Dongdong Jiang

Analysis and Optimization of Caching and Multicasting in Large-Scale Cache-Enabled Wireless Networks

Caching and multicasting at base stations are two promising approaches to supporting massive content delivery over wireless networks. However, existing analysis and designs do not fully explore and exploit the potential advantages of the two approaches. In this paper, we consider the analysis and optimization of caching and multicasting in a large-scale cache-enabled wireless network. We propose a random caching and multicasting design. By carefully handling different types of interferers and adopting appropriate approximations, we derive a tractable expression for the successful transmission probability in the general region, utilizing tools from stochastic geometry. We also obtain a closed-form expression for the successful transmission probability in the high signal-to-noise ratio (SNR) and user density region. Then, we consider the successful transmission probability maximization, which is a very complex nonconvex problem in general. Using optimization techniques, we develop an iterative numerical algorithm to obtain a local optimal caching and multicasting design in the general region. To reduce complexity and maintain superior performance, we also derive an asymptotically optimal caching and multicasting design in the asymptotic region, based on a two-stage optimization framework. Finally, numerical simulations show that the asymptotically optimal design achieves a significant gain in successful transmission probability over some baseline schemes in the general region.

Analysis and Optimization of Caching and Multicasting in Large-Scale Cache-Enabled Heterogeneous Wireless Networks

Heterogeneous wireless networks (HetNets) provide a powerful approach to meeting the dramatic mobile traffic growth, but also impose a significant challenge on backhaul. Caching and multicasting at macro and pico base stations (BSs) are two promising methods to support massive content delivery and reduce backhaul load in HetNets. In this paper, we jointly consider caching and multicasting in a large-scale cache-enabled HetNet with backhaul constraints. We propose a hybrid caching design consisting of identical caching in the macro-tier and random caching in the pico-tier, and a corresponding multicasting design. By carefully handling different types of interferers and adopting appropriate approximations, we derive tractable expressions for the successful transmission probability in the general signal-to-noise ratio (SNR) and user density region as well as the high SNR and user density region, utilizing tools from stochastic geometry. Then, we consider the successful transmission probability maximization by optimizing design parameters, which is a very challenging mixed discrete-continuous optimization problem. By exploring structural properties, we obtain a near optimal solution with superior performance and manageable complexity. This solution achieves better performance in the general region than any asymptotically optimal solution, under a mild condition. The analysis and optimization results provide valuable design insights for practical cache-enabled HetNets.

User-Centric Interference Nulling in Downlink Multi-Antenna Heterogeneous Networks

Heterogeneous networks (HetNets) have strong interference due to spectrum reuse. This affects the signal-to-interference ratio (SIR) of each user, and hence is one of the limiting factors of network performance. However, in previous works, interference management approaches in HetNets are mainly based on interference level, and thus cannot effectively utilize the limited resource to improve network performance. In this paper, we propose a user-centric interference nulling (IN) scheme in downlink two-tier HetNets to improve network performance by improving each users SIR. This scheme has three design parameters: the maximum degree of freedom for IN (i.e., maximum IN DoF), and the IN thresholds for the macro and pico users, respectively. Using tools from stochastic geometry, we first obtain a tractable expression of the coverage (equivalently outage) probability. Then, we characterize the asymptotic behavior of the outage probability in the high reliability regime. The asymptotic results show that the maximum IN DoF can affect the order gain of the asymptotic outage probability, while the IN thresholds only affect the coefficient of the asymptotic outage probability. Moreover, we show that the IN scheme can linearly improve the outage performance, and characterize the optimal maximum IN DoF which minimizes the asymptotic outage probability.

Partition-Based Caching in Large-Scale SIC-Enabled Wireless Networks

Existing designs for content dissemination do not fully explore and exploit potential caching and computation capabilities in advanced wireless networks. In this paper, we propose two partition-based caching designs, i.e., a coded caching design based on random linear network coding and an uncoded caching design. We consider the analysis and optimization of the two caching designs in a large-scale successive interference cancelation (SIC)-enabled wireless network. First, under each caching design, by utilizing tools from stochastic geometry, we derive a tractable expression for the successful transmission probability in the general file size regime. We also derive closed-form expressions in the small and large file size regimes, respectively. Then, under each caching design, we consider the successful transmission probability maximization in the general file size regime, which is an NP-hard problem. By exploring structural properties, we obtain a near optimal solution with 1/2 approximation guarantee and polynomial complexity. We also obtain closed-form asymptotically optimal solutions. The analysis and optimization results show the advantage of the coded caching design over the uncoded caching design, and reveal the impact of caching and SIC capabilities. Finally, we numerically show that the two proposed caching designs achieve significant performance gains over some baseline caching designs.

Network coding-based caching in large-scale SIC-enabled wireless networks

Network coding-based caching at base stations (BSs) is a promising caching approach to support massive content delivery over wireless networks. However, existing network coding-based caching designs do not fully explore and exploit the potential advantages. In this paper, we consider the analysis and optimization of a random linear network coding-based caching design in large-scale successive interference cancelation (SIC)-enabled wireless networks. By utilizing tools from stochastic geometry, we derive a tractable expression for the successful transmission probability in the general file size regime. To further obtain design insights, we also derive closed-form expressions for the successful transmission probability in the small and large file size regimes, respectively. Then, we consider the successful transmission probability maximization by optimizing a design parameter, which is a complex discrete optimization problem. We propose a two-stage optimization framework and obtain a near optimal solution with superior performance and manageable complexity. The analysis and optimization results provide valuable design insights for practical cache and SIC enabled wireless networks. Finally, by numerical results, we show that the proposed near optimal caching design achieves a significant performance gain over some baseline caching designs.

Caching and Multicasting in Large-Scale Cache-Enabled Heterogeneous Wireless Networks

Heterogeneous wireless networks (HetNets) provide a powerful approach to meet the dramatic mobile traffic growth, but also impose a significant challenge on backhaul. Caching and multicasting at macro and pico base stations (BSs) are two promising methods to support massive content delivery and reduce backhaul load in HetNets. In this paper, we jointly consider caching and multicasting in a large-scale cache-enabled HetNet with backhaul constraints. We propose a hybrid caching design to provide high spatial file diversity and a corresponding multicasting design for efficient content dissemination. By carefully handling different types of interferers, we derive tractable expressions for the successful transmission probability in the general signal-to-noise ratio (SNR) and user density region as well as the high SNR and user density region, utilizing tools from stochastic geometry. Then, we consider the successful transmission probability maximization by optimizing the design parameters, which is a very challenging mixed discrete-continuous optimization problem. By exploring the structural properties, we obtain a near optimal solution with superior performance and manageable (polynomial) complexity, based on a two-step optimization framework. The analysis and optimization results provide valuable design insights for practical cache-enabled HetNets.