Abstract
This paper addresses an energy-saving problem for the downlink of a cloud-assisted heterogeneous network (HetNet) using a time-division duplex (TDD) model, which aims to minimize the base stations (BSs) sum power consumption while meeting the rate requirement of each user equipment (UE). The basic idea of this work is to make use of the scalability of system configurations such that green resource management can be employed by flexibly switching off some unnecessary hardware components, especially for off-peak traffic scenarios. This motivates us to utilize a flexible BS power consumption formulation to jointly model its signal processing and circuit power, transmit power, and backhaul transmission power. Instead of using the integer variables $\{1, 0\}$ to control the “on/off” two status of a BS in most previous work, we employ the group sparsity of a transmit power vector to denote the activity of each frequency carrier (FC) such that the signal processing and circuit power can be scaled with the effective bandwidth, thereby leading to multiple sleep modes for a BS in multi-FC systems. Based on this BS power model and the group sparsity concept, a simplified resource allocation scheme for joint BS-UE association, FC assignment, downlink power allocation, and BS sleep modes determination is presented, which is based on the average channel statistics computed over the coherence time of the large scale fading (LSF). This semidynamic green resource management mechanism can be formulated as a NP-hard optimization problem. In order to make it tractable, the successive convex approximation (SCA)-based algorithm is applied to efficiently find a stationary solution using a cloud-based centralized optimization. Simulation results also verify the effectiveness of the proposed mechanism under the developed BS power consumption model.
Highlights
The definition of the generation (5G) networks gives the main focus on providing ubiquitous and high data rate services for massive devices [1]
In Section II: We propose a semi-dynamic green resource management mechanism, which is implemented in two time scales: 1) The green scheduling, downlink transmit power allocation and base stations (BSs) sleep modes are jointly optimized and determined at the central processor (CP) in a centralized fashion only based on the large scale fading (LSF) values, and these strategies are fixed while the LSF values stay constant; 2) The low-complexity maximum ratio transmission (MRT) beamforming is designed and employed locally at each BS based on the instantaneous small scale fading (SSF) coefficients
In this paper, motivated by the high demand for energy saving in a cloud-assisted heterogeneous network (HetNet) with off-peak traffic loads, we propose a semi-dynamic green resource management mechanism to minimize BSs energy consumption and to satisfy each user equipment (UE)’s rate requirement
Summary
The definition of the generation (5G) networks gives the main focus on providing ubiquitous and high data rate services for massive devices [1]. Network densification and offloading, increased bandwidth (e.g., by spectrum sharing [2] and carrier aggregation [3]), and advanced multiple-input and multiple-output (MIMO) techniques (e.g., scaling up the number of antennas [4]) are recognized as the three key technologies for future 5G networks to increase the spectral efficiency [5] By employing these concepts, future 5G networks are more likely to become increasingly dense, massive and heterogeneous in order to target very high data rates everywhere. According to the report from Nokia Networks [7], base stations (BSs) consume over 80 percent of a cellular network’s energy consumption, and this work focuses on the problem of energy saving for BSs in the downlink of a HetNet. To reduce the energy consumption of BSs, there are three main methods from the perspective of resource management: 1) green scheduling (e.g., trafficoffloading and flexible frequency reuse), 2) transmit power allocation and 3) sleep mode for lightly loaded hardware components. A brief, comprehensive, yet non-exhaustive review of related work is given as follows
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