Motoki Morita

Adaptive Power Level Setting of Femtocell Base Stations for Mitigating Interference with Macrocells

Femtocells are expected to increase network capacity, extend macrocell coverage, and introduce new services. Because femtocells share the same frequency band with macrocells in many cases, the femtocell base station (BS) must mitigate the interference with macrocells as well as ensure coverage in customer premises. However, conventional femtocell BS transmit power setting have not adequately accounted for the interference with neighboring macrocell mobile stations (MSs), leading to small femtocell user throughput. In this paper, we describe an adaptive femtocell BS transmit power level setting scheme to mitigate the interference with macrocell MSs. The proposed scheme estimates the path loss between the femtocell BS and the neighboring macrocell MSs on the basis of the received power levels from the neighboring macrocell MSs, thereby it mitigates the interference with macrocell MSs while maintaining good indoor coverage for femtocell MSs. According to the system level simulations of downlink LTE, femtocell user throughput of the proposed scheme at the edge of the macrocells is 36 % to 73 % greater than that of the conventional transmit power level setting scheme.

Uplink power control method for LTE femtocells based on resource usage aggregation

In LTE, uplink (UL) transmit power control is important to mitigate the UL aggregate interference from all femtocells to the macrocell, which is increased as the number of femtocells is increased. We propose an UL power control method for LTE femtocells adaptively setting target received power by using the aggregation of the resource usage of femtocells. With this method, when the aggregate resource usage is small, the UL throughput of femtocells is improved by increasing the UL transmit power. When the aggregate resource usage is large, the UL throughput of macrocells is maintained by decreasing the UL transmit power. With LTE system level simulations, it is shown that while in the full buffer traffic condition the decline in the UL throughput of macrocells due to introducing femtocells was suppressed, in the FTP traffic condition the UL throughput of femtocells was improved by 24% at the largest in comparison with the method using the number of active HeNBs.

A Deadline-Aware Scheduling Scheme for Connected Car Services Using Mobile Networks with Quality Fluctuation

Traffic collision is an extremely serious issue in the world today. The World Health Organization (WHO) reported the number of road traffic deaths globally has plateaued at 1.25 million a year. In an attempt to decrease the occurrence of such traffic collisions, various driving systems for detecting pedestrians and vehicles have been proposed, but they are inadequate as they cannot detect vehicles and pedestrians in blind places such as sharp bends and blind intersections. Therefore, mobile networks such as long term evolution (LTE), LTE-Advanced, and 5G networks are attracting a great deal of attention as platforms for connected car services. Such platforms enable individual devices such as vehicles, drones, and sensors to exchange real-time information (e.g., location information) with each other. To guarantee effective connected car services, it is important to deliver a data block within a certain maximum tolerable delay (called a deadline in this work). The Third Generation Partnership Project (3GPP) stipulates that this deadline be 100 ms and that the arrival ratio within the deadline be 0.95. We investigated an intersection at which vehicle collisions often occur to evaluate a realistic environment and found that schedulers such as proportional fairness (PF) and payload-size and deadline-aware (PayDA) cannot satisfy the deadline and arrival ratio within the deadline, especially as network loads increase. They fail because they do not consider three key elements— radio quality, chunk size, and the deadline—when radio resources are allocated. In this paper, we propose a deadline-aware scheduling scheme that considers chunk size and the deadline in addition to radio quality and uses them to prioritize users in order to meet the deadline. The results of a simulation on ns-3 showed that the proposed method can achieve approximately four times the number of vehicles satisfying network requirements compared to PayDA. key words: IoT, resource control, 5G, LTE, connected car, V2X

Adaptive coverage control using cell-specific beamforming based on throughput prediction

As the number of small cells is increased to improve mobile network capacity, disparity in the traffic load between small cells will unexpectedly widen, and then user throughput in a small cell with high traffic load will decrease. We propose a novel coverage control method that adaptively controls cell coverage for areas where users are densely located by using cell-specific beamforming with multiple array antenna elements on a small cell base station on the basis of user throughput prediction. With our proposed method, since the received signal quality of the densely located users is improved and other users are offloaded to neighboring cells, it is possible to improve user throughput in the small cell with high traffic load. The results of the performance evaluation show that the proposed method can improve the worst 5% of the user throughput by 68% due to load balancing and received signal quality improvement.