A fuzzy Q-learning approach for enhanced intercell interference coordination in LTE-Advanced heterogeneous networks

© 2014 IEEE. Since the transmission power of macro eNodeB (eNB) is higher than pico eNB in long term evolution-advanced heterogeneous network, the coverage area of picocell is small. In order to address the coverage problem, cell range expansion (CRE) technique has been recently proposed. However, CRE can lead to the downlink interference problem on both data and control channels when users are connected to pico eNB. In order to mitigate the downlink interference problem, a new dynamic almost blank subframe (ABS) scheme is proposed in this paper. In this scheme, a fuzzy q-learning approach is used to find the optimum ABS value. Simulation results show that the system performance can be improved through the proposed scheme

A Study about Heterogeneous Network Issues Management based on Enhanced Inter-cell Interference Coordination and Machine Learning Algorithms

Under the circumstance of fast growing demands for mobile data, Heterogeneous Networks (HetNets) has been considered as one of the key technologies to solve 1000 times mobile data challenge in the coming decade. Although the unique multi-tier topology of HetNets has achieved high spectrum efficiency and enhanced Quality of Service (QoS), it also brings a series of critical issues. In this thesis, we present an investigation on understanding the cause of HetNets challenges and provide a research on state of arts techniques to solve three major issues: interference, offloading and handover. The first issue addressed in the thesis is the cross-tier interference of HetNets. We introduce Almost Blank Subframes (ABS) to free small cell UEs from cross-tier interference, which is the key technique of enhanced Inter-Cell Interference Coordination (eICIC). Nash Bargain Solution (NBS) is applied to optimize ABS ratio and UE partition. Furthermore, we propose a power based multi-layer NBS Algorithm to obtain optimal parameters of Further enhanced Inter-cell Interference Coordination (FeICIC), which significantly improve macrocell efficiency compared to eICIC. This algorithm not only introduces dynamic power ratio but also defined opportunity cost for each layer instead of conventional zero-cost partial fairness. Simulation results show the performance of proposed algorithm may achieve up to 31.4% user throughput gain compared to eICIC and fixed power ratio FeICIC. This thesis’ second focusing issue is offloading problem of HetNets. This includes (1) UE offloading from macro cell and (2) small cell backhaul offloading. For first aspect, we have discussed the capability of machine learning algorithms tackling this challenge and propose the User-Based K-means Algorithm (UBKCA). The proposed algorithm establishes a closed loop Self-Organization system on our HetNets scenario to maintain desired offloading factor of 50%, with cell edge user factor 17.5% and CRE bias of 8dB. For second part, we further apply machine learning clustering method to establish cache system, which may achieve up to 70.27% hit-ratio and reduce request latency by 60.21% for Youtube scenario. K-Nearest Neighbouring (KNN) is then applied to predict new users’ content preference and prove our cache system’s suitability. Besides that, we have also proposed a system to predict users’ content preference even if the collected data is not complete. The third part focuses on offloading phase within HetNets. This part detailed discusses CRE’s positive effect on mitigating ping-pong handover during UE offloading, and CRE’s negative effect on increasing cross-tier interference. And then a modified Markov Chain Process is established to map the handover phases for UE to offload from macro cell to small cell and vice versa. The transition probability of MCP has considered both effects of CRE so that the optimal CRE value for HetNets can be achieved, and result for our scenario is 7dB. The combination of CRE and Handover Margin is also discussed

Contributions to Analysis and Mitigation of Cochannel Interference in Cellular Wireless Networks

Cellular wireless networks have become a commodity. We use our cellular devices every day to connect to others, to conduct business, for entertainment. Strong demand for wireless access has made corresponding parts of radio spectrum very valuable. Consequently, network operators and their suppliers are constantly being pressured for its efficient use. Unlike the first and second generation cellular networks, current generations do not therefore separate geographical sites in frequency. This universal frequency reuse, combined with continuously increasing spatial density of the transmitters, leads to challenging interference levels in the network. This dissertation collects several contributions to analysis and mitigation of interference in cellular wireless networks. The contributions are categorized and set in the context of prior art based on key characteristics, then they are treated one by one. The first contribution encompasses dynamic signaling that measures instantaneous interference situations and allows only for such transmissions that do not harm each other excessively. A novel forward signaling approach is introduced as an alternative to traditional reverse signaling. Forward signaling allows the interference management decisions to be done at the receiver, where there is more relevant information available. The second contribution analyzes cross-link interference in heterogeneous networks. Cross-link interference is interference between downlink and uplink transmissions that can appear in time-division duplex (TDD) networks. It is shown that uplink reception of small cells can be disturbed considerably by macrocell downlink transmissions. We proposes an intuitive solution to the problem based on power control. Users in small cells have generally enough power headroom as the distance to the small base station is often short. The third contribution provides an extensive analysis of a specific interference managment method that the Long-Term Evolution (LTE) applies in cochannel heterogeneous deployments. We analyze this so-called time muting using a modern stochastic geometry approach and show that performance of the method strongly depends on residual interference in the muted sections of time. The fourth and last contribution analyzes the impact of interference rank, i.e., number of spatial streams at the interferer, on a beamformed or spatially block coded transmission. It is shown that when the interferer chooses to transmit multiple spatial streams, spreading the power in spatial domain has potential to decrease probability of outage at neighbor receiver, especially if the neighbor transmission uses beamforming