Cooperative Caching Placement in Cache-Enabled D2D Underlaid Cellular Network

Wirelessly powered backscatter communication (WP-BackCom) enables battery-free Internet of Things (IoT) nodes to passively modulate and backscatter information on the energy signals transmitted by power beacons (PBs) and to harvest energy for realizing energy self-sustainability. It has been deemed a promising solution for the large-scale deployment of IoT nodes. In this paper, we exploit stochastic geometry (SG) to develop a tractable framework to evaluate the successful transmission probability in WP-BackCom while considering the imperfect successive interference cancellation (SIC) at each gateway (GW) and the non-linear energy harvesting (EH) model and energy-causality constraint at each backscatter user (BU). The successful transmission probability is defined as the probability for the event that not only the BU can harvest sufficient power from PBs for sustaining its operation but also the backscattered information can be successfully decoded by the GW. We derive the active probability into a closed form and then obtain the successful transmission probability based on the random spectrum access (RSA) policy. The closed-form expression for the successful transmission probability is derived under three special cases. We also devise a closed-form expression for the sub-optimal reflection coefficient to obtain a sub-optimal successful transmission probability. The analysis reveals that the sub-optimal reflection coefficient increases with the SIC coefficient. Numerical simulations validate the correctness of the above theoretical derivations and examine the impacts of various parameters on the successful transmission probability.

To improve signal-to-interference ratio (SIR) and make better use of file diversity provided by random caching, we consider the maximal ratio combining (MRC) receiver at each user in a large-scale cache- enabled single-input multi-output (SIMO) network. First, by utilizing tools from stochastic geometry, we derive a tractable expression and closed-form upper and lower bounds for the successful transmission probability in the general SIR threshold regime. We also derive a closed-form expression for the asymptotic outage probability in the low SIR threshold regime. The analytical results reveal that the successful transmission probability increases with the number of receive antennas M at each user in the general SIR threshold regime, the coefficient of the asymptotic outage probability decreases with M and the order gain of the asymptotic outage probability does not depend on M. Then, we consider the successful transmission probability maximization. In the general SIR threshold regime, we consider the maximization of the tight upper bound on the successful transmission probability by optimizing the caching distribution, which is a non-convex problem. We obtain a stationary point, by solving an equivalent difference of convex (DC) programming problem using concave-convex procedure (CCCP). We also obtain a closed-form asymptotically optimal solution in the low SIR threshold regime. The optimization results indicate that files of higher popularity get more storage resources, and the caching distribution becomes more flat when M is larger.

Caching and multicasting at base stations are two promising approaches to support 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 scheme with a design parameter. 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 non-convex 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-step 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.

To improve signal-to-interference ratio (SIR) and make better use of file diversity provided by random caching, we consider two types of linear receivers, i.e., maximal ratio combining (MRC) receiver and partial zero forcing (PZF) receiver, at users in a large-scale cache-enabled single-input multi-output network. First, for each receiver, by utilizing tools from stochastic geometry, we derive a tractable expression and a tight upper bound for the successful transmission probability (STP). In the case of the MRC receiver, we also derive a closed-form expression for the asymptotic outage probability in the low SIR threshold regime. Then, for each receiver, we maximize the STP. In the case of the MRC receiver, we consider the maximization of the tight upper bound on the STP by optimizing the caching probabilities, which is a non-convex problem. We obtain a stationary point, by solving an equivalent difference of convex programming problem using concave-convex procedure. We also obtain a closed-form asymptotically optimal solution in the low SIR threshold regime. In the case of the PZF receiver, we consider the maximization of the tight upper bound on the STP by optimizing the caching probabilities and the degrees of freedom allocation (for boosting signal power and canceling interference), which is a mixed discrete-continuous problem. Based on structural properties, we obtain a low-complexity near optimal solution by using an alternating optimization approach. The analysis and optimization results reveal the impact of antenna resource at users on random caching.

On the successful transmission probability of cooperative cognitive radio ad hoc 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 and adopting appropriate approximations, 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, 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 successfully transform the original optimization problem into a Multiple-Choice Knapsack Problem (MCKP), and 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, by numerical results, we show that the two proposed caching designs achieve significant performance gains over some baseline caching designs.

