Information Theory (cs.IT)

Abstract: A superdirective antenna array has the potential to achieve an array gain proportional to the square of the number of antennas, making it of great value for future wireless communications. However, designing the superdirective beamformer while considering the complicated mutual-coupling effect is a practical challenge. Moreover, the superdirective antenna array is highly sensitive to excitation errors, especially when the number of antennas is large or the antenna spacing is very small, necessitating demanding and precise control over excitations. To address these problems, we first propose a novel superdirective beamforming approach based on the embedded element pattern (EEP), which contains the coupling information. The closed-form solution to the beamforming vector and the corresponding directivity factor are derived. This method relies on the beam coupling factors (BCFs) between the antennas, which are provided in closed form. To address the high sensitivity problem, we formulate a constrained optimization problem and propose an EEP-aided orthogonal complement-based robust beamforming (EEP-OCRB) algorithm. Full-wave simulation results validate our proposed methods. Finally, we build a prototype of a 5-dipole superdirective antenna array and conduct real-world experiments. The measurement results demonstrate the realization of the superdirectivity with our EEP-based method, as well as the robustness of the proposed EEP-OCRB algorithm to excitation errors.

Abstract: In this paper, we investigate the fundamental limits of MIMO-OFDM integrated sensing and communications (ISAC) systems based on a Bayesian Cram\'er-Rao bound (BCRB) analysis. We derive the BCRB for joint channel parameter estimation and data symbol detection, in which a performance trade-off between both functionalities is observed. We formulate the optimization problem for a linear precoder design and propose the stochastic Riemannian gradient descent (SRGD) approach to solve the non-convex problem. We analyze the optimality conditions and show that SRGD ensures convergence with high probability. The simulation results verify our analyses and also demonstrate a fast convergence speed. Finally, the performance trade-off is illustrated and investigated.

Abstract: We consider a gossip network consisting of a source forwarding updates and $n$ nodes placed geometrically in a ring formation. Each node gossips with $f(n)$ nodes on either side, thus communicating with $2f(n)$ nodes in total. $f(n)$ is a sub-linear, non-decreasing and positive function. The source keeps updates of a process, that might be generated or observed, and shares them with the nodes in the ring network. The nodes in the ring network communicate with their neighbors and disseminate these version updates using a push-style gossip strategy. We use the version age metric to quantify the timeliness of information at the nodes. Prior to this work, it was shown that the version age scales as $O(n^{\frac{1}{2}})$ in a ring network, i.e., when $f(n)=1$, and as $O(\log{n})$ in a fully-connected network, i.e., when $2f(n)=n-1$. In this paper, we find an upper bound for the average version age for a set of nodes in such a network in terms of the number of nodes $n$ and the number of gossiped neighbors $2 f(n)$. We show that if $f(n) = \Omega(\frac{n}{\log^2{n}})$, then the version age still scales as $\theta(\log{n})$. We also show that if $f(n)$ is a rational function, then the version age also scales as a rational function. In particular, if $f(n)=n^\alpha$, then version age is $O(n^\frac{1-\alpha}{2})$. Finally, through numerical calculations we verify that, for all practical purposes, if $f(n) = \Omega(n^{0.6})$, the version age scales as $O(\log{n})$.