Integrated Sensing and Communication for Intelligent Road-Traffic Management

Smart roads, where sensors provide information about traffic density, speed, etc., enable advanced traffic management tools that reduce accidents, traffic jams, and environmental damage. However, current implementations based on sensors built into the road surface are expensive, prone to mechanical damage, and have a limited lifetime. Wireless sensing, i.e., radar, promises to avoid these drawbacks, yet the construction of a completely new wireless infrastructure for this purpose is cost-prohibitive. An alluring way of avoiding these problems is the use of existing cellular 5G infrastructure, and to develop mechanisms for Integrated Sensing and Communications (ISAC), such that the radar operation can “piggyback” on the communications signals, without significantly reducing the communication data rates or otherwise wasting the precious spectrum resources. While sensing of the location of cellphone (user equipment (UE)) location by the network infrastructure nodes (base station (BS)) is commonly used today, it does not provide information about road users that do not have an active cellular connection (henceforth called Non-transmitting road users (NTRUs)). However, one can also consider a transmitting UE as a radar transmitter, such that the receiving BS can act as a radar receiver and thus determine the location of the NTRUs by extracting, with suitable processing, the signal echoes stemming from the reflection on the NTRUs. Importantly, the signals that need to be sent for communication purposes can be largely used for the radar task, thus largely preserving the spectral efficiency of the communications tasks, thus providing true ISAC. This concept of bistatic, uplink ISAC has been formulated in the past. However, the assumptions made in the existing literature are far from the constraints of the 5G standard, which any practical system must adhere to. Furthermore, they have not considered the question of joint multi-user optimization of beamforming and resource allocation. The proposed project will overcome all these issues. It will start by selecting suitable, standards Integrated Sensing and Communication for intelligent road-traffic management compliant 5G signals that can be gainfully used for radar purposes. Then it will proceed to the core challenges, which is finding a suitable joint beamforming and resource allocation for the multi-UE situation, where different UEs transmit quasi-simultaneously (though on orthogonal time-frequency resources), and are received with different beamformers by the BS. In all this, the suitable balance between retaining the performance of the communication links, and providing good radar performance, needs to be found. Finally the research team will perform channel measurements specifically designed to isolate the channel components relevant for communication, and for the sensing, and use those measurements to assess the achievable performance with the derived beamforming + resource allocation techniques. Innovation and Research Significance: the project will break new ground on the theory side, as the joint beamforming/resource allocation problem has generally been little explored, and – more importantly – is completely new for the multi-transmitter case. Formulating and solving this associated problem is thus important from a theoretical point of view. In terms of experiments, there are to the team's knowledge no existing measurements under the relevant constraints (uplink, multiple transmitters, urban environment, sub-6 GHz frequency range) that extract the contributions from NTRUs.

• Record URL:
  https://metrans.org/research/integrated-sensing-and-communication-for-intelligent-road-traffic-management

Language

• English

Project

• Status: Programmed
• Funding: $100000
• Contract Numbers:

  69A3552348309

  65A0674

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  METRANS Transportation Consortium

  University of Southern California
  Los Angeles, CA  United States 
• Project Managers:

  Hong, Jennifer

  Bruner, Britain

• Principal Investigators:

  Molisch, Andreas

• Start Date: 20250101
• Expected Completion Date: 20260630
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Cellular telephones; Data fusion; Intelligent transportation systems; Resource allocation; Traffic control; Wireless communication systems
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01928609
• Record Type: Research project
• Source Agency: Pacific Southwest Region University Transportation Center
• Contract Numbers: 69A3552348309, 65A0674
• Files: UTC, RIP
• Created Date: Aug 24 2024 11:03AM