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

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.

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.

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.

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.

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.

On the successful transmission probability of cooperative cognitive radio ad hoc networks

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.

In a cache-enabled D2D underlaid cellular network, cooperation of BS caching and D2D caching can further exploit the limited storage capacity and achieve more efficient wireless resource utilization. In this complex network scenario, the closed form expression for successful transmission probability is firstly derived using stochastic geometry, to measure the proportion of users satisfying the delay guarantee. On this basis, a cooperative caching placement problem is formulated to maximize the successful transmission probability. We prove it can be transformed equivalently into a biconvex problem and then a block coordinate descent based algorithm is proposed. Simulation results demonstrate the performance gain of the proposed cooperative caching placement.

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.

Massive Internet of Things (mIoT) has provided an auspicious opportunity to build powerful and ubiquitous connections that faces a plethora of new challenges, where cellular networks are potential solutions due to their high scalability, reliability, and efficiency. The contention-based random access procedure (RACH) is the first step of connection establishment between IoT devices and Base Stations (BSs) in the cellular-based mIoT network, where modelling the interactions between static properties of physical layer network and dynamic properties of queue evolving in each IoT device are challenging. To tackle this, we provide a novel traffic-aware spatio- temporal model to analyze RACH in cellular-based mIoT networks, where the physical layer network are modelled and analyzed based on stochastic geometry, and the queue evolution are analyzed based on probability theory. For performance evaluation, we derive the exact expressions for the preamble transmission success probabilities of a randomly chosen IoT device with baseline scheme in each time slot. Our derived analytical results are verified by the realistic simulations capturing the evolution of packets in each IoT device.

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.

We consider a centralized network scheme, where all nodes communicate with a base station (BS). The communication happens in a time slotted fashion and the BS has multi-packet reception capability. Assuming that the success probability of transmissions is always 1 (perfect reception), we prove a lower bound on the delay performance for arbitrary policy. We then study the imperfect reception case in which the success probability of transmissions is not always 1. A convex optimization problem is proposed, which can minimize the upper bound on the expected delay of random scheduling (RS). An approximation and a lower bound on the delay of RS are also developed for the case in which the BS can support simultaneous transmission of up to two users. We implement a recently proposed algorithm that separates multiple simultaneous transmissions in a blind fashion, and show that the approximated delays and the delay bounds match the simulation results very well.

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.

In a wireless uplink, collisions occur when two or more wireless users transmit signals at the same time over the same channel. Traditionally, when this happens, the received packets are discarded and retransmissions are required, which is a waste of power and bandwidth. The main contributions of this dissertation include a studyof approaches for collision resolution, i.e., recovery of collided packets, the design of pulse-shape functions that facilitate collision resolution and also the analysis ofpacket delays in a cellular wireless network whose base station has collision resolution capability. In the first part of this dissertation a new scheme, namely ALOHA with Collision Resolution (ALOHA-CR), is proposed, which is a cross-layer approach for highthroughput wireless communications in a cellular uplink scenario. Transmissions occur in a time-slotted ALOHA-type fashion but with an important difference: simultaneous transmissions of two users can be successful. When two users transmit, the collision is resolved by oversampling the collision signal and exploiting independent information about the users that is contained in the signal polyphase components. The performance of ALOHA-CR is demonstrated on the Wireless Open Access Research Platform (WARP) testbed containing five software defined radio (SDR) nodes. The testbed results indicate that ALOHA-CR leads to significant increase in throughput and reduction of service delays as compared to ALOHA. The second part of this dissertation focuses on optimal pulse-shape design for collision resolution. As mentioned above, the collided packets are separated by oversampling the collision signal. Because of oversampling, high correlations can occur between the columns of the virtual multiple-input multiple-output(MIMO) system matrix, which can be detrimental to user separation. A novel pulse-shape waveform design is proposed, which results in low correlation between the columns of the system matrix, while it exploits all available bandwidth as dictated by a spectral mask. In the third part, we study the delay properties of random scheduling (RS) in a cellular wireless network, under the assumption that the base station (BS) has multi-packet reception (MPR) capability. We minimize the expected delay of RS by determining the scheduling probabilities of nodes that will transmit simultaneously. For the perfect reception case, (i.e., when the success probability of transmissions is 1), a lower bound of the delay performance for an arbitrary scheduling policy is provided. The imperfect reception case is also studied and a convex optimization formulation is proposed, which can minimize theupper bound on the expected delay of RS. An approximation and a lower bound on the expected delay of RS are also developed under the assumption that the basestation can support simultaneous transmission of two users.

With the improvement of quality of service requirement and the increase of energy expenditure, integrating caching and energy harvesting (EH) to device-to-device (D2D) communication is a prospective but challenging research. In this paper, we focus on investigating the network performance with stochastic geometry for cache- and EH-enabled D2D cellular network, in which each mobile user (MU) can cache contents from the base station and be charged through EH. Specifically, taking into account the knowledge of the energy states and the requested contents, along with the randomness of content caching, each MU can fetch its requested file via three modes, i.e., self-satisfied, D2D communication and cellular downlink communication. In view of this observation, stochastic geometry is applied to analyze the system transmission model, and from which the content delivery strategies are designed, as well as the cache hit probability and successful transmission probability are characterized under three modes, respectively. Based on the analyzed results, two probabilistic caching strategies with different objectives are further designed to maximize the cache hit probability and the network successful offloading probability. Finally, comprehensive simulations are provided to analyze the effect of different parameters on network performance and verify the superiority of the proposed caching strategies.