scholarly journals Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2449 ◽  
Author(s):  
Wenpeng Jing ◽  
Xiangming Wen ◽  
Zhaoming Lu ◽  
Haijun Zhang
Keyword(s):  
Content Delivery ◽  
Decision Time ◽  
Base Stations ◽  
Joint Optimization ◽  
Resources Allocation ◽  
User Association ◽  
Placement Problem ◽  
Content Caching ◽  
Backhaul Link ◽  
Content Placement

Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs’ cache tends to be small, while mobile users’ content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wireless networks. All of these pose great challenges on the content caching and content delivery. This paper studies the joint optimization of the content placement and content delivery schemes in the cache-enabled ultra-dense small-cell network (UDN) with constrained-backhaul link. Considering the differences in decision time-scales, the content placement and content delivery are investigated separately, but their interplay is taken into consideration. Firstly, a content placement problem is formulated, where the uncertainty of user-BS association is considered. Specifically, different from the existing works, the specific multi-location request pattern is considered that users tend to send content requests from more than one but limited locations during one day. Secondly, a user-BS association and wireless resources allocation problem is formulated, with the objective of maximizing users’ data rates under the backhaul bandwidth constraint. Due to the non-convex nature of these two problems, the problem transformation and variables relaxation are adopted, which convert the original problems into more tractable forms. Then, based on the convex optimization methods, a content placement algorithm, and a cache-aware user association and resources allocation algorithm are proposed, respectively. Finally, simulation results are given, which validate that the proposed algorithms have obvious performance advantages in terms of the network utility, the hit ratio of the cache, and the quality of service guarantee, and are suitable for the cache-enabled UDN with constrained-backhaul link.

scholarly journals Joint Optimization of Content Placement and User Association in Cache-Enabled Heterogeneous Cellular Networks Based on Flow-Level Models

2018 ◽  
Vol 2018 ◽  
pp. 1-20
Author(s):  
Hua Qu ◽  
Gongye Ren ◽  
Jihong Zhao ◽  
Zhenjie Tan ◽  
Shuyuan Zhao
Keyword(s):  
Cellular Networks ◽  
Content Delivery ◽  
Mixed Integer ◽  
Joint Optimization ◽  
User Association ◽  
Heterogeneous Cellular Networks ◽  
Coupled Models ◽  
Average Delay ◽  
Delivery Delay ◽  
Content Placement

Cache-enabled heterogeneous cellular networks (HCNs) have been investigated extensively to alleviate backhaul congestion and reduce content delivery delay. In this paper, we jointly optimize content placement and user association to minimize the average content delivery delay in cache-enabled HCNs based on flow-level models. This formulation considers (1) different timescales of content placement and content delivery, (2) locality of content popularity, and (3) the heterogeneity of spatial traffic distribution, which are often neglected in existing researches. The joint optimization problem is formulated as a mixed integer nonlinear programming problem in load-non-coupled and load-coupled models, respectively. We decouple this problem into two interrelated subproblems and resolve them individually. For the user association problem under a given content placement situation, we propose a content-level selective association algorithm, which allows the requests for different contents at the same location to connect to different base stations (BSs). In addition, we propose a greedy content caching algorithm to add contents to the caches of BSs in an iterative manner. These two algorithms are alternately executed until the caches of all the BSs are filled to capacity. Simulation results show that the proposed algorithm achieves better performance in terms of average delay and backhaul usage compared with traditional content placement and user association approaches.

scholarly journals Caching and Placement for In-Network Caching in Device-to-Device Communications

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Somayeh Soleimani ◽  
Xiaofeng Tao
Keyword(s):  
Optimization Problem ◽  
Optimal Solution ◽  
Content Delivery ◽  
Base Stations ◽  
D2d Communications ◽  
Dual Decomposition ◽  
Placement Problem ◽  
Content Discovery ◽  
Device To Device ◽  
Promising Solution

