Multi-cell Joint Transmission Research Articles

Energy-efficient cluster division for multi-cell joint transmission technology

Coordinated Multi-Point (CoMP) is an effective way to improve user performance in next-generation wireless cellular networks, such as 3GPP LTE-Advanced(LTE-A). The base station cooperation can reduce interference, and increase the signal to interference and noise ratio (SINR) of cell-edge users and improve the system capacity. However, the base station cooperation also adds additional power consumption for signal processing and sharing information through back-haul links between cooperative base stations. As such, CoMP may potentially consume more energy. This paper studies such energy consumption issue in CoMP, presents a semi-dynamic CoMP cluster division algorithm based on energy efficiency (SCCD-EE) that can effectively adapt to users' real-time interference, and employs the idea of Maximal Independent Set (MIS) to solve the problem of cluster overlapping. To verify the feasibility of the proposed algorithm, this paper performs comprehensive evaluations in terms of energy efficiency and system capacity. The simulation results show that the proposed semi-dynamic cluster division algorithm can not only improve the system capacity and the quality of service (QoS) of cell-edge users, but also achieve higher network energy efficiency compared with static cluster methods and Non-CoMP approaches. Copyright © 2016 John Wiley & Sons, Ltd.

Joint Precoding and Load Balancing Optimization for Energy-Efficient Heterogeneous Networks

This paper considers a downlink heterogeneous network, where different types of multiantenna base stations (BSs) communicate with a number of single-antenna users. Multiple BSs can serve the users by spatial multiflow transmission techniques. Assuming imperfect channel state information at both BSs and users, the precoding, load balancing, and BS operation mode are jointly optimized for improving the network energy efficiency. We minimize the weighted total power consumption while satisfying quality-of-service constraints at the users. This problem is nonconvex, but we prove that for each BS mode combination, the considered problem has a hidden convexity structure. Thus, the optimal solution is obtained by an exhaustive search over all possible BS mode combinations. Furthermore, by iterative convex approximations of the nonconvex objective function, a heuristic algorithm is proposed to obtain a suboptimal solution of low complexity. We show that although multicell joint transmission is allowed, in most cases, it is optimal for each user to be served by a single BS. The optimal BS association condition is parameterized, which reveals how it is impacted by different system parameters. Simulation results indicate that putting a BS into sleep mode by proper load balancing is an important solution for energy savings.

Distributed Pre-Coder Design for Multi-Cell Joint Transmission with Interference Controlling

In coordinated multi-cell communication, inter-cell interference (ICI) is one key factor limiting the performance of the networks, many solutions are proposed to overcome this problem, such as inter-cell interference nullification (INFN) and signal-to-leakage ratio maximization (SLRM). In this paper, one new pre-coding method is proposed from the perspective of interference controlling (INFC). This method realizes the merits of INFN and SLRM, and can flexible control interference level of networks so that it satisfies a preassigned level. Numerical simulation shows that INFC is more suitable for the multi-cell joint transmission than INFN and SLRM.

On multicell cooperative transmission in backhaul-constrained cellular systems

Recent work has shown that multicell cooperative signal processing in cellular networks can significantly increase system capacity and fairness. For example, multicell joint transmission and joint detection can be performed to combat intercell interference, often mentioned in the context of distributed antenna systems. Most publications in this field assume that an infinite amount of information can be exchanged between the cooperating base stations, neglecting the main downside of such systems, namely, the need for an additional network backhaul. In recent publications, we have thus proposed an optimization framework and algorithm that applies multicell signal processing to only a carefully selected subset of users for cellular systems with a strongly constrained backhaul. In this paper, we consider the cellular downlink and provide a comprehensive summary and extension of our previous and current work. We compare the performance obtained through centralized or decentralized optimization approaches, or through optimal or suboptimal calculation of precoding matrices, and identify reasonable performance–complexity trade-offs. It is shown that even low-complexity optimization approaches for cellular systems with a strongly constrained backhaul can yield major performance improvements over conventional systems.