In this article, the millimeter wave (mmWave) cellular-connected unmanned aerial vehicle (UAV) equipped with conformal phased array antennas in cylindrical shape is investigated, where the UAV acts as an aerial user and served by the base station (BS). Although the cylindrical conformal array (CCA)-enabled UAV can achieve the full spatial coverage and fully exploit the beam gain with directional antenna elements, the curved carrier of CA forces the cellular-connected UAV to activate only a portion of antenna elements rather than activating the entire of them to mitigate the severe aerial-ground interference from other BSs. The subarray selection problem is formulated to maximize signal-to-interference-plus-noise ratio (SINR) with non-linear antenna radiation patterns. To handle the non-linearity of objective problem, we propose a low complexity subarray selection scheme based on genetic algorithm (GA), which utilizes only the information that UAV can acquire in practical scenarios. The simulation results demonstrate that the proposed subarray selection scheme always shows higher SINR and achievable rate compared to the benchmark schemes. Specifically, the proposed subarray selection scheme shows an achievable rate that is about 2% higher than the accelerated particle swarm optimization (APSO) algorithm, and its computational complexity is only about 25%. In addition, the proposed scheme has near optimal performance while having only about 10.4% complexity compared to the optimal subarray obtained through the full search.

This paper presents the design, implementation and performance analysis of the L1 Control SW among the components of a 5G NR gNB using FAPI interface. In addition, this paper proposes HW platform and a load distribution method for each processor for real-time operation. For the implemented SW, we performed size and timing analysis of FAPI messages/CH PDUs in an actual execution environment, and it is verified that real-time operation to support downlink 8CC and uplink 1CC is possible.

While the deployment of base stations (BSs) becomes increasingly dense in order to accommodate the growth in traffic demand, these BSs may be under-utilized during most hours except peak hours. The deactivation of these under-utilized BSs is regarded as the key to reducing network power consumption; however, the remaining active BSs should increase their transmit power in order to fill network coverage holes that result from BS switching off. This paper investigates the optimal balance between such beneficial and harmful effects of BS switching off in terms of minimizing the network power consumption, through comprehensively considering the spatial BS distribution, BS transmit power, BS power consumption behaviors, radio propagation environments, and frequency reuse. The suboptimal and approximated design problems are formulated as geometric programming and the numerical results demonstrate that the proposed suboptimal solutions for the spatial density, transmit power, and frequency reuse of remaining active BSs significantly contribute to reducing the power consumption of BSs.

We propose a new contention resolution scheme designed for large scale autonomous wireless systems and fully distributed D2D (device-to-device) communications networks. The proposed contention resolution scheme is designed for scalability, efficiency, and fairness. Unlike traditional contention resolution schemes, the proposed contention resolution scheme uses idle time of channel as a measure of the channel condition. Idle time of channel is not only a much more reliable and versatile measure of channel condition than the traditional way of collision detection using ACK, it also makes it possible to use the proposed contention resolution scheme in situations where ACK is not expected such as with broadcast and multicast messages or in fully distributed synchronization procedures. The simulation study confirms that the proposed scheme exhibits high degree of scalability, efficiency, and fairness.

A low-complexity planar antenna array with antenna switching for wireless communication applications is addressed. The planar array consists of N1linear antenna arrays where each linear antenna array consists of N2receiving antennas. In each cycle, the receiving antennas on each linear antenna array are switched to the single receiving channel in turn from the 1st antenna to the N2th antenna. We first derive the Cramer-Rao lower bound (CRLB) expressions for estimating the azimuth angle, elevation angle, velocity, and range using the considered planar array. We then propose a wideband beamforming algorithm for estimation of the source parameters. The proposed algorithm called the wideband Capon beamformer uses the time-varying steering vector model.

The problem of estimating information symbols transmitted through non-Gaussian multipath CDMA wireless channels with a phased array is considered. First, a robust detector based on the minimax robust estimation theory is proposed. This proposed robust technique has a decreased sensitivity of the estimates with respect to an actually unknown distribution of random noises and interferences. Then, the estimation accuracy of information signals is analysed by Monte Carlo simulation of this direction-of-arrival estimation-based robust detector in multipath scenario.

In this paper, new robust M-estimation techniques are developed for combating impulsive noise and multiple-access interference in communication systems. Power functions of the proposed robust estimators are obtained by minimizing a nonquadratic residual function derived from the Huber's minimax robust estimation theory. Maximum peaks of these power functions are used for estimation of communication signals as well as direction of arrival. A strong advantage of the proposed robust M-estimation algorithms is a decreased sensitivity of the estimates with respect to an actual unknown distribution of random noises and interferences. Simulation results demonstrate that the proposed robust algorithms, the robust median, and robust Huber estimators, offer significant performance gain over the conventional and minimum-variance distortionless-response estimators, with the best results given by the robust Huber estimator.