Single or Multiple Frames Content Delivery for Next-Generation Networks?

With the successful demonstration of in-band full-duplex (IBFD) transceivers, a new research dimension has been added to wireless networks. This paper proposes a use case of this capability for IBFD self-backhauling heterogeneous networks (HetNets). IBFD self-backhauling in a HetNet refers to IBFD-enabled small cells backhauling themselves with macro cells over the wireless channel. Owing to their IBFD capability, the small cells simultaneously communicate over the access and backhaul links, using the same frequency band. The idea is doubly advantageous, as it obviates the need for fiber backhauling small cells every hundred meters and allows the access spectrum to be reused for backhauling at no extra cost. This paper considers the case of a two-tier cellular network with IBFD-enabled small cells, wirelessly backhauling themselves with conventional macro cells. For clear exposition, the case considered is that of the Frequency Division Duplexing (FDD) network, where within access and backhaul links, the downlink (DL) and uplink are frequency duplexed (f1 , f2 respectively), while the total frequency spectrum used at access and backhaul (f1+f2 ) is the same. Analytical expressions for coverage and average DL rate in such a network are derived using tools from the field of stochastic geometry. It is shown that DL rate in such networks could be close to double that of a conventional TDD/FDD self-backhauling network, at the expense of reduced coverage due to higher interference in IBFD networks. For the proposed IBFD network, the conflicting aspects of increased interference on one side and high spectral efficiency on the other are captured into a mathematical model. The mathematical model introduces an end-to-end joint analysis of backhaul (or fronthaul) and access links, in contrast to the largely available access-centric studies.

Caching at network edges has attracted more and more research interests recently for the purpose of alleviating the network traffic pressure especially in backhaul links and improving user experience. We study Heterogeneous Cellular Caching Networks (HCCNs) consisting of macro cells in which <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> small cell base stations (SBSs) equipped with cache memory operate in conjunction with the macro cell base station (MBS). We provide closed-form expressions of the MBS and SBSs utilization factors and average user-experienced-delay in HCCNs with overlapping coverage regions, considering general traffic models for the request arrivals based on the Independent Reference Model (IRM) and renewal traffic models. Moreover, we propose a novel caching scheme in HCCNs, namely Cooperative Most Popular Caching (CMPC), which outperforms the existing schemes in terms of delay. Subsequently, we present the bandwidth assignment problem aiming to minimize the average user-experienced-delay under stability and cache size constraints in HCCNs with overlapping coverage regions and stochastic request arrivals. Finally, the analytic results are validated through numerical results and real trace-driven experiments.

In this study, the authors adopt the non‐orthogonal multiple access (NOMA) technique to improve the spectrum efficiency in the wireless backhaul networks, whereby the downlink and uplink NOMA techniques are applied for the backhaul and access links, respectively. Due to the coupling between the backhaul and access transmission stages, the transmission power should be carefully allocated in both stages so that the overall throughput can be maximised. They start with the single user equipment (UE) case and consider different scenarios and analyse the tradeoff between the access and backhaul links, and the optimal power allocation solutions are obtained accordingly. They then extend the analysis to the multi‐UE case and formulate the optimal power allocation problem, which is solved using the Lagrangian dual decomposition algorithm. Simulation results demonstrate that the proposed schemes are effective in improving the throughput and outperforms the conventional orthogonal multiple access technique under different network settings.

This paper provides the system performance for the type 1 relay that 3GPP LTE-Advanced supports. Since type 1 relay is operated in half duplex mode to avoid self-interference, the overall relay system performance highly depends on the backhaul link performance and the resource allocation between backhaul and access link. In this paper, we applied the dual-layer beamforming(DLBF) in the backhaul link to increase the backhaul link performance by adopting spatial multiplexing with the multiple relays. Also, we optimized the resource allocation to maximize the relay system performance.

We consider a cache network, where a single server is connected to multiple users via a shared bottleneck link. The server has a set of files, which can be cached by each user in a prefetching phase. In a following delivery phase, each user requests a file and the server delivers user demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the bottleneck link for a given cache size available at each user. We propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we can also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without coordination.

Recently, distributed resource allocation for relay enhanced cellular networks has gained increasing attention. However, it poses a new challenge for the backhaul link scheduling. In this paper, we propose a queue-status-based resource allocation scheme for the backhaul link in a distributed manner in relay enhanced networks. By applying this scheme, the evolved Node B (eNB) adjusts the data rate for each user equipment (UE) in the backhaul link according to its queue status at the relay node (RN). It can guarantee the rate match between the backhaul and access links while minimizing feedback signaling. Simulation results show that the proposed scheme can achieve a good tradeoff between the spectral efficiency and the signaling overhead.

