1,012 research outputs found

    Content Placement in Cache-Enabled Sub-6 GHz and Millimeter-Wave Multi-antenna Dense Small Cell Networks

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    This paper studies the performance of cache-enabled dense small cell networks consisting of multi-antenna sub-6 GHz and millimeter-wave base stations. Different from the existing works which only consider a single antenna at each base station, the optimal content placement is unknown when the base stations have multiple antennas. We first derive the successful content delivery probability by accounting for the key channel features at sub-6 GHz and mmWave frequencies. The maximization of the successful content delivery probability is a challenging problem. To tackle it, we first propose a constrained cross-entropy algorithm which achieves the near-optimal solution with moderate complexity. We then develop another simple yet effective heuristic probabilistic content placement scheme, termed two-stair algorithm, which strikes a balance between caching the most popular contents and achieving content diversity. Numerical results demonstrate the superior performance of the constrained cross-entropy method and that the two-stair algorithm yields significantly better performance than only caching the most popular contents. The comparisons between the sub-6 GHz and mmWave systems reveal an interesting tradeoff between caching capacity and density for the mmWave system to achieve similar performance as the sub-6 GHz system.Comment: 14 pages; Accepted to appear in IEEE Transactions on Wireless Communication

    Matching Theory for Future Wireless Networks: Fundamentals and Applications

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    The emergence of novel wireless networking paradigms such as small cell and cognitive radio networks has forever transformed the way in which wireless systems are operated. In particular, the need for self-organizing solutions to manage the scarce spectral resources has become a prevalent theme in many emerging wireless systems. In this paper, the first comprehensive tutorial on the use of matching theory, a Nobelprize winning framework, for resource management in wireless networks is developed. To cater for the unique features of emerging wireless networks, a novel, wireless-oriented classification of matching theory is proposed. Then, the key solution concepts and algorithmic implementations of this framework are exposed. Then, the developed concepts are applied in three important wireless networking areas in order to demonstrate the usefulness of this analytical tool. Results show how matching theory can effectively improve the performance of resource allocation in all three applications discussed

    NOMA Assisted Wireless Caching: Strategies and Performance Analysis

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    Conventional wireless caching assumes that content can be pushed to local caching infrastructure during off-peak hours in an error-free manner; however, this assumption is not applicable if local caches need to be frequently updated via wireless transmission. This paper investigates a new approach to wireless caching for the case when cache content has to be updated during on-peak hours. Two non-orthogonal multiple access (NOMA) assisted caching strategies are developed, namely the push-then-deliver strategy and the push-and-deliver strategy. In the push-then-deliver strategy, the NOMA principle is applied to push more content files to the content servers during a short time interval reserved for content pushing in on-peak hours and to provide more connectivity for content delivery, compared to the conventional orthogonal multiple access (OMA) strategy. The push-and-deliver strategy is motivated by the fact that some users' requests cannot be accommodated locally and the base station has to serve them directly. These events during the content delivery phase are exploited as opportunities for content pushing, which further facilitates the frequent update of the files cached at the content servers. It is also shown that this strategy can be straightforwardly extended to device-to-device caching, and various analytical results are developed to illustrate the superiority of the proposed caching strategies compared to OMA based schemes

    Cooperative Multi-Bitrate Video Caching and Transcoding in Multicarrier NOMA-Assisted Heterogeneous Virtualized MEC Networks

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    Cooperative video caching and transcoding in mobile edge computing (MEC) networks is a new paradigm for future wireless networks, e.g., 5G and 5G beyond, to reduce scarce and expensive backhaul resource usage by prefetching video files within radio access networks (RANs). Integration of this technique with other advent technologies, such as wireless network virtualization and multicarrier non-orthogonal multiple access (MC-NOMA), provides more flexible video delivery opportunities, which leads to enhancements both for the network's revenue and for the end-users' service experience. In this regard, we propose a two-phase RAF for a parallel cooperative joint multi-bitrate video caching and transcoding in heterogeneous virtualized MEC networks. In the cache placement phase, we propose novel proactive delivery-aware cache placement strategies (DACPSs) by jointly allocating physical and radio resources based on network stochastic information to exploit flexible delivery opportunities. Then, for the delivery phase, we propose a delivery policy based on the user requests and network channel conditions. The optimization problems corresponding to both phases aim to maximize the total revenue of network slices, i.e., virtual networks. Both problems are non-convex and suffer from high-computational complexities. For each phase, we show how the problem can be solved efficiently. We also propose a low-complexity RAF in which the complexity of the delivery algorithm is significantly reduced. A Delivery-aware cache refreshment strategy (DACRS) in the delivery phase is also proposed to tackle the dynamically changes of network stochastic information. Extensive numerical assessments demonstrate a performance improvement of up to 30% for our proposed DACPSs and DACRS over traditional approaches.Comment: 53 pages, 24 figure
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