Paper Info
Title
Content Pushing Over Multiuser MISO Downlinks With Multicast Beamforming and Recommendation: A Cross-Layer Approach
Abstract
Proactive caching is recognized as a promising approach to handle the rapid growth of data traffic, thereby attracting much attention recently. As a key performance metric of caching, the hit ratio is determined by demand probabilities of users for content items and caching decisions. Because the recommendation system is capable of shaping user demands, the joint caching and recommendation holds the potential of improving the hit ratio substantially. In this paper, joint pushing and recommendation (JPR) schemes are presented for multiuser multiple-input single-output (MISO) systems, in which content items are pushed over MISO downlinks with multicast beamforming. Aiming at maximizing the effective throughput, we formulate a multi-stage stochastic programming problem under the constraints of transmit power and quality of experience (QoE). Since the formulated problem is intractable, suboptimal online JPR policies are presented based on the convex–concave procedure and branch-and-bound methods. Simulations show that presented JPR policies are capable of attaining significant effective throughput gains.
Year
DOI
Venue
2019
10.1109/TCOMM.2019.2929129
IEEE Transactions on Communications
Keywords
Field
DocType
Array signal processing,Throughput,MISO communication,Quality of experience,Multicast communication,Multicast algorithms,Signal to noise ratio
Recommender system,Beamforming,Transmitter power output,Computer science,Performance metric,Computer network,Electronic engineering,Quality of experience,Multicast,Throughput,Stochastic programming
Journal
Volume
Issue
ISSN
67
10
0090-6778
Citations 
PageRank 
References 
2
0.36
0
Authors
2
Name
Order
Citations
PageRank
Zhiyuan Li11380155.70
Wei Chen21711246.70