The integrated access and backhaul (IAB) has demonstrated tremendous potential in the fifth-generation (5G) network, acting as an economical and sustainable alternative to conventional fiber-like architectures. Although promising, how to efficiently and effectively allocate bandwidth and power resource to the backhaul and access links is a challenging issue for IAB. In this paper, we propose a novel scheme to jointly allocate the spectrum and transmitting power of the IAB donor and IAB nodes, so as to serve their respective access links and backhaul links. With the objective of maximizing the downlink data rate, we formulate the spectrum allocation and power management as a mix-integer and non-linear programming problem. Then, we propose to use an advanced deep reinforcement learning (DRL), i.e., double deep Q-learning, to achieve an efficient policy for joint spectrum allocation and power management, namely SAPM-DDQN. We perform the proposed SAPM-DDQN in a decentralized manner, which can significantly reduce the transmission overhead, compared to the centralized one. To the best of the authors’ knowledge, this is the first attempt on the joint spectrum allocation and power management in a decentralized manner for IAB, leveraging the property of DRL techniques. The proposed SAPM-DDQN does not require any prior information from other units for optimization, which is suitable for practical deployment. The extensive simulation results are presented to verify the effectiveness of the proposed scheme for joint spectrum allocation and power management.

In this paper, we present Wi-Cache, an SDN (Software Defined Networking) based distributed content caching system in a wireless local area network (WLAN). One way to effectively reduce congestion in the backhaul links of today's IP network is caching videos and non-voice traffic closer to mobile and wireless devices. Cellular base stations and WiFi access points (APs) are the major serving points and the closest network nodes to mobile and wireless devices. WiFi APs are becoming a part of heterogeneous cellular networks (HCNs), and are also present abundantly at homes and workplaces. Therefore, one viable solution to reduce the bandwidth consumption of backhaul links is caching contents in these WiFi APs so that user requests can be served locally. Wi-Cache caches contents on low-cost wireless APs, and delivers them to mobile clients when they are requested. It minimizes the need to fetch contents from remote content servers. It also addresses two major WLAN challenges during content delivery-client mobility and load balancing on WiFi APs. Wi-Cache prototype implementation, and the evaluation of its feasibility and performance is based on Odin, an open source SDN framework for enterprise WLANs.

Caching on the edge has been recognized as an effective solution to tackle the backhaul constraint of network densification. However, most related works ignored user mobility in wireless networks, which is unreasonable under the background of network densification. For a more flexible and context-aware caching decision, the concept of caching on the edge can be extended to mobile edge computing (MEC) that enables computation and storage resources at mobile edge networks. With MEC servers deployed on base stations, a huge amount of collected radio access network context data can be analyzed and utilized to render a caching scheme adaptive to user’s context-aware information. In this regard, a novel mobility-aware coded probabilistic caching scheme is proposed for MEC-enabled small cell networks (SCNs). Different from previous mobility-aware caching schemes, user mobility and distributed storage are incorporated into a conventional probabilistic caching scheme, with the aim of throughput maximization. Based on stochastic geometry theory and a modified mobility model of discrete random jumps, the explicit expression of throughput is derived. Due to the complexity of the expression, two light-weight heuristic algorithms are provided to numerically obtain the optimal solutions. Moreover, a significant trade-off among the gains of mobility diversity, content diversity, and channel selection diversity is discussed, and we further numerically analyze how such a trade-off is influenced by user mobility, content popularity, and backhaul capacity, with some fundamental insights into the application of the proposed scheme in MEC-enabled SCNs. The superiority of our proposed scheme is demonstrated by the comparisons with the classical M most popular caching scheme and the conventional probabilistic caching scheme. Numerical results show that our proposed caching scheme achieves higher throughput than those of the other two, especially when users of intense mobility request contents, of which the popularity profile is not skewed, in MEC-enabled SCNs with poor backhaul capacity, indicating that the proposed caching scheme is a promising solution for network densification.

