In this paper, the reliable routing design problem is investigated in predictable wireless networks over unreliable links. The predictable wireless networks are described as a sequence of static graphs, and then modeled as a space-time graph. The reliable routing design problem on the space-time graph is defined as a bi-objective optimization problem. The aim of the new routing design problem is to find a routing path with the maximum routing reliability and the minimum routing cost. Next, a hierarchical shortest routing algorithm is proposed to find the feasible routing path. Simulation results validate the effectiveness of the proposed routing algorithm.

Caching content in devices and sharing content via device-to-device (D2D) communications is a promising way to offload the cellular data traffic. In fact, the distribution of caching content has a direct effect on the behavior of D2D communications and thus the results of content sharing. On the other hand, the behavior of D2D communications decides whether the cached content can be shared successfully. In other words, there is an interaction between content caching and D2D communications. Moreover, content caching is usually operated in a slow timescale span (e.g, a half hour), while the communication behavior should be performed in a fast timescale span (e.g, several milliseconds), i.e., channel coherence time, owing to the variable nature of wireless channels. Therefore, it is essential to study the channel-aware content caching and sharing problem under two timescale. In this paper, we formulate the problem as a stochastic mixed- integer nonlinear programming (SMINLP), and then approximate the problem as a mixed-integer nonlinear programming. Subsequently, a heuristic algorithm is proposed to handle the approximated problem. Simulation results show that the proposed scheme is more efficient in traffic offloading than that without considering the interactions under two timescale.

Caching content in devices and sharing content via device-to- device (D2D) communications can help reduce cellular data traffic. However, the content caching in devices will reshape the way the conventional D2D communications work, which has not been fully understood. Therefore, we explore the coupling relationship of content caching and sharing in this paper. Par- ticularly, we first propose a concept of content-topology and give its corresponding graph model, which reveals the relationship among devices, content caching, and D2D links. Subsequently, a heuristic algorithm is proposed to find a content-topology, where the content caching among devices and the link activations for content sharing are well matched. Simulation results show that the scheme based on content- topology outperforms the existing algorithms in terms of the amount of offloaded traffic, the number of link activation, and link efficiency.

Content caching at base stations (BSs) is a promising technique for future wireless networks by reducing network traffic and alleviating server bottleneck. However, in practice, the content popularity distribution may change with spatio-temporal variation but be unknown for BSs, which is an intractable obstacle for efficient caching strategy design. In this paper, considering unknown popularity distribution, we explore the content caching problem by jointly optimizing the content caching in cooperative BSs, content sharing among BSs, and cost of content retrieving. We tackle the problem from a multiarmed bandit learning perspective, where the learning of the popularity distribution is incorporated with the content caching and sharing process. Specifically, we first propose a centralized algorithm by employing a semidefinite relaxation approach, and we prove that this centralized algorithm learns efficient caching by deriving a sub-linear learning regret bound. To further reduce computational complexity, we propose a distributed algorithm based on alternating direction method of multipliers, where each BS only solves their own problems by exchanging local information with neighbor BSs. Extensive simulation results show the effectiveness of the proposed algorithms in terms of learning content popularity distributions of individual BSs, offloading traffic from the content server, and reducing cost of content retrieving.

In this letter, we investigate the fundamental tradeoff between rate and energy for sparse code multiple access (SCMA) networks with wireless power transfer. A weighted rate and energy maximization problem by jointly considering power allocation, codebook assignment, and power splitting, is formulated. To solve the hard problem, an iterative algorithm based on the univariate search technique is proposed, which has good performance with low complexity. Specifically, we analyze the special structure of the problem and exploit it to obtain the optimal power splitting ratio and resource allocation strategy when one of them is fixed. Simulation results indicate that our algorithm achieves a better rate-energy tradeoff compared to other schemes.

In wireless networks, the technique of caching contents cooperatively in user equipments (UEs) and base stations (BSs) enables to improve the performance of data access. In this paper, we consider cluster based cooperative device-to-device (D2D) caching enabled network and formulate the caching problem to minimize content retrieving delay. To achieve this, we develop a content caching and replacement scheme by considering the limited storage capacity of UEs, content popularity, and content access process in the network. As a result, our scheme has shown the minimal delay by caching popular contents on UEs and BS with delivering requested contents at smaller average request hops. Moreover, we evaluate our approach with other caching schemes based on parameters as the number of UEs joining the cluster, content popularity and the number of edge UE in a cluster. Simulation results show that the proposed caching scheme significantly outperforms the other schemes.

To cater for the exploding growth of video traffic, small cell base stations (SBSs) and deviceto- device-enabled caching and delivery have been regarded as promising techniques for future wireless networks. In this article, we design a proximity communications enhanced multilayer caching and delivery architecture. Then merits possessed by the proposed architecture are highlighted, and challenges and open issues are comprehensively presented. Specifically, we shed light on the trade-offs between key performance indicators (e.g., hit ratio, latency, and coverage) and operation costs (e.g., device storage space, wireless bandwidth, and device battery life), and then clarify fundamental coupling between content caching and delivery. To further verify the effectiveness of the cooperation among SBSs and user equipments, we propose a distributed content caching and delivery strategy, jointly considering popularity distribution, diverse storage capability, and user mobility. Simulation results demonstrate that the proposed strategy can significantly lower the content retrieval latency and reduce the traffic flowing to core networks. Furthermore, design details of the experimental testbed are presented, and the validity of our developed strategy is verified.

In this paper, we address the problem of power consumption minimization in Heterogeneous networks (HetNets) of China Mobile by implementing dynamic base stations (BSs) switching operation. Particularly, considering the minimal rate requirements of users as well as the realistic power consumption model of BSs, we formulate the problem as an integer linear programming which is NP-complete. Then, to efficiently solve this problem, the Power Efficient Base Station Operation with User Association scheme (PEBUA) and Adaptive Multi-cell Coordination Algorithm for Energy Saving (AMCES) have been developed, which can be efficiently adopted in different network conditions, respectively. Simulation results verify the validity of our analysis and additionally, compared with the existing method in practice network operation, show the effectiveness of the proposed schemes. It should be noted that both of the proposed algorithms can be applied in real HetNets to save the overall power consumption without decreasing users' traffic rates, which makes our study more feasible.

In this paper, by jointly considering subchannels, power, and Modulation and Coding Scheme (MCS) allocation, we address the sum-rate maximization problem in OFDMA downlink systems. We formulate the problem as an integer linear programming (ILP), which maximizes the system sum-rate subject to the minimum rate requirements of users and total transmit power constraint of base station. To solve the formulation with low complexity, we propose a two-level iterative Subchannels, Power, and MCS allocation Algorithm (SPMA) by exploiting Tabu Search (TS). At each iteration, the SPMA firstly assigns MCS to users and then allocates subchannels and power based on a SubChannels and Power allocation Algorithm (SCPA). Particularly, the SCPA maximizes the system sum-rate by first satisfying the minimum rate requirements with the least transmit power. Simulation results show that the SPMA outperforms the existing algorithms in terms of sum-rate and average rate per user, as well as demonstrate that the sum-rate is distributed flexibly among users in instantaneous channel conditions with the SPMA.