The human blockage problem is an open issue in next- generation wireless access networks using millimeter-wave (mmWave) communications. A proactive base station (BS) handover system leveraging RGB and depth (RGB-D) cameras is proposed for solving the human blockage problem. RGB-D cameras observe mmWave communication ranges, and BS handover is conducted proactively before a human blockage causes serious performance degradation. However, this system must rely on a scheme that provides a guideline for selecting a BS to which the transfer can be done. In this paper, we propose a mmWave throughput estimation scheme using an online machine learning algorithm and depth images obtained by the RGB-D camera. The algorithm learns the relationship between depth images and measured throughputs, and estimates throughput from depth images. The scheme enables the handover system to estimate throughput quickly and adaptively to the wireless environment without transmitting any control frames. We conducted a proof-of-concept experiment by using a testbed consisting of IEEE 802.11ad mmWave wireless local area network devices and an RGB-D camera. The experiment confirmed that the proposed scheme estimates throughput from a depth image with an RMS error of 114-178 Mbit/s in real time.

This paper proposes a dynamic channel selection method for direct spectrum division transmission systems, which are autonomous decentralized control systems like CSMA/CA systems, in order to use frequency resources efficiently. In the method each terminal monitors the usage status of the whole system bandwidth, then searches for and memorizes all combinations of currently vacant channels. When the terminal transmits data it selects the combination having the lowest occupancy rate for the transmission. The method's effectiveness was confirmed in discrete event simulations with probabilistic resource sharing between terminals. The aggregate throughput improvement compared with simple random selection achieved in the simulations ranged between 2.5% and 11%.

Delay-tolerant networks (DTNs) are a promising network architecture which can provide reliable multi-hop message transmission between participating mobile nodes in an unfavorable environment that is prone to link disruption and disconnection by replicating and relaying messages without any need of physical infrastructure. Additionally, DTNs can also operate as cooperative DTNs to extend the coverage of other type of networks by carrying the messages that originate from farther away base station in a multi-hop fashion to the base station. In this paper, we focus on these cooperative DTNs and propose a novel routing scheme, ring distribution routing (RDR), that controls the replication and forwarding based on the source node surroundings. This paper also analyzes the reliability and buffer efficiency in RDR. Furthermore, we show that RDR provides the reliable and immediate message delivery in any environment through extensive computer simulations.

This paper introduces Direct Spectrum Division Transmission combined with a novel phase compensation method that offers improve frequency utilization efficiency. The proposed method divides a single-carrier modulated signal into multiple sub-spectra in the transmitter (Tx) side and assigns each sub-spectrum to an unused frequency slot. It combines them in the receiver (RX) side without phase distortion. To prevent phase discontinuity after spectrum combination due to propagation delay, we propose a novel phase compensator that estimates the phase difference between sub-spectra to compensate Rx sub-spectra; no specific frame pattern is required. A simulation shows that the degradation in required C/N is negligible. The results confirm that the proposed method realizes highly accurate phase compensation.

To develop large capacity high quality mobile satellite communication systems in the future, a multi-beam that can cope with extremely high levels of frequency reuse must be used. We describe a novel resource allocation scheme that enables systems to contend with ever-changing user distribution and inter-beam interference conditions. The proposed scheme simultaneously controls various kinds of radio resources, such as transmission power, frequency bandwidth, and modulation parameters. It adapts them to each user depending on the radio propagation environment. Our performance evaluations demonstrate that the scheme can satisfactorily allocate multi-beam satellite resources to greatly increase communication capacity and still improve the communication quality, thus ensuring QoS under various user distribution and traffic conditions.

To obtain large capacity, high quality future mobile satellite communication systems, we must use a multi-beam that has extremely high levels of frequency reuse. This paper describes a novel resource allocation scheme for multi-beam satellite communication systems that can dynamically offer maximum communication capacity without compromising quality. The scheme optimizes the frequency bandwidth, satellite transmission power, modulation level, and coding rate to each beam to deal with the ever-changing user distribution and inter-beam interference conditions. First, to minimize interference, we clarified the optimal constraint conditions when all clusters share the same bandwidth, while consuming the system bandwidth. We then used them as constraints in the optimization algorithm that allocates resources to each beam. Second, to manage the various needed resources and adapt them to the beam gain and interference levels at user locations, we propose two schemes for allocating resources within a beam. As a result, although both schemes were able to accommodate the same number of users, the fixed power with adaptive modulation secured a more stable communication quality. This means that our scheme can satisfactorily allocate multi-beam satellite resources, while increasing communication capacity and improving quality