Autonomous Algorithms for Centralized and Distributed Interference Coordination: A Virtual Layer Based Approach

Interference mitigation techniques are essential for improving the performance of interference limited wireless networks. In this paper, we introduce novel interference mitigation schemes for wireless cellular networks with space division multiple access (SDMA). The schemes are based on a virtual layer that captures and simplifies the complicated interference situation in the network and that is used for power control. We show how optimization in this virtual layer generates gradually adapting power control settings that lead to autonomous interference minimization. Thereby, the granularity of control ranges from controlling frequency sub-band power via controlling the power on a per-beam basis, to a granularity of only enforcing average power constraints per beam. In conjunction with suitable short-term scheduling, our algorithms gradually steer the network towards a higher utility. We use extensive system-level simulations to compare three distributed algorithms and evaluate their applicability for different user mobility assumptions. In particular, it turns out that larger gains can be achieved by imposing average power constraints and allowing opportunistic scheduling instantaneously, rather than controlling the power in a strict way. Furthermore, we introduce a centralized algorithm, which directly solves the underlying optimization and shows fast convergence, as a performance benchmark for the distributed solutions. Moreover, we investigate the deviation from global optimality by comparing to a branch-and-bound-based solution.Comment: revised versio

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Recent advances in radio resource management for heterogeneous LTE/LTE-A networks

As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies

Scheduling heuristic for reduced complexity of coordinated beamforming in large multi-carrier heterogeneous wireless networks

The research and development of wireless communication systems is often based on relatively simple models of the network topology, the radio channel and the radio propagation. This is considered to be mostly appropriate, as only under these conditions the complex technical problems in this field can be fully solved to their theoretical boundaries. However, it can also be the case that algorithms or concepts created under simplified assumptions perform in a significantly different way, when they are applied in more realistic scenarios. This Thesis presents research work which can be seen as a step towards extending the existing research on Coordinated Beamforming to a complex network scenario, i.e. to a large-scale heterogeneous multi-carrier network. For this purpose, a complex simulation framework has been developed. This is used to analyse the significant implications the conditions in a complex network can have on the achievable performance gains. In more detail, the out of cluster interference and the number of mobile stations are identified as factors which heavily influence the performance. This knowledge is then used to design a novel scheduling heuristic, designed to be able to adapt to the particular network scenarios and to estimate the extent of the achievable performance gains. Our simulation results show that the new heuristic achieves significant performance gains for a low number of mobile stations (by applying zero forcing precoding) as well as for a high number of mobile stations (by a coordinated resource assignment that intelligently pairs mobile stations when applying maximum ratio transmission). The Thesis also demonstrates that the effect of the out of cluster interference can cause the reduction of the achievable gains. Due to the knowledge of performance limiting factors, the scheduling heuristic is in addition able to realize a trade-off between complexity and performance by excluding transmission parameters from the scheduling process which are not expected to be beneficial