Efficient dissemination of videos is an important problem for mobile telecom carriers. In this paper, to facilitate massive video dissemination, we study joint caching and multicasting for multi-quality videos encoded using two video encoding techniques, namely, scalable video coding (SVC) and HEVC or H.264 as in dynamic adaptive streaming over HTTP (DASH) respectively, in a large-scale wireless network. First, for each type of video, we propose a random caching and multicasting scheme, carefully reflecting the relationship between layers of an SVC-based video or descriptions of a DASH-based video. Then, for each type of video, we derive tractable expressions for the successful transmission probability in the general and high user density regions, respectively, utilizing tools from stochastic geometry. The analytical results reveal that in the high user density region, the marginal increase of the successful transmission probability with respect to the caching probability of a video with a certain quality reduces when the caching probability increases. Next, for each type of video, we consider the maximization of the successful transmission probability in the high user density region, which is a convex problem with an exceedingly large number of optimization variables. We propose a two-stage optimization method to obtain a low-complexity near-optimal solution by solving a relaxed convex problem and a related packing problem. The optimization results reveal the impact of the caching gain of a layer for an SVC-based video or a description for a DASH-based video on its caching probability. Finally, we show that the proposed solutions for SVC-based and DASH-based videos achieve significant performance gains over baseline schemes in the general and high user density regions, and demonstrate their respective operating regions, using numerical results based on real video sequences.

In this paper, the edge caching optimization problem in fog radio access networks (F-RANs) is investigated. Considering that fog access points (F-APs) can offer cooperation gain by jointly transmitting the same file or content diversity gain by concurrently transmitting the coded subfiles, we propose to use both joint transmission (JT) strategy and parallel transmission (PT) strategy to serve users. Using tools from stochastic geometry, we first derive the expressions of successful transmission probability (STP) under different transmission strategies, and then derive the expressions of fractional offloaded traffic (FOT) and delay. We further formulate the corresponding edge caching optimization problem to maximize the STP, FOT or minimize the delay. Considering the NP-hard property of the above optimization problem, we propose an improved fruit fly optimization (FFO) based edge caching scheme, which utilizes the dynamic search step to avoid pre-mature convergence. Furthermore, we theoretically analyze the convergence and global optimality of our proposed scheme. Numerical results show that a significant performance gain is achieved by using our proposed edge caching scheme compared with the baseline schemes.

Wireless body area networks (WBANs) are expected to influence the traditional medical model by assisting caretakers with health telemonitoring. Within WBANs, the transmit power of the nodes should be as small as possible owing to their limited energy capacity but should be sufficiently large to guarantee the quality of the signal at the receiving nodes. When multiple WBANs coexist in a small area, the communication reliability and overall throughput can be seriously affected due to resource competition and interference. We show that the total network throughput largely depends on the WBANs distribution density (λp), transmit power of their nodes (Pt), and their carrier-sensing threshold (γ). Using stochastic geometry, a joint carrier-sensing threshold and power control strategy is proposed to meet the demand of coexisting WBANs based on the IEEE 802.15.4 standard. Given different network distributions and carrier-sensing thresholds, the proposed strategy derives a minimum transmit power according to varying surrounding environment. We obtain expressions for transmission success probability and throughput adopting this strategy. Using numerical examples, we show that joint carrier-sensing thresholds and transmit power strategy can effectively improve the overall system throughput and reduce interference. Additionally, this paper studies the effects of a guard zone on the throughput using a Matern hard-core point process (HCPP) type II model. Theoretical analysis and simulation results show that the HCPP model can increase the success probability and throughput of networks.

This paper investigates the impact of the polarization on the achievable throughput and the probability of successful transmission in the cellular network architectures. A channel link model is proposed in the specific case of Rayleigh-faded communication links. More precisely, we propose a closed-form expression for the link probability of success with respect to the topology of the deployment and the channel characteristics. The per-node throughput is analyzed and the gain achieved by using two different polarization modes is discussed. It turns out that, for uniform random placement of the nodes in a scenario where two cellular networks are deployed on a same location, the diversity of polarization ensures that the networks can be operate as if they were disjoint.

