Superposition of PRS and PDSCH for ISAC System: Spectral Efficiency Enhancement and Range Ambiguity Elimination

From the telecommunication companies' perspective, the preference for integrated sensing and communication (ISAC) for sixth-generation (6G) is to enhance existing infrastructure with sensing capabilities while minimizing network alterations and optimizing available resources. This prompts the investigation of ISAC leveraging the existing infrastructure of fifth-generation (5G) new radio (NR) signals as defined by the 3rd generation partnership project (3GPP). Additionally, improving spectral efficiency is crucial in scenarios with high demand for both communication and sensing applications to maintain the required quality of service (QoS). To address these challenges, we propose the superposition of the physical downlink shared channel (PDSCH) for communication and the positioning reference signal (PRS) for sensing with proper power allocation. Furthermore, we propose a novel algorithm to reduce the interference for data decoding caused by PRS. Moreover, we introduce the joint exploitation of PRS and demodulation reference signal (DMRS) to prevent range ambiguity in the form of ghost targets. Through simulation analysis, we demonstrate the effectiveness of integrating PDSCH and PRS symbols within a unified resource grid. Our results show that the introduced approaches not only eliminate range ambiguity when sensing targets from gNBs but also enhance spectral efficiency by reducing interference between PRS and PDSCH. Simulation results show throughput enhancement and up to 57% improvement in bit error rate (BER). This paves the way for supporting sensing applications in the forthcoming network generation.

Doppler Ambiguity Elimination Using 5G Signals in Integrated Sensing and Communication

The industrial point of view towards integrated sensing and communication (ISAC), the preference is to leverage existing resources and fifth-generation (5G) infrastructure to minimize deployment costs and complexity. In this context, we explore the utilization of current 5G new radio (NR) signals aligned with 3rd generation partnership project (3GPP) standards. Positioning reference signals (PRS) for sensing and physical downlink shared channel (PDSCH) for communication have been chosen to form an ISAC framework. However, PRS-based sensing suffers from Doppler ambiguity when the Doppler frequency shift is severe. To address this challenge, we introduce a novel method within the ISAC system that leverages the demodulation reference signal (DMRS) present in PDSCH to eliminate Doppler ambiguity. Furthermore, we formulate a resource allocation problem between PRS and PDSCH to achieve a Pareto optimal point between communication and sensing without Doppler ambiguity. Through simulations and analysis, we demonstrate the effectiveness of our proposed method on joint DMRS-PRS exploitation in mitigating Doppler ambiguity and the efficiency of the resource allocation scheme in achieving Pareto optimality for ISAC within a 5G NR framework.

Leveraging PRS and PDSCH for Integrated Sensing and Communication Systems

From the industrial standpoint on integrated sensing and communication (ISAC), the preference lies in augmenting existing infrastructure with sensing services while minimizing network changes and leveraging available resources. This paper investigates the potential of utilizing the existing infrastructure of fifth-generation (5G) new radio (NR) signals as defined by the 3rd generation partnership project (3GPP), particularly focusing on pilot signals for sensing within the ISAC framework. We propose to take advantage of the existing positioning reference signal (PRS) for sensing and the physical downlink shared channel (PDSCH) for communication, both readily available in 5G NR. However, the use of PRS for sensing poses challenges, leading to the appearance of ghost targets. To overcome this obstacle, we propose two innovative approaches for different PRS comb sizes within the ISAC framework, leveraging the demodulation reference signal (DMRS) within PDSCH to eliminate ghost targets. Subsequently, we formulate a resource allocation problem between PRS and PDSCH and determine the Pareto optimal point between communication and sensing without ghost targets. Through comprehensive simulation and analysis, we demonstrate that the joint exploitation of DMRS and PRS offers a promising solution for ghost target removal, while effective time and frequency resource allocation enables the achievement of Pareto optimality in ISAC.