This paper investigates the design of integrated detection and communication waveforms with a particular focus on the exploitation of constructive interference (CI) at both the system and symbol levels. We formulate a waveform design problem with the objective of optimizing the detection performance which is characterized by the Kullback Leibler distance (KLD) between the probability density functions (PDFs) under two hypotheses, subject to the constraints of the CI condition and constant modulus. To address the challenging non-convex problem, a low-complexity recursive penalty-based Riemannian conjugate gradient (RE-PRCG) algorithm is proposed. The numerical results demonstrate the effectiveness of the proposed algorithm in improving the detection performance and reducing the computational burden over the benchmark.

This paper proposes a novel reconfigurable intelligent surface (RIS)-aided integrated communication and positioning design for orthogonal frequency division multiplexing systems in indoor scenarios. A non-geometric strategy is employed to realize accurate positioning. Specifically, location-related information is embedded into channel frequency responses (CFR) and estimated through regular pilot subcarriers. The coefficients of RIS are optimized to maximize the norm of the CFR vector differences among users, exclusively considering physically adjacent users. To enhance positioning accuracy, we propose a two-stage framework that incorporates the prior information about the user in physical space. A unique feature, named “correlation dispersion”, within this framework is leveraged to enhance performance compared to geometric-based methods. By transforming the geometric prior information into the frequency domain capitalizing on Gaussian kernel method, we derive the Cramer-Rao Lower Bound (CRLB) of the proposed framework. A notable gain in CRLB is observed, highlighting the efficacy. Theoretical comparison with the CRLB of conventional methods validates the correlation dispersion property. Simulation results demonstrate a significant improvement in positioning accuracy when meticulously combining prior information with a non-geometric positioning method. Furthermore, our results unveil that the incorporation of rough positioning methods yields exceptionally high positioning performance, provided that the location information depicts different aspects.

This paper investigates an integrated communication and positioning (ICAP) system facilitated by rate-splitting multiple access (RSMA). We propose encoding part of users’ messages into a common stream using a public codebook, which simultaneously facilitates fingerprint-based positioning. To enhance positioning accuracy, we investigate the interplay between geometric and non-geometric spatial consistency, which intriguingly leads to improved quality of imperfect channel state information (ICSI). In particular, we establish a novel strategy to significantly reduce the minimum mean square error of channel estimation via the Bayes pooling principle. We also demonstrate the theoretical equivalence between ICSI enhancement and positioning accuracy. Moreover, we develop a progressive transmission protocol that minimizes training overhead alongside ICSI enhancement strategy while allowing for the reallocation of spare resources without compromising designed performance. Our cooperative ICAP system leverages both reconfigurable intelligent surface and transmit precoding techniques to reconfigure the spatial consistency of the propagation space. Numerical results underscore advantages of proposed system in achieving the broadest Pareto boundary among existing ICAP designs. Furthermore, we reveal that RSMA bolsters communication capabilities while the ICSI enhancement strategy predominantly augments positioning.

This paper investigates the cooperative integrated communication and positioning (ICAP) within multiple-input single-output (MISO) systems. A novel strategy that leverages positioning outcomes is presented to enhance the quality of imperfect channel state information (ICSI), thereby bridging these two functionalities. Initially, a fingerprint-based method is developed to establish positioning function with the channel frequency responses serving as identification features. We focus on the interplay of geometric and non-geometric spatial consistency to improve positioning accuracy. To this end, reconfigurable intelligent surface (RIS) and transmit precoding techniques are employed to promote the non-geometric spatial consistency while ensuring communication quality. Moreover, we refine the distribution of random channel uncertainty through the Bayes pooling principle by leveraging the reshaped spatial consistency, resulting in an updated ICSI covariance matrix. This refinement is proven to significantly enhance the quality of ICSI, as evidenced by a reduction in the minimum mean square error. Furthermore, the study introduces a progressive transmission protocol that reduces training overhead in line with the channel enhancement strategy. Numerical results validate that the proposed protocol enhances the accuracy positioning by adjusting the power allocation without compromising the performance of communication. Moreover, opting for overhead reduction rather than directly utilizing enhanced ICSI quality demonstrates superior communication performance.

The performance of wireless communication systems is fundamentally constrained by random and uncontrollable wireless channels. Recently, reconfigurable intelligent surfaces (RIS) has emerged as a promising solution to enhance wireless network performance by smartly reconfiguring the radio propagation environment. While significant research has been conducted on RIS-assisted wireless systems, this paper focuses specifically on the deployment of RIS in a wideband millimeter wave (mmWave) multiple-input-multiple-output (MIMO) system to achieve maximum sum-rate. First, we derive the average user rate as well as the lower bound rate when the covariance of the channel follows the Wishart distribution. Based on the lower bound of users’ rate, we propose a heuristic method that transforms the problem of optimizing the RIS’s orientation into maximizing the number of users served by the RIS. Simulation results show that the proposed RIS deployment strategy can effectively improve the sum-rate. Furthermore, the performance of the proposed RIS deployment algorithm is only approximately 7.6% lower on average than that of the exhaustive search algorithm.