Base Station Switching Off Research Articles

Energy-Efficient Base Station Switching-Off With Guaranteed Cooperative Profit Gain of Mobile Network Operators

This paper studies the energy-efficient cooperative base station (BS) switching-off in multi-input single-output (MISO) cellular networks, where the roaming-cost-based cooperation and the cooperative beamforming among multiple mobile network operators (MNOs) are jointly designed. To make the cooperation among MNOs practical, we introduce a new constraint to make sure the cooperative profit gain of MNOs is non-negative and also formulate an optimization problem to maximize the system energy efficiency (EE) by jointly considering multiple factors, including the operation modes of BSs, the connection states between users and BSs, the beamforming vectors of multi-antenna BSs under constraints of users’ quality of service, BSs’s power budget, and the non-negative profit gain of MNOs, etc. To solve the non-convex problem, we propose an energy-efficient beamforming-aware BS switching off method (EBBSOM), in which we first design a roaming-cost-based BS switching-off algorithm (EE-BSOA) to search the feasible inactive BSs and then propose a successive convex approximation (SCA) and Dinkelbach’s method-based EE maximization beamforming algorithm (EE-BFA) to optimize beamforming vectors. In order to keep the cooperative profit gain non-negative for MNOs and also to balance the load and power consumption of BS from the profit perspective, we present a profit-wise BS switching-off priority method. We theoretically prove that the proposed EBBSOM is able to resolve the inconsistency between BS switching-off and EE maximization. Simulations show that the proposed EBBSOM enhances the system EE without degrading the economic profit gain of MNOs. Also, the proposed profit-wise BS switching-off priority enables the EBBSOM to achieve higher EE than traditional load-wise one. Furthermore, it is also observed that there exists a feasible rate price region, which is able to clearly characterize network EE and the average profit gain of MNOs simultaneously.

User re-association and resource/power re-allocation of cell switched-off User Equipments in green cellular networks

Energy consumption of cellular networks has gained significant attention in recent years as green cellular networking paradigm appeared. Base Station (BS) switch-off is a solution for minimizing energy consumption of green cellular networks. However, User Equipments (UEs) of switched-off BSs lose their connectivity to the network and should be re-associated with BSs, attain new radio resources, and re-adjust their transmission powers. Previous studies have either not addressed this issue or have considered the joint problem of BS switch-off and BS association/resource allocation, while those joint problems are not spectrum efficient. In this paper, we formulate two different optimization problems for spectrum efficient re-association of involved UEs and re-allocation of their uplink radio/power resources after an energy-efficient BS switch-off. The first optimization problem aims at maximizing the achievable rate of cell switched-off UEs, while the second problem intends to maximize the achievable rate of all UEs of the network when a cell switch-off occurs. In formulated problems, the required rate of UEs is regarded as the QoS constraint. Decoupling the problems into sub-problems, we propose a distributed solution for user re-association, channel re-allocation, and power adjustment of UEs. Simulation results show superior performance of the proposed methods compared to the baseline methods in terms of the network capacity and QoS guarantee.

A TLBO-BASED ENERGY EFFICIENT BASE STATION SWITCH OFF AND USER SUBCARRIER ALLOCATION ALGORITHM FOR OFDMA CELLULAR NETWORKS

Downlink of a cellular network with orthogonal frequency-division multiple access (OFDMA) is considered. Joint base station switch OFF and user subcarrier-allocation with guaranteed user quality of service, is shown to be a promising approach for reducing network’s total power consumption. However, solving the aforementioned mix-integer and nonlinear optimization problem requires robust and powerful optimization techniques. In this paper, teaching-learning based optimization algorithm has been adopted to lower cellular network’s total power consumption. The results show that the proposed technique is able to reduce network’s total power consumption by determining a near optimum set of base stations to be switched OFF and near optimum subcarrier-user assignments. It is shown that the proposed scheme is superior to existing base station switch OFF schemes. Robustness of the proposed TLBO-based technique is verified.

Energy-efficient infrastructure sharing in multi-operator mobile networks

Network infrastructure sharing and base station switching off mechanisms have been recently introduced as promising solutions toward energy and cost reduction in cellular networks. Although these techniques are usually studied independently, their combination offers new alternatives to MNOs for serving their users and could potentially provide them with additional benefits. In this article we introduce the concept of intra-cell roaming-based infrastructure sharing, where the MNOs may switch off their BSs and roam their traffic to active BSs operated by other MNOs in the same cell. Motivated by the coexistence of multiple operators in the same area, we present possible network deployments and architectures in current and future cellular scenarios, discussing their particular characteristics. In addition, we propose an innovative distributed game theoretic BS switching off scheme, employing an integrated cost function that takes into account all the different cases for a given operator to serve its own traffic (i.e. through active BSs of neighboring cells or exploiting intra-cell roaming-based infrastructure sharing). Finally, we demonstrate some indicative simulation results in realistic scenarios to quantify the potential energy and financial benefits that our proposed scheme offers to the MNOs in multi-operator environments, providing them with the necessary incentives to participate in the infrastructure sharing.