Integrated Sensing and Communication: Joint Pilot and Transmission Design

TL;DR

The paper tackles joint sensing and communication in an ISAC system by optimizing pilot design and downlink transmission within a two-stage coherence interval. It jointly designs the pilot matrix and transmit beamforming to maximize target-detection probability while meeting a minimum user rate, using an information-theoretic MI criterion to balance channel-estimation accuracy (MSE) and sensing information (MI). A nonunitary pilot structure is proposed for channel-estimation emphasis, alongside a unitary, equal-power pilot design for sensing emphasis; a block-coordinate descent framework and brute-force search over training length enable practical optimization. The results demonstrate significant improvements in MSE-MI and Rate-MI regions compared to benchmarks, with larger gains when the communication channel is more spatially correlated. The work advances ISAC by revealing pilot-structure–tradeoffs and providing a scalable algorithm that jointly optimizes pilot sequences, training duration, and beamforming to enhance both detection probability and communication throughput.

Abstract

This paper studies a communication-centric integrated sensing and communication (ISAC) system, where a multi-antenna base station (BS) simultaneously performs downlink communication and target detection. A novel target detection and information transmission protocol is proposed, where the BS executes the channel estimation and beamforming successively and meanwhile jointly exploits the pilot sequences in the channel estimation stage and user information in the transmission stage to assist target detection. We investigate the joint design of pilot matrix, training duration, and transmit beamforming to maximize the probability of target detection, subject to the minimum achievable rate required by the user. However, designing the optimal pilot matrix is rather challenging since there is no closed-form expression of the detection probability with respect to the pilot matrix. To tackle this difficulty, we resort to designing the pilot matrix based on the information-theoretic criterion to maximize the mutual information (MI) between the received observations and BS-target channel coefficients for target detection. We first derive the optimal pilot matrix for both channel estimation and target detection, and then propose an unified pilot matrix structure to balance minimizing the channel estimation error (MSE) and maximizing MI. Based on the proposed structure, a low-complexity successive refinement algorithm is proposed. Simulation results demonstrate that the proposed pilot matrix structure can well balance the MSE-MI and the Rate-MI tradeoffs, and show the significant region improvement of our proposed design as compared to other benchmark schemes. Furthermore, it is unveiled that as the communication channel is more correlated, the Rate-MI region can be further enlarged.

Figures (9)

• Figure 1: A communication-centric ISAC system.
• Figure 2: Target detection and information transmission protocol.
• Figure 3: MSE-MI region for the different length of pilot sequences $L$ under $\delta _g^2 = - 90~{\rm dBm}$.
• Figure 4: MSE-MI region comparison for different pilot design approaches under $L=8$ and $\delta _g^2 = - 90~{\rm dBm}$.
• Figure 5: Rate-MI region comparison for different pilot design approaches under $\delta _g^2 = - 100~{\rm dBm}$ and ${P_{{\rm{ave}}}} = 40~{\rm dBm}$.