Caching content by users constitutes a promising solution to decrease the costly transmissions with going through the base stations (BSs). To improve the performance of in-network caching in device-to-device (D2D) communications, caching placement and content delivery should be jointly optimized. To this end, we jointly optimize caching decision and content discovery strategies by considering the successful content delivery in D2D links for maximizing the in-network caching gain through D2D communications. Moreover, an in-network caching placement problem is formulated as an integer nonlinear optimization problem. To obtain the optimal solution for the proposed problem, Lagrange dual decomposition is applied in order to reduce the complexity. Simulation results show that the proposed algorithm has a near-optimal performance, approaching that of the exhaustive search method. Furthermore, the proposed scheme has a notable in-network caching gain and an improvement in traffic offloading compared to that of other caching placement schemes.

scholarly journals Joint Optimization of User Association and Resource Allocation for Millimeter-Wave Integrated Backhaul and Access Network

2019 ◽  
Vol 37 (5) ◽  
pp. 943-951
Author(s):  
Zhongyu Ma ◽  
Bo Li ◽  
Zhongjiang Yan ◽  
Mao Yang
Keyword(s):  
Resource Allocation ◽  
Millimeter Wave ◽  
Optimization Problem ◽  
Access Network ◽  
Joint Optimization ◽  
Utilization Rate ◽  
User Association ◽  
Access Rate ◽  
Backhaul Link ◽  
Access Link

Since the millimeter wave integrated backhaul and access network(mm-Wave IBAN) can divide the resource ratio between the access and the backhaul link as needed, there is a huge advantage in the improvement of the utilization rate for 5G communication network. A joint optimization method of user association and resource allocation is proposed and implemented for the mm-Wave IBAN from the perspective of the maximization of the transmission traffic in the whole network. The joint optimization problem of the user association and the resource allocation is formulated as a combined non-convex optimization problem, and then the problem is decomposed into two sub-problems. The first sub-problem, which is aimed at the maximization of the whole access rate, is the problem of the user association under the condition of the match between the access rate and backhaul rate. The second sub-problem, which is aimed at the maximization of the whole traffic of the network, is the problem of the resources allocation between the access link and backhaul link. The artificial immune optimization algorithm (IOA) is used to solve the first sub-problem. After that, the optimal transmission resource ratio between the access link and backhaul link is obtained according to the differentiating of the expression for the whole traffic. The simulation results show that the proposed method has more gains in the improvement of the whole network traffic when compared with the user association mechanism based on the nearest distance.

scholarly journals On the Performance of UAV-Aided Content Caching in Small-Cell Networks with Joint Transmission

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1040
Author(s):  
Menghan Wei ◽  
Youjia Chen ◽  
Ming Ding
Keyword(s):  
Transmission Rate ◽  
High Mobility ◽  
Limited Resource ◽  
Small Cell ◽  
Base Stations ◽  
Cell Content ◽  
Small Cell Networks ◽  
Content Caching ◽  
Cell Networks ◽  
Joint Transmission

Unmanned aerial vehicles (UAVs), featured by the high-mobility and high-quality propagation environment, have shown great potential in wireless communication applications. In this paper, a novel UAV-aided small-cell content caching network is proposed and analyzed, where joint transmission (JT) is considered in the dense small-cell networks and mobile UAVs are employed to shorten the serving distance. The system performance is evaluated in terms of the average cache hit probability and the ergodic transmission rate. From the analytical results, we find that (i) the proposed UAV-aided small-cell network shows superior caching performance and, even with a small density of UAVs the system’s cache hit probability, can be improved significantly; (ii) the content’s optimal caching probability to maximize the cache hit probability is proportional to the (K+1)-th root of its request probability, where K is the number of small-cell base stations that serve each user by JT; (iii) caching the most popular content in UAVs may lead to a low transmission rate due to the limited resource offered by the low-density UAVs. Simulation results are presented to validate the theoretical results and the performance gain achieved by the optimal caching strategy.

