4K/8K satellite broadcasting featuring ultra-high definition video and sound was launched in Japan in 2018. This is the first 8K ultra high definition television (UHDTV) broadcasting in the world, with 16 times as many pixels as HDTV and 3D sound with 22.2ch audio. The large amount of information that has to be transmitted means that a new satellite broadcasting transmission system had to be developed. In this paper, we describe this transmission system, focusing on the technology that enables 4K/8K UHDTV satellite broadcasting.

A spectrum suppressed transmission that increases the frequency utilization efficiency, defined as throughput/bandwidth, by suppressing the required bandwidth has been proposed. This is one of the most effective schemes to solve the exhaustion problem of frequency bandwidths. However, in spectrum suppressed transmission, its transmission quality potentially degrades due to the ISI making the bandwidth narrower than the Nyquist bandwidth. In this paper, in order to improve the transmission quality degradation, we propose the spectrum suppressed transmission applying both FEC (forward error correction) and LE (linear equalization). Moreover, we also propose a new channel allocation scheme for the spectrum suppressed transmission, in multi-channel environments over a satellite transponder. From our computer simulation results, we clarify that the proposed schemes are more effective at increasing the system throughput than the scheme without spectrum suppression.

In the typical unmanned aircraft system (UAS), several unmanned aerial vehicles (UAVs) traveling at a velocity of 40-100km/h and with altitudes of 150-1,000m will be used to cover a wide service area. Therefore, Doppler shifts occur in the carrier frequencies of the transmitted and received signals due to changes in the line-of-sight velocity between the UAVs and the terrestrial terminal. By observing multiple Doppler shift values for different UAVs or observing a single UAV at different local times, it is possible to detect the user position on the ground. We conducted computer simulations for evaluating user position detection accuracy and Doppler shift distribution in several flight models. Further, a positioning accuracy index (PAI), which can be used as an index for position detection accuracy, was proposed as the absolute value of cosine of the inner product between two gradient vectors formed by Doppler shifts to evaluate the relationship between the location of UAVs and the position of the user. In this study, a maximum positioning error estimation method related to the PAI is proposed to approximate the position detection accuracy. Further, computer simulations assuming a single UAV flying on the curved routes such as sinusoidal routes with different cycles are conducted to clarify the effectiveness of the flight route in the aspects of positioning accuracy and latency by comparing with the conventional straight line fight model using the PAI and the proposed maximum positioning error estimation method.

In this paper, we propose a radio frequency (RF) anti-aliasing filter design method considering the effect of a roll-off characteristic on a noise figure (NF) in the direct RF undersampling receiver. The proposed method is useful for broadband reception that a system bandwidth (BW) has nearly half of the sampling frequency (1/2 f_s). When the system BW is extended nearly 1/2 f_s, the roll-off band is out of the desired Nyquist zone and it affects NF additionally. The proposed method offers a design target regarding the roll-off characteristic not only the rejection ratio. The target is helpful as a design guide to meet the allowed NF. We design the filter based on the proposed method and it is applied to the direct RF undersampling on-board receiver for Ka-band high throughput satellite (HTS). The measured NF value of the implemented receiver almost matched the designed value. Moreover, the receiver achieved the reception bandwidth which is 90% of 1/2 f_s.

Radio frequency energy transfer (RET) technology has been introduced as a promising energy harvesting (EH) method to supply power in both wireless communication (WLC) and power-line communication (PLC) systems. However, current RET modified MAC (medium access control) protocols have been proposed only for WLC systems. Due to the difference in the MAC standard between WLC and PLC systems, these protocols are not suitable for PLC systems. Therefore, how to utilize RET technology to modify the MAC protocol of PLC systems (i.e., IEEE 1901), which can use the radio frequency signal to provide the transmission power and the PLC medium to finish the data transmission, i.e., realizing the ‘cooperative communication’ remains a challenge. To resolve this problem, we propose a RET modified MAC protocol for PLC systems (RET-PLC MAC). Firstly, we improve the standard PLC frame sequence by adding consultation and confirmation frames, so that the station can obtain suitable harvested energy, once it occupied the PLC medium, and the PLC system can be operated in an on-demand and self-sustainable manner. On this basis, we present the working principle of RET-PLC MAC. Then, we establish an analytical model to allow mathematical verification of RET-PLC MAC. A 2-dimension discrete Markov chain model is employed to derive the numerical analysis results of RET-PLC MAC. The impacts of buffer size, traffic rate, deferral counter process of 1901, heterogeneous environment and quality of information (QoI) are comprehensively considered in the modeling process. Moreover, we deduce the optimal results of system throughput and expected QoI. Through extensive simulations, we show the performance of RET-PLC MAC under different system parameters, and verify the corresponding analytical model. Our work provides insights into realizing cooperative communication at PLC's MAC layer.

