Adaptive inter-cell time-domain resource partitioning schemes for multi-cell OFDMA networks

Abstract

To achieve high network system capacity, 4G cellular standards are targeting an aggressive spectrum reuse (frequency reuse 1) approach, which unfortunately results in severe performance degradation for cell edge users owing to the increased inter-cell interference (ICI). Furthermore, this phenomenon becomes more critical when the number of base stations (BSs) is increased to enhance the spatial capacity for a given service area. Therefore, effective interference coordination among BSs is essential to attain the full potential gain of multi-cell OFDMA networks and provide ubiquitous user experiences throughout the network. Motivated by this observation, in this thesis we first focus on an inter-cell time-domain resource partitioning that adapts to time varying user distribution and traffic loads for multi-cell OFDMA networks. We propose an adaptive fractional time reuse (FTR) scheme that combines reuse 1, soft FTR, and an inter-cell time-domain resource partitioning algorithm in conjunction with intra-cell user scheduling to maximize the network-wide performance. Through intensive simulations, we show that the proposed adaptive FTR significantly improves the 5th percentile average throughput while sustaining the geometric average throughput. Next, we study a technique that improves the network-wide performance by jointly considering cross-tier and intra-tier interference under heterogeneous multi-cell OFDMA networks. We propose an enhanced FTR scheme that adaptively combines reuse 1, soft time reuse 3, and nearly muted resource partitions for both macrocells and picocells. We also propose a unified inter-cell resource partitioning algorithm considering overall performance maximization and inter-cell/cross-tier fairness under time varying users` channel status as well as traffic loads. Extensive simulations show that the proposed enhanced FTR enhances the geometric average throughput, the 5th percentile average throughput, and fairness under various traffic loads among macrocells and picocells. Finally, we focus on a quality of experience (QoE) aware resource allocation that considers users` time varying channel status and heterogeneous service requirements in multi-cell OFDMA networks. We propose a QoE-based proportional fair (PF) scheduling considering the tradeoff between maximizing QoE and guaranteeing fairness among users. Our utility function is based on the mean opinion score (MOS) model reflecting the application-specific characteristics. We introduce a Bezier curve based continuously differentiable MOS model instead of using the conventional bounded logarithmic MOS model which is generally non-concave. Then, we propose a utility function, which is proven to be concave, for QoE provision to achieve the global optimality with opportunistic gradient scheduling, which can be easily incorporated with the proposed adaptive FTR for ICI coordination. Simulation results show that our proposed technique significantly improves the network-wide users` average QoE while sustaining the edge users` performance, e.g., the 5th percentile users` QoE.