An Efficient Trajectory Planning for Cellular-Connected UAV under the Connectivity Constraint

Unmanned Aerial Vehicles(UAVs)acting as aerial users to access the cellular network form a promising solution to guarantee its safe and efficient operations via the high-quality communication.Due to the flexible mobility of UAVs and the coverage range limits of ground base station(GBS),the signalto-noise ratio(SNR)of the communication link between UAVs and GBS will fluctuate.It is an important requirement to maintain the UAV’s cellular connection to meet a certain SNR requirement during the mission for UAV flying from take off to landing.In this paper,we study an efficient trajectory planning method that can minimize a cellular-connected UAV’s mission completion time under the connectivity requirement.The conventional method to tackle this problem adopts graph theory or a dynamic programming method to optimize the trajectory,which generally incurs high computational complexities.Moreover,there is a nonnegligible performance gap compared to the optimal solution.To this end,we propose an iterative trajectory optimizing algorithm based on geometric planning.Firstly,we apply graph theory to obtain all the possible UAV-GBS association sequences and select the candidate association sequences based on the topological relationship among UAV and GBSs.Next,adopting the triangle inequality property,an iterative handover location design is proposed to determine the shortest flight trajectory with fast convergence and low computation complexity.Then,the best flight trajectory can be obtained by comparing all the candidate trajectories.Lastly,we revealed the tradeoff between mission completion time and flight energy consumption.Numerical results validate that our proposed solution can obtain the effectiveness with set accuracy and outperform against the benchmark schemes with affordable computation time.

Predicting the Geographic Traffic Distribution in Cellular Networks

Early detection and rapid resolution network congestion can considerably improve network capacity. Consequently, much research has been carried out on predicting traff ic patterns in 3G networks. This paper introduces an access point centric approach that is implemented by two prediction models, the traffic abstraction model and the order-k Markov model. Traffi c predictions are carried out to support the congestion control in the semi-smart antenna systems. The simulation result shows that the cumulative error rate is below 25% even carrying out multi-step-ahead predictions.

QoS in Node-Disjoint Routing for Ad Hoc Networks

Ad hoc network (MANET) is a collection of mobile nodes that can communicate with each other without using any fixed infrastructure. To support multimedia applications such as video and voice MANETs require an efficient routing protocol and quality of service (QoS) mechanism. Node-Disjoint Multipath Routing Protocol (NDMR) is a practical protocol in MANETs: it reduces routing overhead dramatically and achieves multiple node-disjoint routing paths. QoS support in MANETs is an important issue as best-effort routing is not efficient for supporting multimedia applications. This paper presents a novel adaptation of NDMR, QoS enabled NDMR, which introduces agent-based SLA management. This enhancement allows for the intelligent selection of node-disjoint routes based on network conditions, thus fulfilling the QoS requirements of Service Level Agreements (SLAs).

Multi-cell uplink power allocation game for user minimum performance guarantee in OFDMA systems

The multi-cell uplink power allocation problem for orthogonal frequency division multiplexing access （OFDMA） cellular networks is investigated with the uplink transmission power allocation on each co-frequency subchannel being defined as a multi-cell non-cooperative power allocation game （MNPG）.The principle of the design of the utility function is given and a novel utility function is proposed for MNPG.By using this utility function,the minimum signal to interference plus noise ratio （SINR） requirement of a user can be guaranteed.It can be shown that MNPG will converge to the Nash equilibrium and that this Nash equilibrium is unique.In considering the simulation results,the effect of the algorithm parameters on the system performance is discussed,and the convergence of the MNPG is verified.The performance of MNPG is compared with that of traditional power allocation schemes,the simulation results showing that the proposed algorithm increases the cell-edge user throughput greatly with only a small decrease in cell total throughput; this gives a good tradeoff between the throughput of cell-edge users and the system spectrum efficiency.

Transmission strategies for wireless powered MIMO relay systems

This paper studies a multiple input multiple output （MIMO） simultaneous wireless information and power transfer （SWIPT） relay system, in which the source node （SN） send information and energy simultaneously to the relay node （RN）, and the RN forward the received signal to the destination node （DN） powered by harvested energy. In particular, we consider two SWIPT receiver designs, namely power splitting （PS） and antenna switching （AS） in the relay system. For each design, iterative algorithms based on convex optimization technique are proposed to maximize the system rate. Furthermore, in order to strike a balance between computational complexity and system performance, based on the AS scheme, we propose a low complexity optimization method for PS scheme where a suboptimal PS ratio is given. Numerical results are provided to evaluate the performance of the proposed algorithm for MIMO SWIPT relay systems. It is shown that the performance of the proposed suboptimal method approaches that of the optimal PS scheme.