrum profitability by choosing the frequency reuse‐1 model. Owing to this frequency usage model, advanced radio resource management and power allocation schemes are required to avoid the negative impact of interference on system performance. Some of these schemes modify resource allocation between network cells, while others adjust both resource and power allocation. In this study, the authors introduce a cooperative distributed interference management algorithm, where resource and power allocation decisions are jointly made by each cell in collaboration with its neighbouring cells. Objectives sought are: increasing user satisfaction, improving system throughput, and increasing energy efficiency. The proposed technique is compared with the frequency reuse‐1 model and to other state‐of‐the‐art techniques under uniform and non‐uniform user distributions and for different network loads. They address scenarios where throughput demands are homogeneous and non‐homogeneous between network cells. System‐level simulation results demonstrate that their technique succeeds in achieving the desired objectives under various user distributions and throughput demands.