Fundamental Limits of Energy-Efficient Resource Sharing, Power Control and Discontinuous Transmission

The achievable gains via power-optimal scheduling are investigated. Under the QoS constraint of a guaranteed link rate, the overall power consumed by a cellular BS is minimized. Available alternatives for the minimization of transmit power consumption are presented. The transmit power is derived for the two-user downlink situation. The analysis is extended to incorporate a BS power model (which maps transmit power to supply power consumption) and the use of DTX in a BS. Overall potential gains are evaluated by comparison of a conventional SOTA BS with one that employs DTX exclusively, a power control scheme and an optimal combined DTX and power control scheme. Fundamental limits of the achievable savings are found to be at 5.5 dB under low load and 2 dB under high load when comparing the SOTA consumption with optimal allocation under the chosen power model.Comment: 12 pages, ISBN 978-1-4577-0928-9. In Future Network & Mobile Summit (FutureNetw), 201

Enhancing the energy efficiency of radio base stations

This thesis is concerned with the energy efficiency of cellular networks. It studies the dominant power consumer in future cellular networks, the Long Term Evolution (LTE) radio Base Station (BS), and proposes mechanisms that enhance the BS energy efficiency by reducing its power consumption under target rate constraints. These mechanisms trade spare capacity for power saving. First, the thesis describes how much power individual components of a BS consume and what parameters affect this consumption based on third party experimental data. These individual models are joined into a component power model for an entire BS. The component model is an essential step in analysis but is too complex for many applications. It is therefore abstracted into a much simpler parameterized model to reduce its complexity. The parameterized model is further simplified into an affine model which can be applied in power minimization. Second, Power Control (PC) and Discontinuous Transmission (DTX) are identified as promising power-saving Radio Resource Management (RRM) mechanisms and applied to multi-user downlink transmission. PC reduces the power consumption of the Power Amplifier (PA) and is found to be most effective at high traffic loads. DTX mostly reduces the power consumption of the Baseband (BB) unit while interrupting transmission and is better applied in low traffic loads. Joint optimization of these two techniques is found to enable additional power-saving at medium traffic loads and to be a convex problem which can be solved efficiently. The convex problem is extended to provide a comprehensive power-saving Orthogonal Frequency Division Multiple Access (OFDMA) frame resource scheduler. The proposed scheduler is shown to reduce power consumption by 25-40% in computer simulations, depending on the traffic load. Finally, the thesis investigates the influence of interference on power consumption in a network of multiple power-saving BSs. It discusses three popular alternative distributed uncoordinated methods which align DTX mode between neighbouring BSs. To address drawbacks of these three, a fourth memory-based DTX alignment method is proposed. It decreases power consumption by up to 40% and retransmission probability by around 20%, depending on the traffic load

Minimizing Base Station Power Consumption

We propose a new radio resource management algorithm which aims at minimizing the base station supply power consumption for multi-user MIMO-OFDM. Given a base station power model that establishes a relation between the RF transmit power and the supply power consumption, the algorithm optimizes the trade-off between three basic power-saving mechanisms: antenna adaptation, power control and discontinuous transmission. The algorithm comprises two steps: a) the first step estimates sleep mode duration, resource shares and antenna configuration based on average channel conditions and b) the second step exploits instantaneous channel knowledge at the transmitter for frequency selective time-variant channels. The proposed algorithm finds the number of transmit antennas, the RF transmission power per resource unit and spatial channel, the number of discontinuous transmission time slots, and the multi-user resource allocation, such that supply power consumption is minimized. Simulation results indicate that the proposed algorithm is capable of reducing the supply power consumption by between 25% and 40%, dependend on the system load.Comment: 27 page

Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks

The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm which incorporates the cloud computing into heterogeneous networks (HetNets), thereby taking full advantage of cloud radio access networks (C-RANs) and HetNets. Characterizing the cooperative beamforming with fronthaul capacity and queue stability constraints is critical for multimedia applications to improving energy efficiency (EE) in H-CRANs. An energy-efficient optimization objective function with individual fronthaul capacity and inter-tier interference constraints is presented in this paper for queue-aware multimedia H-CRANs. To solve this non-convex objective function, a stochastic optimization problem is reformulated by introducing the general Lyapunov optimization framework. Under the Lyapunov framework, this optimization problem is equivalent to an optimal network-wide cooperative beamformer design algorithm with instantaneous power, average power and inter-tier interference constraints, which can be regarded as the weighted sum EE maximization problem and solved by a generalized weighted minimum mean square error approach. The mathematical analysis and simulation results demonstrate that a tradeoff between EE and queuing delay can be achieved, and this tradeoff strictly depends on the fronthaul constraint

Optimal Cell Clustering and Activation for Energy Saving in Load-Coupled Wireless Networks

Optimizing activation and deactivation of base station transmissions provides an instrument for improving energy efficiency in cellular networks. In this paper, we study optimal cell clustering and scheduling of activation duration for each cluster, with the objective of minimizing the sum energy, subject to a time constraint of delivering the users' traffic demand. The cells within a cluster are simultaneously in transmission and napping modes, with cluster activation and deactivation, respectively. Our optimization framework accounts for the coupling relation among cells due to the mutual interference. Thus, the users' achievable rates in a cell depend on the cluster composition. On the theoretical side, we provide mathematical formulation and structural characterization for the energy-efficient cell clustering and scheduling optimization problem, and prove its NP hardness. On the algorithmic side, we first show how column generation facilitates problem solving, and then present our notion of local enumeration as a flexible and effective means for dealing with the trade-off between optimality and the combinatorial nature of cluster formation, as well as for the purpose of gauging the deviation from optimality. Numerical results demonstrate that our solutions achieve more than 60% energy saving over existing schemes, and that the solutions we obtain are within a few percent of deviation from global optimum.Comment: Revision, IEEE Transactions on Wireless Communication