Integrated Sensing and Communications for 3D Object Imaging via Bilinear Inference

We consider an uplink integrated sensing and communications (ISAC) scenario where the detection of data symbols from multiple user equipment (UEs) occurs simultaneously with a three-dimensional (3D) estimation of the environment, extracted from the scattering features present in the channel state information (CSI) and utilizing the same physical layer communications air interface, as opposed to radar technologies. By exploiting a discrete (voxelated) representation of the environment, two novel ISAC schemes are derived with purpose-built message passing (MP) rules for the joint estimation of data symbols and status (filled/empty) of the discretized environment. The first relies on a modular feedback structure in which the data symbols and the environment are estimated alternately, whereas the second leverages a bilinear inference framework to estimate both variables concurrently. Both contributed methods are shown via simulations to outperform the state-of-the-art (SotA) in accurately recovering the transmitted data as well as the 3D image of the environment. An analysis of the computational complexities of the proposed methods reveals distinct advantages of each scheme, namely, that the bilinear solution exhibits a superior robustness to short pilots and channel blockages, while the alternating solution offers lower complexity with large number of UEs and superior performance in ideal conditions

Soft-connected Rigid Body Localization: State-of-the-Art and Research Directions for 6G

This white paper describes a proposed article that will aim to provide a thorough study of the evolution of the typical paradigm of wireless localization (WL), which is based on a single point model of each target, towards wireless rigid body localization (W-RBL). We also look beyond the concept of RBL itself, whereby each target is modeled as an independent multi-point three-dimensional (3D), with shape enforced via a set of conformation constraints, as a step towards a more general approach we refer to as soft-connected RBL, whereby an ensemble of several objects embedded in a given environment, is modeled as a set of soft-connected 3D objects, with rigid and soft conformation constraints enforced within each object and among them, respectively. A first intended contribution of the full version of this article is a compact but comprehensive survey on mechanisms to evolve WL algorithms in W-RBL schemes, considering their peculiarities in terms of the type of information, mathematical approach, and features the build on or offer. A subsequent contribution is a discussion of mechanisms to extend W-RBL techniques to soft-connected rigid body localization (SCW-RBL) algorithms

AFDM vs OTFS: A Comparative Study of Promising Waveforms for ISAC in Doubly-Dispersive Channels

This white paper aims to briefly describe a proposed article that will provide a thorough comparative study of waveforms designed to exploit the features of doubly-dispersive channels arising in heterogeneous high-mobility scenarios as expected in the beyond fifth generation (B5G) and sixth generation (6G), in relation to their suitability to integrated sensing and communications (ISAC) systems. In particular, the full article will compare the well-established delay-Doppler domain-based orthognal time frequency space (OTFS) and the recently proposed chirp domain-based affine frequency division multiplexing (AFDM) waveforms. Both these waveforms are designed based on a full delay- Doppler representation of the time variant (TV) multipath channel, yielding not only robustness and orthogonality of information symbols in high-mobility scenarios, but also a beneficial implication for environment target detection through the inherent capability of estimating the path delay and Doppler shifts, which are standard radar parameters. These modulation schemes are distinct candidates for ISAC in B5G/6G systems, such that a thorough study of their advantages, shortcomings, implications to signal processing, and performance of communication and sensing functions are well in order. In light of the above, a sample of the intended contribution (Special Issue paper) is provided below

A Rate Splitting Multiple Access Interface for Clustered Wireless Federated Learning

Consider a wireless federated learning (WFL) system where the edge devices (EDs) performing local training are closely located in a cluster, such that in addition to their private model updates, a locally common (a.k.a. consensus) model can be computed or selected at each cycle of the learning process. For such a clustered WFL (CWFL) paradigm, we design an uplink (UL) radio access scheme based on the rate splitting multiple access (RSMA) architecture, which is shown not only to significantly reduce the latency of WFL in comparison to systems employing time-domain multiple access (TDMA) and nonorthogonal multiple access (NOMA), but also to be more energy efficient, reaching a lower latency with less power than the latter alternatives. To that end, we exploit the cluster-wide consensus model as the common message used to construct the common component of the RSMA scheme and build an optimization problem aimed at minimizing the latency of each CWFL round by means of optimally allocating the corresponding computation times and uplink transmission durations of each ED, taking into account constraints such as energy consumption, data rates and computational capabilities of each ED. By adequately setting a system parameter referred to as the rate-splitting factor, the formulation also applies to systems employing conventional TDMA or NOMA methods, such that the proposed technique can be seen as a generalization of those approaches, in the context of CWFL schemes. Simulation results on the proposed RSMA-interfaced UL scheme for CWFL are given, both with and without the incorporation of optimal NOMA decoding at the base station (BS), the first of which is found to yield only a mild improvement over the latter, indicating that the proposed approach is in fact the key factor in the overall latency reduction achieved

Sparse Codesigned Communication and Radar Systems

In the envisioned beyond-fifth-generation (B5G) and sixth-generation (6G) scenarios which expect massive multiple-input multiple-output (mMIMO) and high frequency communications in the millimeter-wave (mmWave) and Terahertz (THz) bands, efficiency in both energy and spectrum is of increasing significance. To that extent, a novel ISAC framework called "sparse codesigned communication and radar (SCCR)" systems is described, which codesigns both communication and radar signals by a sparsification of the resource domain and the waveform spectrum domain. This improves the spectral and energy efficiency, but at the inherent cost of missing radar spectrum and irregular beampattern, and decreased throughput and diversity. Such challenges can however be corroborated, by leveraging various sparsity-robust signal processing techniques such as sparse radar reconstruction and index modulation (IM). In light of the above, the white paper aims to outlined the proposed article which provide an overview and a novel classification of the relevant state-of-the-art (SotA) methods and the implications of the challenges in the sparse codesign of the system, followed by a variety of novel SCCR frameworks