Energy-Efficient Resource Allocation for Fractional Frequency Reuse in Heterogeneous Networks

Abstract

Next generation wireless networks face the challenge of increasing energy consumption while satisfying the unprecedented increase in the data rate demand. To address this problem, we propose a utility-based energy-efficient resource allocation algorithm for the downlink transmissions in heterogeneous networks (HetNets). We consider the fractional frequency reuse (FFR) method in order to mitigate the intraand inter-cell interference. The proposed algorithm divides the resource allocation problem into frequency and power assignment problems and sequentially solves them. The proposed power control algorithm uses the gradient ascent method to control the transmit power of macrocell base stations (MeNBs) as most of the power in the network is consumed there. We present the optimality conditions of the resource allocation problem and the convergence of the proposed algorithm. In order to mitigate the inter-cell interference further, we study the interference pricing mechanisms and obtain an upper bound to the maximum energy efficiency problem including the inter-cell interference contributions. The performance of the proposed algorithm is studied in a Long Term Evolution (LTE) system. Our simulation results demonstrate that the proposed algorithm provides substantial improvements in the energy efficiency and throughput of the network. It is also shown that interference pricing provides only marginal improvements over the proposed algorithm.

New algorithms for maximizing cellular wireless network energy efficiency

“…This model is also proposed in [26]. We adopt the same simulation parameters and models as in [5]. For the scheduler, we employ the Equal Bandwidth Scheduler which is detailed in [5], [26], [27].…”

“…We also incorporate the minimum rate constraints per user to account for different quality-of-service levels. Since the proposed algorithms employ closed-form expressions for the power updates and do not require any derivatives, their implementation complexities are significantly low compared to the works in [5], [13]- [15]. We evaluate the performance of the proposed algorithm and compare its performance with the ones proposed in [4] and [5] and demonstrate that the proposed algorithm outperforms both of these works.…”

“…Second, in our formulation, we extend the energy efficiency maximizing problem to include other constraints such as the minimum rate, total power constraints, and spectral mask constraints per subcarrier. Our prior work in [5] addresses the same problem, but it uses constant power allocation across subbands. It employs two variables to characterize the power transmissions per sector, which are to be optimized.…”

On the Performance of Multi-Tier Heterogeneous Networks under LoS and NLoS Transmissions

“…is the average spatial power consumption [7]. By substituting (11) into (12), we have the EE of a K-tier as…”

“…It is also worth noting that most HetNet performance analyses do not focus on energy efficiency (EE), and that a rapid increase in the number of deployed small-cell BSs may lead to an increase in the total energy consumption of a HetNet, affecting its environmental friendliness or economic sustainability [7]. Thus, there is a need for comprehensive HetNet performance analyses, considering also HetNet EE.…”