Inter-cell interference coordination in 5G ultra-dense networks

Doctoral Thesis


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The exponentially increasing demand for mobile broadband communications has led to the dense deployment of cellular networks with aggressive frequency reuse patterns. The future Fifth Generation (5G) networks are expected to overcome capacity and throughput challenges by adopting a multi-tier architecture where several low-power Base Stations (BSs) are deployed within the coverage area of the macro cell. Hence, Inter-Cell Interference (ICI) caused by the simultaneous usage of the same spectrum in different cells creates severe problems. ICI reduces system throughput and network capacity, and has a negative impact on cell-edge users and overall system performance. Therefore, effective interference coordination techniques are required, especially, for user-to-cell association and resource allocation to mitigate severe impact of ICI on system performance in 5G heterogeneous networks (HetNets). This is to improve Quality of Service (QoS) and maximize system throughput arising from the deployment of small cell overlay on macro BSs in heterogeneous cellular networks, which creates traffic load imbalance due to varying transmit power of different BSs in the downlink. In this research, a cell association scheme based on Cell Range Expansion (CRE), integrated with power control techniques is proposed. Simulation results are presented to show the ability of this technique to protect offloaded users from severe ICI and maximize throughput while achieving desirable QoS and load balancing for users of different tiers. With the advancement of information and computer technology, the envisioned 5G wireless communication is expected to encompass an unprecedented heterogeneous and ultra-dense communication environment. Vehicular communications play a vital role in 5G wireless network and have been widely studied recently due to its great potential to ensure reliability and support intelligent transportation and various safety applications. This research therefore exploits the tractability of stochastic geometry to analyze the coverage of urban vehicular networks, by deriving a closed-form expression to maximize the ergodic capacity of cellular users (CUEs) and mitigate interference, taking into consideration the QoS requirements of both vehicle-to-vehicle (V2V) and vehicleto-infrastructure (V2I) links. Consequently, the latency and reliability requirements of V2V/V2I links are formulated as optimization constraints, involving joint power allocation and spectrum sharing (PASS), taking into account the slow varying and large scale channel state information (CSI) measurements. Due to non-convex nature of the problem, the optimization is transformed into sub-optimal convex equivalence, while a low complexity Algorithm that yields optimal resource allocation is then designed to solve it. Simulation results are used to show enhanced performance in our approach compared to related works. Finally, the upsurge in the number of connected devices, such as smart cars, to the envisioned 5G technology is expected to pose high capacity and data rate demands on the network. The conventional access techniques (i.e., CDMA, TDMA and OFDMA) may not meet stringent requirements, such as ultra-low latency, high reliability, improved spectral efficiency and massive device connectivity. This work further investigates non-orthogonal multiple access (NOMA) technique as promising solution to improve spectral efficiency and reduce interference in 5G Ultra Dense Network (UDN). The NOMA scheme is combined with two promising capacity and bandwidth enhancement techniques - massive multiple input and multiple output (MIMO) and carrier aggregation (CA), for overall network performance. In particular, for the proposed novel NOMA-CA approach, we justify the importance of maintaining green communication as a key requirement for 5G with Energy Efficiency (EE) analysis. Firstly, a proportional fairness scheduler is used to perform resource allocation and maintain fairness among users based on their channel condition. Secondly, an optimization problem to maximize the EE weighted-sum under joint power and bandwidth allocation on each aggregated component carrier (CC) is formulated. Conventionally, the formulated optimization is transformed from non-convex to convex problem. An iteratively adaptive Algorithm is then developed to find optimal solution for the problem. Simulation results show better improvement in EE and sum rate compared to the traditional OMA scheme.