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Communication systems operating at high frequency bands must use narrow beams to compensate the high path loss. However, it is incredibly time-consuming to achieve beam alignment between the transmitter and receiver due to the large volume of beam space with narrow beams. The high latency of initial beam establishment will challenge the implementation of future 6G networks at high frequency bands. To tackle this problem, this paper proposes an initial beam establishment method using the material sensing results from joint communications and sensing (JCAS) systems. The reflection loss (RL) induced by each reflector can be predicted by exploiting the pre-identified material information of reflectors in the environment. The base station (BS) first scans the beam directions with low RL and establishes the connection immediately without sweeping the rest of the beam directions. In this way, the latency of initial beam establishment is significantly reduced., Comment: Submitted to ICC2024 workshop

Waveform design for joint communication and sensing (JCAS) is an important research direction, focusing on providing an optimal tradeoff between communication and sensing performance. In this paper, we first describe the conventional grid-type waveform structure and the corresponding two-dimension (2D)-discrete Fourier transform (DFT) algorithm. We then introduce an emerging diagonal scheme, including a diagonal waveform structure and corresponding 1D-DFT diagonal algorithm. The diagonal scheme substantially reduces the signaling overhead and computational complexity compared to the conventional 2D-DFT algorithm while still achieving the same radar performance. But the previous study of diagonal waveform used a single target to evaluate the performance of the diagonal scheme. This paper verifies the diagonal waveform with simulations demonstrating its feasibility in a traffic monitoring scenario with multiple vehicles., Comment: This paper has been accepted by 97th Vehicular Technology Conference, 2023

The dominating waveform in 5G is orthogonal frequency division multiplexing (OFDM). OFDM will remain a promising waveform candidate for joint communication and sensing (JCAS) in 6G since OFDM can provide excellent data transmission capability and accurate sensing information. This paper proposes a novel OFDM-based diagonal waveform structure and corresponding signal processing algorithm. This approach allocates the sensing signals along the diagonal of the time-frequency resource block. Therefore, the sensing signals in a linear structure span both the frequency and time domains. The range and velocity of the object can be estimated simultaneously by applying 1D-discrete Fourier transform (DFT) to the diagonal sensing signals. Compared to the conventional 2D-DFT OFDM radar algorithm, the computational complexity of the proposed algorithm is low. In addition, the sensing overhead can be substantially reduced. The performance of the proposed waveform is evaluated using simulation and analysis of results., Comment: 3rd IEEE International Symposium on Joint Communications & Sensing (JC&S 2023), accepted and to be published

The cellular-connected drone market is one of the most promising markets of 5G. However, it still accounts for a small share of overall telecommunication market, and it is unlikely to increase significantly for the foreseeable future. Deploying dedicated network with up-tilted antennas can be an option, but the monetary cost of dedicated network directly impacts the acceptance of mobile operators. Therefore, cost-efficient aerial coverage solutions must be developed. Reusing network for terrestrial coverage is a cost-efficient approach for aerial coverage, but several critical challenges caused by antenna sidelobe should be solved. In this paper, a novel method for aerial coverage is proposed. By tweaking the measurement report handling mechanism, signals from sidelobes reported by drones above the predefined height can be identified and ignored. Simulation results show that the conventional cellular network with the proposed method can provide wide and continuous aerial coverage with satisfactory quality., Comment: 6 pages, submitted to Globecom 2022

The inclusion of material identification in wireless communication system is an emerging area that offers many opportunities for 6G systems. By using reflected radio wave to determine the material of reflecting surface, not only the performance of 6G networks can be improved, but also some exciting applications can be developed. In this paper, we recap a few prior methods for material identification, then analyze the impact of thickness of reflecting surface on reflection coefficient and present a new concept "settling thickness", which indicates the minimum thickness of reflecting surface to induce steady reflection coefficient. Finally, we propose a novel material identification method based on ray-tracing and 3D-map. Compared to some prior methods that can be implemented in single-bounce-reflection scenario only, we extend the capability of the method to multiple-bounce-reflection scenarios., Comment: Submitted to EUCNC & 6G Summit 2022, 6 pages

Cellular network technologies and radar sensing technologies have been developing in parallel for decades. Instead of developing two individual technologies, the 6G cellular network is expected to naturally support both communication and radar functionalities with shared hardware and carrier frequencies. In this regard, radio access technology (RAT)-based scatterer localization system is one of the important aspects of joint communication and sensing system (JCAS) that uses communication signals between transceivers to determine the location of scatterers in and around the propagation paths. In this article, we first identify the challenges of RAT-based scatterer localization system, then present single- and multiple-bounce reflection loss (RL) simulation results for three common building materials in indoor environments. We also propose two novel methods to jointly localize and identify the type of the scatterers in a rich scattering environment., Comment: 11 pages, submitted to Special Issue "Wireless Technologies towards 6G" of the EURASIP Journal on Wireless Communications and Networking

In many sensing applications, typically radio signals are emitted by a radar and from the bounced reflections of the obstacles, inference about the environment is made. Even though radars can be used to sense the landscapes around the user-equipment (UE) such as whether UE is in the forested region, inside buildings, etc., it is not suitable in many wireless applications as many UEs does not have radars in them. Using radar will also increase the cost and power requirements on the UEs in applications requiring sensing of the landscapes. In this paper, we provide a mechanism where basestation (BS) is able to sense the UE's landscape without the use of a radar. We propose an artificial intelligence (AI) based approach with suitable choice of the features derived from the wireless channel to infer the landscape of the UEs. Results for the proposed methods when applied to practical environments such as London city scenario yields a precision score of more than 95 percent., Comment: 5 Pages, Submitted to IEEE PIMRC 2021