Naguib K.M.Ali A.S.Mahmoud K.R.Department of Electrical Systems EngineeringOctober University for Modern Sciences and Arts (MSA)GizaEgypt; Department of Electronics Communications and ComputersHelwan UniversityCairoEgypt2020-01-092020-01-0920199.78E+12https://doi.org/10.1109/ICENCO.2018.8636120PubMed ID :https://t.ly/R28WDScopusContent caching in Device-to-Device (D2D) wireless cellular network can be considered an attractive solution to decrease network load during peak time hence improve network performance. In such network, predicting users' movement pattern allows proactive caching to alleviate its congestion leading to load decrease. Optimizing caching process is one important issue to enhance network performance and thus increase offloading probability. In this work, a caching policy strategy is introduced where the network jointly recognizes group mobility and user preferences to solve the caching optimization problem. Particle Swarm Optimization (PSO) algorithm is used to minimize the overall network load by optimizing the amount of data cached in users devices. Simulations are carried out to evaluate performance of presented optimal caching policy. Numerical results in terms of network gain show that the proposed caching scheme optimized by PSO outperforms both baseline scenario and random mobility-based schemes. � 2018 IEEE.EnglishDevice-to-Device networkGroup mobilityParticle Swarm OptimizationProactive cachingUser preferenceNetwork performanceAttractive solutionsGroup mobilityOptimization problemsParticle swarm optimization algorithmProactive cachingRandom mobilitiesUser preferenceWireless cellular networksParticle swarm optimization (PSO)Conference Paperhttps://doi.org/10.1109/ICENCO.2018.8636120PubMed ID :