The explosion of traffic caused by the rapid growth of multimedia services of Internet of Vehicles (IoV) has brought heavy load to mobile networks. The edge caching of the Internet of vehicles is considered as a promising technology. When the existing content caching strategy is used in the vehicle network, it faces the challenge of high content caching delay caused by the high-speed mobility of vehicle users and insufficient social relations. To address these challenges, this paper proposes a Cooperative Edge Caching Scheme based on Mobility Prediction and Society Aware (CCMPSA). In this strategy, the Long Short-Term Memory (LSTM) network is used to predict the location of the vehicle at the next moment, the vehicle cache nodes are selected according to the social relationship reflected by the similarity of interest and communication probability between the vehicles, and the dynamic decision of the content cache problem is realized by deep reinforcement learning. The simulation results show that the performance of the proposed strategy is better than random caching and non-cooperative caching algorithms, and it not only reduces the content transmission delay and improves the cache hit ratio, but also improves the experience quality of the whole system.KeywordsCaching decisionsDeep reinforcement learningThe edge cachingThe long short-term memory networkInternet of Vehicles

In-band full-duplex (IBFD) self-backhauling is promising to provide cost-effective and flexible backhaul connectivity in ultra-dense wireless networks. In this paper, we propose a user-centric joint access-backhaul transmission framework for performance optimization in IBFD-enabled self- backhauled cooperative wireless networks. In the access link, user-centric clustering is adopted so that each user is cooperatively served by a cluster of small base stations (SBSs) via joint beamforming. In the backhaul link, user-centric multicast transmission is proposed so that the macro base station (MBS) treats each user's data as a multicast message and sends it to its serving SBS cluster. We formulate an optimization problem to maximize the end-to-end weighted sum rate of all users under power constraints through joint design of multicast beamforming in the backhaul link as well as SBS clustering and beamforming in the access link. We first tackle the joint access- backhaul beamforming problem under given SBS clustering by transforming it into a manifold optimization problem, for which a stationary solution is obtained using the Riemannian optimization technique. We then develop a heuristic algorithm to determine the SBS clustering. Simulation results demonstrate the effectiveness of the proposed algorithms.

Wireless self-backhaul technology is an effective solution to the backhaul bottleneck of 5G Heterogeneous Networks (HetNets). To effectively utilize the spectrum resource as well as reduce the transmission load of backhaul links, we propose a joint Context-aware Data Caching and Resource Allocation (CDCRA) scheme for self-backhauled HetNets aiming at maximizing the total system throughput. Context-aware technology combined with many-to-many matching theory is utilized for data caching in small base stations (SBSs). Then interference management based on graph theory is considered when allocating spectrum resource for both access links and backhaul links. Different comparison schemes are designed to verify the performance of our proposed scheme. Simulation results indicate that the total system throughput is significantly improved by CDCRA scheme comparing with other data caching and resource allocation schemes.

In this paper, we propose a heterogeneous cellular network based on orthogonal frequency division multiple access consisting of full‐duplex femtorelays. Then, we design schemes for the uplink radio resource allocation. The goal of the proposed schemes is to maximize the sum rate, taking into account the back‐haul and transmission power constraints. Moreover, the superiority of the proposed system is shown by comparing it with the half‐duplex femtorelay‐assisted counterpart. Since the proposed resource allocation optimization problem is nonconvex and intractable, we divide it into subcarrier and transmission power allocation subproblems and then use an iterative algorithm to solve each of them. Toward this end, in each iteration, subcarriers are allocated via a binary linear program, while the successive convex approximation method is adapted to transform the nonconvex transmission power allocation subproblem into a sequence of convex subproblems. To achieve this goal, we use 1 of the 3 proposed approaches, namely, dual, arithmetic‐geometric mean approximation, and difference of 2 concave functions. In addition, we investigate the performance, convergence, and computational complexity of these approaches. The simulation results reveal that the proposed approaches are close to the optimal solution while providing less computational complexity. Moreover, they illustrate that even by considering self‐interference in the full‐duplex mode, the sum rate will be increased approximately by 41%in comparison with the half‐duplex mode.

Early Access

This paper presents how to design fiber-optic relay node considering interferences between backhaul and access links. The way of proper arrangement of two different antennas is described as parameters of optical fiber length and radio frequency. Theoretical DUR due to the interference is provided relating to CNR performance mainly determined by the optical link. Provided that the radio frequency is 3.4 GHz and the antenna facing to eNB is positioned at high-SNR environments, optical fiber length (antenna separation) of 200 meters is enough to meet DUR of 30 dB. This will provide a solution of relaying without interference canceller for in-band relaying.