To tackle the distributed power optimization problems in wireless sensor networks localization systems, we model the problem as a hierarchical game, i.e. a multi-leader multi-follower Stackelberg game. Existing researches focus on the power allocation of anchor nodes for ranging signals or the power management of agent nodes for cooperative localization, individually. However, the power optimizations for different nodes are indiscerptible due to the common objective of localization accuracy. So it is a new challenging task when the power allocation strategies are considered for anchor and agent nodes simultaneously. To cope with this problem, a hierarchical game is proposed where anchor nodes are modeled as leaders and agent nodes are modeled as followers. Then, we prove that games of leaders and followers are both potential games, which guarantees the Nash equilibrium (NE) of each game. Moreover, the existence of Stackelberg equilibrium (SE) is proved and achieved by the best response dynamics. Simulation results demonstrate that the proposed algorithm can have better localization accuracy compared with the decomposed algorithm and uniform strategy.

In this paper, we propose a user-assisted QoS control scheme that utilizes media adaptive buffering to enhance QoE of audiovisual and haptic IP communications. The scheme consists of two modes: a manual mode and an automatic mode. It enables users to switch between these two modes according to their inclinations. We compare four QoS control schemes: the manual mode only, the automatic mode only, the switching scheme starting with the manual mode, and the switching scheme starting with the automatic mode. We assess the effects of the four schemes, user attributes, and tasks on QoE through a subjective experiment which provides information on users' behavior in addition to QoE scores. As a result of the experiment, we show that the user-assisted QoS control scheme can enhance QoE. Furthermore, we notice that the proper QoS control scheme depends on user attributes and tasks.

Road traffic collisions are an extremely serious and often fatal issue. One promising approach to mitigate such collisions is the use of connected car services that share road traffic information obtained from vehicles and cameras over mobile networks. In connected car services, it is important for data chunks to arrive at a destination node within a certain deadline constraint. In this paper, we define a flow from a vehicle (or camera) to the same vehicle (or camera) via an MEC server, as a mission critical (MC) flow, and call a deadline of the MC flow the MC deadline. Our research objective is to achieve a higher arrival ratio within the MC deadline for the MC flow that passes through both the radio uplink and downlink. We previously developed a deadline-aware scheduler with consideration for quality fluctuation (DAS-QF) that considers chunk size and a certain deadline constraint in addition to radio quality and utilizes these to prioritize users such that the deadline constraints are met. However, this DAS-QF does not consider that the congestion levels of evolved NodeB (eNB) differ depending on the eNB location, or that the uplink congestion level differs from the downlink congestion level in the same eNB. Therefore, in the DAS-QF, some data chunks of a MC flow are discarded in the eNB when they exceed either the uplink or downlink deadline in congestion, even if they do not exceed the MC deadline. In this paper, to reduce the eNB packet drop probability due to exceeding either the uplink and downlink deadline, we propose a deadline coordination function (DCF) that adaptively sets each of the uplink and downlink deadlines for the MC flow according to the congestion level of each link. Simulation results show that the DAS-QF with DCF offers higher arrival ratios within the MC deadline compared to DAS-QF on its own

Direction of arrival (DOA) estimation of wireless signals has a long history but is still being investigated to improve the estimation accuracy. Non-linear algorithms such as compressed sensing are now applied to DOA estimation and achieve very high performance. If the large computational loads of compressed sensing algorithms are acceptable, it may be possible to apply a deep neural network (DNN) to DOA estimation. In this paper, we verify on-grid DOA estimation capability of the DNN under a simple estimation situation and discuss the effect of training data on DNN design. Simulations show that SNR of the training data strongly affects the performance and that the random SNR data is suitable for configuring the general-purpose DNN. The obtained DNN provides reasonably high performance, and it is shown that the DNN trained using the training data restricted to close DOA situations provides very high performance for the close DOA cases.

