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Yi Geng

Publications and source records attributed to Yi Geng.

10 recordsLinked to original sources

Sensing with Random Signals: The Role of Time Sharing

In monostatic, decision-aided, or known-waveform integrated sensing and communications (ISAC) formulations, the sensing receiver is often modeled as knowing the transmitted waveform. This assumption is not suitable for passive, bistatic, or distributed settings where the sensing receiver knows the signaling rule but not the transmitted symbols. We study such a symbol-unaware ISAC model, where sensing is measured by the unconditioned mutual information $I(S;V)$ rather than the symbol-aware quantity $I(S;V|X)$. For discrete-input memoryless channels, we characterize the capacity-sensing region through an auxiliary time-sharing variable, showing that the optimal upper boundary is the upper concave envelope of the single-mode frontier. Thus, explicit time sharing is unnecessary when the single-mode frontier is already concave, but strictly beneficial when its upper concave envelope strictly dominates the frontier. For Rayleigh-fading BPSK, we further show that the curvature of the single-mode boundary is determined by the stochastic ordering of the communication- and sensing-side effective SNR distributions. Communication-side dominance yields a concave single-mode frontier and no time-sharing gain, sensing-side dominance yields a convex single-mode frontier and a strict time-sharing gain, and equality yields a linear boundary. The result extends to SIMO-BPSK through the ordering of post-combining SNR distributions. These findings explain when symbol-unaware ISAC optimally moves from data-symbol transmission to pilot-like sensing modes.

cs.IT

Multi-Periodogram Velocity Estimation with Irregular Reference Signals for Robot-Aided ISAC

This paper addresses velocity estimation within robot-aided integrated sensing and communications (ISAC), where mobile robots act as sensing nodes but can only opportunistically reuse irregular 5G/6G reference signals (RSs). We show that the velocity profile induced by such irregular time-domain patterns can be decomposed into a periodic-peak component and an amplitude-shaping (weighting) component. Leveraging this structure, we propose a multi-periodogram velocity estimation algorithm that is standard-compliant and does not require new sensing-dedicated RSs or 3GPP modifications. Simulation results demonstrate that, compared with conventional periodogram processing, the proposed method improves low-SNR robustness by achieving a 3 dB SNR gain at the 10% missed-detection rate and reducing false alarms by 51%.

cs.RO

Grouped Pattern and Multi-Periodogram Algorithm for Range Estimation in ISAC Systems

This paper proposes a grouped pattern (GP) for sensing signals and a corresponding multi-periodogram algorithm for range estimation in integrated sensing and communications (ISAC) systems. GP partitions subcarriers into groups with an identical intra-group configuration replicated across groups, producing range profiles with periodic peaks and a structured multi-peak signature that improves low-SNR target detection. By identifying targets via cross-pattern peak validation, the proposed approach reduces missed detections and false alarms while requiring fewer dedicated sensing resources. Extensive simulations demonstrate a 16.5% extended detection range and a 61% reduced false alarm rate compared to conventional methods.

cs.IT

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.

eess.SP

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.

cs.IT

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.

cs.IT

Beyond Conic Section Mainlobe Coverage for Unmanned Aerial Vehicle

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.

cs.IT

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.

cs.IT

Joint Scatterer Localization and Material Identification Using Radio Access Technology

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.

cs.IT

AI Based Landscape Sensing Using Radio Signals

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.

cs.IT