Proliferation of mobile devices over the past few years has explosively increased demand for multimedia content in various service scenarios such as video and game streaming. This growth in demand for mobile content has brought a significant challenge of how to efficiently deliver such content to users. Content delivery networks (CDNs) have grown in popularity as the most feasible solution to overcome this challenge. Many mobile network operators have tried to develop customized CDN solutions suited to their network systems in practice. In this paper, we focus on an intriguing paradigm where mobile devices are used as cache servers and localized content sharing is activated via device-to-device (D2D) communication. As the most feasible network system, we consider a network-assisted D2D CDN where a mobile network assists and controls D2D communication processes. We first investigate inherent characteristics of the network system, resulting in the following findings: 1) D2D communication utilization and 2) network assisted control. As a new approach to devise efficient CDN design and control algorithms that simultaneously consider the inherent characteristics, we adopt the Lyapunov stability theory. As a result, we can derive efficient algorithms including content placement, content request routing, and content scheduling as a total solution including CDN design as well as control based on a cross-layer design approach. Through packet simulations, it is demonstrated that the performance yielded by the proposed strategies is superior to that delivered by other strategies in terms of delay to directly represent content delivery performance.

Wireless content delivery networks (WCDNs) have received attention as a promising solution to reduce the network congestion caused by rapidly growing demands for mobile content. The amount of reduced congestion is intuitively proportional to the hit ratio in a WCDN. Cooperation among cache servers is strongly required to maximize the hit ratio in a WCDN where each cache server is equipped with a small-size cache storage space. In this paper, we address a content replacement problem that deals with how to manage contents in a limited cache storage space in a reactive manner to cope with a dynamic content demand over time. As a new challenge, we apply reinforcement learning, which is Q-learning, to the content replacement problem in a WCDN with coooperative caching. We model the content replacement problem as a Markov Decision Process (MDP) and finally propose an efficient content replacement strategy to maximize the hit ratio based on a multi-agent Q-learning scheme. Simulation results exhibit that the proposed strategy contributes to achieving better content delivery performance in delay due to a higher hit ratio, compared to typical existing schemes of least recently used (LRU) and least frequently used (LFU).

Internet content caching for multimedia services has received much attention mainly in the field of large-scale wired networking as a primary solution to save network resources and improve quality of service (QoS). Rapidly increasing consumption of multimedia content in mobile networks brings a challenge of how to efficiently deliver content in local wireless access networks. Cache embedment in wireless mesh environment is an intriguing attempt to enhance the QoS and service capacity, leading to the question of how to design an efficient content delivery network considering the inherent characteristics of the wireless environment. We propose and investigate an efficient cache placement strategy in novel two-tier wireless content delivery networks, which utilize separate channels for content dissemination and content service. Such a two-tier network system model helps to achieve much better content delivery performance with a greatly reduced system design complexity compared to single-tier network system models. Further, we incorporate a delay cost due to contention, which is mainly responsible for performance in shared-medium wireless networks, as a key metric for cache placement under the system model. After formally formulating the cache placement problem, we propose a cross-layer heuristic algorithm and demonstrate its performance compared with an optimal solution by integer linear programming. Simulation results show significant performance improvements by our strategy compared to the performance of existing representative strategies in terms of service delay, packet delivery ratio, and the amount of delivered packets within a given delay deadline.

Content delivery network (CDN) with a high quality-of-service (QoS) requirement deals with three challenging problems: 1) a cache server deployment problem to determine where to locate cache servers, 2) a request routing problem to settle which cache server serves a user request, and 3) a content replication problem to decide which content is stored in a cache server. Cooperation among cache servers significantly improves the user QoS by increasing the cached content diversity of the network. Since the aforementioned problems are tightly coupled, we formulate a new CDN model which jointly considers all the three problems under the cooperative content replication with optimal solutions using integer linear programming. As the joint optimization problem is an NP-hard problem, we propose a greedy heuristic algorithm which is close to the optimal solution. We consider two scenarios for application of the algorithm, where the popularities of contents are identical and are different among nodes. The performance of the algorithm is investigated on the actual topology sampled from the Level 3 CDN network. By increasing the cached content diversity in the network, the joint optimization problem under the cooperative content replication shows higher performance than that of the non-cooperation case.

Wireless mesh networking (WMN) for video surveillance provides a strong potential for rapid deployment in a large community, for which reliability and survivability for real-time streaming are the key performance measure. However, current routing protocols do not provide a robust solution to meet video transmission requirements such as providing load balancing for the high data rate and delay requirements. We propose an application of field-based anycast routing (FAR) protocol, which utilizes rapid routing dynamics inspired by an electrostatic potential field model governed by Poisson's equation. This routing metric takes into account geometric proximity and congestion degree in order to increase delivery ratio and decrease end-to-end delay, which determine the quality of the delivered video. In addition, FAR protects node failure with an on-the-fly rerouting process that guarantees the continuity of video streaming. Simulation results show 100% delivery ratio in congestion situations and it shows tolerance to different delay requirements compared with AODV and FDMR protocols in terms of delivering real-time and non real-time video surveillance which verifies FAR as a strong candidate for video transmission over WMN.

In this paper, we propose channel training and beamforming schemes to maximize the benefit of large-scale antenna, or massive multiple-input multiple-output (MIMO) systems. The proposed schemes are operated by transmitting continuous precoding matrix indicator (PMI) feedback signals through a series of pattern. Conventional communication systems, such as LTE systems, use PMI, rank indicator (RI), and channel quality indicator (CQI) to report the channel state information (CSI) to the enhanced node B (eNB), with an increasing feedback overhead as the number of antenna elements increases. The proposed beamforming and feedback schemes solve this problem by iterative CSI reports and codebook extension. Each PMI report is conducted based on a component codebook of smaller size, and cumulated feedback information is utilized to build an extended beamformer. The proposed methods are applicable to many different types of wireless systems, including frequency division duplex (FDD) systems which do not possess the channel reciprocity assumed by many of earlier works. The methods also ensure the backward compatibility which allows the operation of legacy user equipment (UE). The continuous feedback process also enables the enhancement of the codebook resolution. The resulting system performance improvement is verified by computer simulation results.

In this paper, we propose strategies to mitigate inter-cell interference by using remote radio heads (RRHs) installed at cell edge areas. For conventional systems, all user equipments (UEs) located in the coverage of a macro base station (BS) are assumed to be scheduling candidates for the corresponding cell. This makes UEs located near cell edge areas experience significant inter-cell interference. The proposed strategies solve the problem by virtually extending the coverage area to be larger than the area where the scheduling candidates are located. The advantage of the coverage extension is mainly obtained from a concept of moving cell boundaries, which is realized by partially activating the RRHs in a time-division fashion. Based on the Monte-Carlo simulations, performance benefits of moving boundary schemes over the static boundary schemes are presented.