A Material Sensing-Assisted Initial Beam Establishment Method for JCAS Systems

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.

Diagonal Waveform and Algorithm to Estimate Range and Velocity in Multi-Object Scenarios

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.

A Novel Waveform Design for OFDM-Based Joint Sensing and Communication System

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.

Map-Assisted Material Identification at 100 GHz and Above Using Radio Access Technology

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.