scholarly journals Transmission of wireless backhaul signal in a cellular system with small moving cells

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Hyoung-Keon Kim ◽  
Yong-Suk Byun ◽  
Geon-Woong Jung ◽  
Yong-Hwan Lee
Keyword(s):  
Signal Transmission ◽  
Cellular Systems ◽  
Base Stations ◽  
Wireless Backhaul ◽  
Backhaul Link ◽  
Channel Information ◽  
Short And Long Term ◽  
Water Filling ◽  
Noise Ratio

Abstract Deployment of small moving cells (SMCs) has been considered in advanced cellular systems, where wireless backhaul links are required between base stations and SMCs. In this paper, we consider signal transmission by means of multiuser beamforming in the wireless backhaul link. We generate the beam weight in an eigen-direction of weighted combination of short- and long-term channel information of the backhaul link. The beam weight can maximize the average signal-to-leakage-plus-noise ratio (SLNR), while providing the transmission robust to SMC mobility. We analyze the performance of the proposed scheme in terms of the average signal-to-interference-plus-noise ratio (SINR) and optimize the transmit power by iterative water-filling. Finally, we verify the performance of the proposed scheme by computer simulation.

scholarly journals Resource Allocation for Energy Efficient User Association in User-Centric Ultra-Dense Networks Integrating NOMA and Beamforming

2020 ◽  
Author(s):  
Long Zhang ◽  
Guobin Zhang ◽  
Xiaofang Zhao ◽  
Yali Li ◽  
Chuntian Huang ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Large Scale ◽  
Mixed Integer ◽  
Joint Optimization ◽  
User Association ◽  
Dual Decomposition ◽  
Dense Networks ◽  
Wireless Backhaul ◽  
User Centric

A coupling of wireless access via non-orthogonal multiple access and wireless backhaul via beamforming is a promising way for downlink user-centric ultra-dense networks (UDNs) to improve system performance. However, ultra-dense deployment of radio access points in macrocell and user-centric view of network design in UDNs raise important concerns about resource allocation and user association, among which notably is energy efficiency (EE) balance. To overcome this challenge, we develop a framework to investigate the resource allocation problem for energy efficient user association in such a scenario. The joint optimization framework aiming at the system EE maximization is formulated as a large-scale non-convex mixed-integer nonlinear programming problem, which is NP-hard to solve directly with lower complexity. Alternatively, taking advantages of sum-of-ratios decoupling and successive convex approximation methods, we transform the original problem into a series of convex optimization subproblems. Then we solve each subproblem through Lagrangian dual decomposition, and design an iterative algorithm in a distributed way that realizes the joint optimization of power allocation, sub-channel assignment, and user association simultaneously. Simulation results demonstrate the effectiveness and practicality of our proposed framework, which achieves the rapid convergence speed and ensures a beneficial improvement of system-wide EE.<br>

scholarly journals Matching-based cache placement decision for 5G network caching

2021 ◽  
Author(s):  
Shadi Sadeghpour Kharkan
Keyword(s):  
Graph Matching ◽  
Placement Problem ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Cell Network ◽  
5G Network ◽  
Backhaul Link ◽  
Random Placement ◽  
Cache Placement ◽  
Bottleneck Link

In this thesis, we present a cache placement scheme to deal with backhaul link constraint in Small Cell Network for 5G wireless network. We formulated the cache placement problem as a graph matching problem and presented an optimal file-helper matching algorithm. We defined stability criterion for the matching and found that our matching solution is stable in the sense that every helper finds at least one file to cache given that no file exceed minimum cache size. We achieved a unique placement of a file within a cluster of helpers to increase the number of files cached within a cluster. Further, our experimental evaluation demonstrates that our algorithm increases local and neighbor hit ratios as compared to a random placement, which in turn significantly decreases the traffic that goes over the backhaul bottleneck link.

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