Intersymbol interference (ISI) is a significant source of degradation in many digital communication systems including our proposed non-far region communication system using large array antennas in the millimeter-wave band in which the main cause of ISI can be attributed to the path delay differences among the elements of an array antenna. This paper proposes a quantitative method to evaluate the ISI estimated from the measured near-field distribution of the array antenna. The influence of the uniformity in the aperture field distribution in ISI is discussed and compared with an ideally uniform excitation. The reliability of the proposed method is verified through a comparison with another method based on direct measurements of the transmission between the actual antennas. Finally, the signal to noise plus interference is evaluated based on the estimated ISI results and ISI is shown to be the dominant cause of the degradation in the reception zone of the system.

This paper presents a weighted spatial filter (WSF) design method based on direction of arrival (DOA) estimates for a novel array configuration called a sum and difference composite co-array. A sum and difference composite co-array is basically a combination of sum and difference co-arrays. Our configuration can realize higher degrees of freedom (DOF) with the sum co-array part at a calculation cost lower than those of the other sparse arrays. To further enhance the robustness of our proposed sum and difference composite co-array we design an optimal beam pattern by WSF based on the information of estimated DOAs. Performance of the proposed system and the DOA estimation accuracy of close-impinging waves are evaluated through computer simulations.

One of key technologies in the fifth generation mobile communications is a distributed antenna system (DAS). As DAS creates tightly packed antenna arrangements, inter-user interference degrades its spectrum efficiency. Round-robin (RR) scheduling is known as a scheme that achieves a good trade-off between computational complexity and spectrum efficiency. This paper proposes a user equipment (UE) allocation scheme for RR scheduling. The proposed scheme offers low complexity as the phase of UE allocation sequences are predetermined. Four different phase selection criteria are compared in this paper. Numerical results obtained through computer simulation show that maximum selection, which sequentially searches for the phase with the maximum tentative throughput realizes the best spectrum efficiency next to full search. There is an optimum number of UEs which obtains the largest throughput in single-user allocation while the system throughput improves as the number of UEs increases in 2-user RR scheduling.

This paper proposes a deterministic pilot pattern placement optimization scheme based on the quantum genetic algorithm (QGA) which aims to improve the performance of sparse channel estimation in orthogonal frequency division multiplexing (OFDM) systems. By minimizing the mutual incoherence property (MIP) of the sensing matrix, the pilot pattern placement optimization is modeled as the solution of a combinatorial optimization problem. QGA is used to solve the optimization problem and generate optimized pilot pattern that can effectively avoid local optima traps. The simulation results demonstrate that the proposed method can generate a sensing matrix with a smaller MIP than a random search or the genetic algorithm (GA), and the optimized pilot pattern performs well for sparse channel estimation in OFDM systems.

In this paper, we propose a decentralized probabilistic frequency-block activation control method for the cellular downlink. The aim of the proposed method is to increase the downlink system throughput within the system coverage by adaptively controlling the individual activation of each frequency block at all base stations (BSs) to achieve inter-cell interference coordination (ICIC) and traffic load balancing. The proposed method does not rely on complicated inter-BS cooperation. It uses only the inter-BS information exchange regarding the observed system throughput levels with the neighboring BSs. Based on the shared temporal system throughput information, each BS independently controls online the activation of their respective frequency blocks in a probabilistic manner, which autonomously achieves ICIC and load balancing among BSs. Simulation results show that the proposed method achieves greater system throughput and a faster convergence rate than the conventional online probabilistic activation/deactivation control method. We also show that the proposed method successfully tracks dynamic changes in the user distribution generated due to mobility.