The customized fifth generation (5G) private net-work is one of the most promising solutions to deal with the challenges of various flexible and differentiated application demands. Before customizing the 5G private network, network traffic analysis is necessary to be conducted. This article first introduces three typical 5G private network deployment modes and the typical application scenarios. Due to the correlation between spatial traffic and temporal traffic in 5G private net-works, characterizing both spatial randomness and temporal randomness is challenging. Thus, a spatiotemporal traffic analytical framework based on stochastic geometry and queueing theory is introduced in this article. This spatiotemporal traffic analytical framework helps guide the traffic analysis of 5G private networks and the deployment of 5G private networks. A case study of the spatiotemporal traffic analysis on a 5G private network is illustrated, where the metrics such as successful transmission probability, data transmission rate, and time delay are analyzed.

Recent studies show that platoon is can substantially improve traffic safety and efficiency. In this paper, resource partition and message transmission schemes with geo-based resources allocation (GRA) for inter-platoon communication are proposed. Based on that, received signal-to-interference-plus-noise ratio (SINR) is analyzed. The expressions of success transmission probability and average energy efficiency (EE) are obtained by using the tool of stochastic geometry. In particular, the optimum transmit power that fulfills a given minimum success probability constraint while maximizing the average EE is calculated. Mathematical results show both success probability and average EE can be improved by adjusting the transmit power. All the analytical results are validated through extensive Monte Carlo simulations.

Coded caching is able to exploit accumulated cache size in a wireless network by storing fractions of files in each node. In this work, we model, analyze, and optimize coded caching in cache-enabled small-cell networks (SCNs). We first propose a content delivery framework for coded caching, where multiple small base stations (SBSs) that cache different coded packets of a desired file transmit simultaneously upon a user request and the packets are decoded using successive interference cancellation (SIC)-based receiver. A closed-form expression for the successful transmission probability with SIC receiver in the high signal-to-noise ratio (SNR) region is derived by using stochastic geometry. We next optimize the cache placement to maximize the average fraction of offloaded traffic by the cache-enabled SBSs. The coded cache placement problem is formulated as a multiple-choice knapsack problem (MCKP). By exploiting the analytic properties of the average traffic offload fraction, we propose a greedy but optimal algorithm. Numerical results show our proposed coded caching scheme facilitated by simultaneous transmission and SIC-based receiving significantly outperforms uncoded caching. In addition, the coded caching only needs to split each file into a small number of fragments to approach an ideal performance.

Device‐to‐device (D2D) communication underlaying cellular networks is a promising technology to improve network resource utilization. In D2D‐enabled cellular networks, interference among spectrum‐sharing links is severer than that in traditional cellular networks, which motivates the adoption of interference cancelation (IC) techniques at the receivers. However, to date, how IC can affect the performance of D2D‐enabled cellular networks is still unknown. In this paper, we present an analytical framework for studying the performance of two IC methods, that is, unconditional IC and successive IC, in large‐scale D2D‐enabled cellular networks using the tools from stochastic geometry. To facilitate the interference analysis, we propose an approach of stochastic equivalence of the interference, which converts the two‐tier interference (interference from the cellular tier and D2D tier) to an equivalent single‐tier interference. Based on the proposed stochastic equivalence models, we derive the general expressions for the successful transmission probabilities of both cellular uplinks and D2D links in the networks where unconditional IC and successive IC are respectively applied. We demonstrate how these IC methods affect the network performance using both analytical and numerical results. Copyright © 2016 John Wiley & Sons, Ltd.

We investigate the near-optimal video layer placement in cache-enabled small-cell networks to provide on-demand video services with differential perceptual experiences. By employing scalable video coding, each video file is encoded into multiple layers, which are then stored in the local cache of small-cell base stations (SBSs). Based on the proposed caching scheme, we define the concept of average offloaded traffic (AOT), which quantitatively indicates the total amount of data traffic that can be sourced from the local cache of SBSs. Relying on stochastic geometry, we derive the expression for the successful transmission probability, based on which the closed form of AOT is obtained. Afterwards, under the cache size constraint of each SBS, the AOT maximization problem is formulated. Due to the NP-hard property of this integer programming problem, it is first relaxed into the convex form. Then, a greedy-strategy based heuristic algorithm is proposed, which can yield the near-optimal layer caching indicators. Numerical results validate our derivations and demonstrate that the proposed layer caching scheme outperforms the benchmark in terms of the AOT performance.