TY - JOUR
T1 - Joint Assortment and Cache Planning for Practical User Choice Model in Wireless Content Caching Networks
AU - Fu, Yaru
AU - Xu, Xinyu
AU - Liu, Hanlin
AU - Yu, Quan
AU - Dai, Hong Ning
AU - Quek, Tony Q.S.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2024/5/1
Y1 - 2024/5/1
N2 - In wireless content caching networks (WCCNs), a user's content consumption crucially depends on the assortment offered. Here, the assortment refers to the recommendation list. An appropriate user choice model is essential for greater revenue. Therefore, in this paper, we propose a practical multinomial logit choice model to capture users' content requests. Based on this model, we first derive the individual demand distribution per user and then investigate the effect of the interplay between the assortment decision and cache planning on WCCNs' achievable revenue. A revenue maximization problem is formulated while incorporating the influences of the screen size constraints of users and the cache capacity budget of the base station (BS). The formulated optimization problem is a non-convex integer programming problem. For ease of analysis, we decompose it into two folds, i.e., the personalized assortment decision problem and the cache planning problem. By using structure-oriented geometric properties, we design an iterative algorithm with examinable quadratic time complexity to solve the non-convex assortment problem in an optimal manner. The cache planning problem is proved to be a 0-1 Knapsack problem and thus can be addressed by a dynamic programming approach with pseudo-polynomial time complexity. Afterwards, an alternating optimization method is used to optimize the two types of variables until convergence. It is shown by simulations that the proposed scheme outperforms various existing benchmark schemes.
AB - In wireless content caching networks (WCCNs), a user's content consumption crucially depends on the assortment offered. Here, the assortment refers to the recommendation list. An appropriate user choice model is essential for greater revenue. Therefore, in this paper, we propose a practical multinomial logit choice model to capture users' content requests. Based on this model, we first derive the individual demand distribution per user and then investigate the effect of the interplay between the assortment decision and cache planning on WCCNs' achievable revenue. A revenue maximization problem is formulated while incorporating the influences of the screen size constraints of users and the cache capacity budget of the base station (BS). The formulated optimization problem is a non-convex integer programming problem. For ease of analysis, we decompose it into two folds, i.e., the personalized assortment decision problem and the cache planning problem. By using structure-oriented geometric properties, we design an iterative algorithm with examinable quadratic time complexity to solve the non-convex assortment problem in an optimal manner. The cache planning problem is proved to be a 0-1 Knapsack problem and thus can be addressed by a dynamic programming approach with pseudo-polynomial time complexity. Afterwards, an alternating optimization method is used to optimize the two types of variables until convergence. It is shown by simulations that the proposed scheme outperforms various existing benchmark schemes.
KW - Cache planning
KW - personalized assortment decision
KW - revenue optimization
KW - user's choice model
UR - http://www.scopus.com/inward/record.url?scp=85165899679&partnerID=8YFLogxK
U2 - 10.1109/TMC.2023.3297987
DO - 10.1109/TMC.2023.3297987
M3 - Article
AN - SCOPUS:85165899679
SN - 1536-1233
VL - 23
SP - 4709
EP - 4722
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 5
M1 - 10192067
ER -