Delay-Constrained Caching in Cognitive Radio Networks

Zhao, Jing; Gao, Wei; Yi, Wang

doi:10.1109/tmc.2015.2426715

Cited by 12 publications

(7 citation statements)

References 29 publications

(43 reference statements)

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“…Although the caching technique has been studied in traditional networks, the application of the caching technique in CRNs has not been clearly studied. Zhao et al [20] applied caching in CRNs to reduce total cost under delay constraints. A services routing based caching scheme is proposed in Ref.…”

Section: Related Workmentioning

confidence: 99%

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Cache-enabled in cooperative cognitive radio networks for transmission performance

Yang

Man

et al. 2020

Tinshhua Sci. Technol.

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The proliferation of mobile devices that support the acceleration of data services (especially smartphones) has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents. Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay from the backhaul link to the secondary base station. First, in terms of the content caching and the transmission strategies, we provide a cooperation scheme to maximize the secondary user's effective data transmission rates under the constraint of the primary users target rate. Then, we investigate the impact of the caching allocation and prove that the formulated problem is a concave problem with regard to the caching capacity allocation for any given power allocation. Furthermore, we obtain the joint caching and power allocation by an effective bisection search algorithm. Finally, our results show that the content caching cooperation scheme can achieve significant performance gain for the primary and secondary systems over the traditional two-hop relay cooperation without caching.

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Section: Related Workmentioning

confidence: 99%

“…Caching in CRNs is investigated in Ref. [20], where data retrieval probability is derived, but primary-secondary cooperation is not considered and the cooperation caching scheme in CCRNs is still not investigated.…”

Section: Introductionmentioning

confidence: 99%

Cache-enabled in cooperative cognitive radio networks for transmission performance

Yang

Man

et al. 2020

Tinshhua Sci. Technol.

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“…In [15], they cached the popular content in both core network and radio access network. The authors in [16] solved the cache placement problem in cognitive radio networks to minimize the total cost subject to delay constraint. Data replication techniques were proposed to improve data access performance in [17], where they attempted to determine the optimal replication location for maximizing the average data retrieval probability.…”

Section: Related Workmentioning

confidence: 99%

Cooperative Caching Placement in Cognitive Device-to-Device Networks

Chen¹,

Shen²,

Cao³

2016

jcm

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Cognitive radio is regarded as a key technique in the fifth generation communication system. We consider that the popular contents can be cached in cognitive mobile users who compose a cognitive Device-to-Device (D2D) network. Cached Contents in this network can be shared by cooperating with each other. Consequently, contents can be downloaded from local cache, cognitive D2D network or cellular network with different access cost. It has communication cost when accessing cellular networks, and time delay and cooperative cost when accessing cognitive D2D networks. To minimize the total cost of all the mobile users, we formulate an optimal content placement problem. This problem is hard to solve, and we proposed a suboptimal cache scheme, including cache placement and cache replacement. Our approach quantifies time delay cost by modeling the primary appearance as a continuous-time Markov chain. Numerical results show that our approach is lowcomplexity and implementable.

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“…The proposed approach would support heterogeneous networks. The existing research work on cache-enabled cooperation in CRN didn't address the limitations with floating caching, which has become an important implementation of content caching, to enhance the performance [7].…”

Section: Introductionmentioning

confidence: 99%

Cache-Enabled Unmanned Aerial Vehicles for Cooperative Cognitive Radio Networks

Yang

Xiao

Jiang

et al. 2020

IEEE Wireless Commun.

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Cooperative cognitive radio network is a new method to alleviate the spectrum scarcity problem. The proactive content caching and unmanned aerial vehicles (UAVs) relaying techniques are deployed in a cognitive radio network (CRN), to enable the achievable rates for primary and secondary systems. Even though these two emerging technologies are grateful to solve the problem of spectrum scarcity, there are still open issues to influence the system performance and the utilization of spectrum. In this article, we provide an overview of the cooperation technique, including their theoretical schemes and the advanced performance in radio networks. Then, this paper proposes a cache-enabled UAV cooperation scheme in CRN, which enhances the CRN's transmission capability and reduces the redundant traffic load of CRN. The experimental results show that the cache-enabled UAV scheme significantly improves the achievable rates for both systems in cooperative cognitive radio network (CCRN). In addition, we present the future work related to content caching, deployment of UAV and CCRN to support radio networks.

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Delay-Constrained Caching in Cognitive Radio Networks

Cited by 12 publications

References 29 publications

Cache-enabled in cooperative cognitive radio networks for transmission performance

Cache-enabled in cooperative cognitive radio networks for transmission performance

Cooperative Caching Placement in Cognitive Device-to-Device Networks

Cache-Enabled Unmanned Aerial Vehicles for Cooperative Cognitive Radio Networks

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