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In this paper, we propose a novel joint trajectory and communication scheduling scheme for multiple unmanned aerial vehicles (UAVs) enabled wireless caching networks. To exploit the favorable propagation of air-to-ground channels, we consider an ultra dense UAVs enabled content-centric wireless transmission network, where massive UAVs are deployed to transmit cached contents to a group of random distributed ground users. We formulate the problem as an infinite horizon ergodic stochastic differential game (SDG) for optimizing the users’ quality-of-experience (QoE). In particular, stochastic dynamics of channel states, UAVs’ mobility, energy queues and content request queues are modeled in this game. To deal with the state coupling between the UAVs, we consider a limiting problem for large number of UAV based on mean field analysis. A reduced-complexity decentralized solution can be obtained through mean-field equilibrium analysis. To further reduce the solution complexity on each UAV, we propose a model-specific deep neural network (DNN) to learn the optimal control solution in an online manner. The DNN is not arbitrarily generated but tailored to the structural properties of the value function and stationary distribution based on the homotopy perturbation method analysis. Finally, simulation results are provided to show that the proposed solution can achieve significant gain over the existing baselines. [ABSTRACT FROM AUTHOR]

An important ingredient of fifth generation (5G) networks will be Multiaccess Edge Computing (MEC). MEC brings the computational intelligence of the cloud within the Radio Access Network (RAN). The virtualized functionality is accessible through Application Programming Interfaces (APIs). In this paper, we study capabilities of reuse existing time-tested Web Services to provide mobile edge middleware services. The focus is on mobile edge services that can be used by applications for bandwidth management and access to user contextual information. An extension of Web Service functionality is proposed. Implementation issues of Web Services in RAN are considered. [ABSTRACT FROM AUTHOR]

The burgeoning growth of real-time applications, such as interactive video and VoIP, places a heavy demand for a high data rate and guarantee of QoS from a network. This is being addressed by fourth generation networks such as Long-Term Evolution (LTE). But, the mobility of user equipment that needs to be handed over to a new evolved node base-station (eNB) while maintaining connectivity with high data rates poses a significant challenge that needs to be addressed. Handover normally takes place at cell borders, which normally suffers high interference. This inter-cell interference (ICI) can affect HO procedures, as well as reduce throughput. In this paper, soft frequency reuse (SFR) and multiple preparations (MP), so-called SFRAMP, are proposed to provide a seamless and fast handover with high throughput by keeping the ICI low. Simulation results using LTE-Sim show that the outage probability and delay are reduced by 24.4% and 11.9%, respectively, over the hard handover method -- quite a significant result. [ABSTRACT FROM AUTHOR]

We propose a novel wireless radio resource manager to control both the transmission power and the bit rate of mobile devices cooperatively, whereas previous work has focused on handling them separately. The proposed scheme is called Genetic Algorithm for Mobiles Equilibrium (GAME). Based on an evolutionary computational model, GAME assigns optimally both the transmitting power and bit rate values to every mobile device in a given cell. Optimal allocation is in the sense that every mobile unit gets only enough resources necessary for meeting or exceeding its quality of service (QoS) requirements. GAME solves an optimization function that strives to maintain the QoS requirements of the different multimedia streams subject to the physical channel characteristics. Having done that, we gain further benefits as well. In addition to maintaining the QoS requirements, GAME tends to prefer assigning lower levels of transmission power, thus extending the mobile units' battery life, minimizing interference seen by other users, and significantly decreasing the call blocking (or dropping) rates. Furthermore, GAME radio resource allocations reduce infrastructure costs by requiring fewer base stations per square kilometer. In our experiments, we have seen a 70% average expansion in the base station coverage area with 40% decrease in mobile call outage probability among other benefits. [ABSTRACT FROM PUBLISHER]