Information Theory (cs.IT)

Abstract: By integrating a nearly infinite number of reconfigurable elements into a finite space, a spatially continuous array aperture is formed for holographic multiple-input multiple-output (HMIMO) communications. This three-part tutorial aims for providing an overview of the latest advances in HMIMO communications. As Part I of the tutorial, this letter first introduces the fundamental concept of HMIMO and reviews the recent progress in HMIMO channel modeling, followed by a suite of efficient channel estimation approaches. Finally, numerical results are provided for demonstrating the statistical consistency of the new HMIMO channel model advocated with conventional ones and evaluating the performance of the channel estimators. Parts II and III of the tutorial will delve into the performance analysis and holographic beamforming, and detail the interplay of HMIMO with emerging technologies.

Abstract: As Part II of a three-part tutorial on holographic multiple-input multiple-output (HMIMO), this Letter focuses on the state-of-the-art in performance analysis and on holographic beamforming for HMIMO communications. We commence by discussing the spatial degrees of freedom (DoF) and ergodic capacity of a point-to-point HMIMO system, based on the channel model presented in Part I. Additionally, we also consider the sum-rate analysis of multi-user HMIMO systems. Moreover, we review the recent progress in holographic beamforming techniques developed for various HMIMO scenarios. Finally, we evaluate both the spatial DoF and the channel capacity through numerical simulations.

Abstract: Holographic multiple-input multiple-output (HMIMO) technology, which uses spatially continuous surfaces for signal transmission and reception, is envisioned to be a promising solution for improving the data rate and coverage of wireless networks. In Parts I and II of this three-part tutorial on HMIMO communications, we provided an overview of channel modeling and highlighted the state-of-the-art in holographic beamforming. In this part, we will discuss the unique properties of HMIMO systems, highlighting the open challenges and opportunities that arise as the transceiver array apertures become denser and electromagnetically larger. Additionally, we explore the interplay between HMIMO and other emerging technologies in next-generation networks.

Abstract: We study the problem of decentralized power allocation in a multi-access channel (MAC) with non-cooperative users, additive noise of arbitrary distribution and a generalized power constraint, i.e., the transmit power constraint is modeled by an upper bound on $\mathbb{E}[\phi(|S|)]$, where $S$ is the transmit signal and $\phi(.)$ is some non-negative, increasing and bounded function. The generalized power constraint captures the notion of power for different wireless signals such as RF, optical, acoustic, etc. We derive the optimal power allocation policy when there a large number of non-cooperative users in the MAC. Further, we show that, once the number of users in the MAC crosses a finite threshold, the proposed power allocation policy of all users is optimal and remains invariant irrespective of the actual number of users. We derive the above results under the condition that the entropy power of the MAC, $e^{2h(S)+c}$, is strictly convex, where $h(S)$ is the maximum achievable entropy of the transmit signal and $c$ is a finite constant corresponding to the entropy of the additive noise.

Abstract: With increasing availability of spectrum in the market due to new spectrum allocation and re-farming bands from previous cellular generation networks, a more flexible, efficient and green usage of the spectrum becomes an important topic in 5G-Advanced. In this article, we provide an overview on the 3rd Generation Partnership Project (3GPP) work on flexible spectrum orchestration for carrier aggregation (CA). The configuration settings, requirements and potential specification impacts are analyzed. Some involved Release 18 techniques, such as multi-cell scheduling, transmitter switching and network energy saving, are also presented. Evaluation results show that clear performance gain can be achieved by these techniques.

Abstract: This paper investigates the resource allocation problem combined with fronthaul precoding and access link sparse precoding design in cloud radio access network (C-RAN) wireless fronthaul systems.Multiple remote antenna units (RAUs) in C-RAN systems can collaborate in a cluster through centralized signal processing to realize distributed massive multiple-input and multiple-output (MIMO) systems and obtain performance gains such as spectrum efficiency and coverage.Wireless fronthaul is a flexible, low-cost way to implement C-RAN systems, however, compared with the fiber fronthaul network, the capacity of wireless fronthaul is extremely limited.Based on this problem, this paper first design the fronthaul and access link precoding to make the fronthaul capacity of RAUs match the access link demand.Then, combined with the precoding design problem, the allocation optimization of orthogonal resources is studied to further optimize the resource allocation between fronthaul link and access link to improve the performance of the system.Numerical results verify the effectiveness of the proposed precoding design and resource allocation optimization algorithm.

Abstract: A future millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) system may serve hundreds or thousands of users at the same time; thus, research on multiple access technology is particularly important.Moreover, due to the short-wavelength nature of a mmWave, large-scale arrays are easier to implement than microwaves, while their directivity and sparseness make the physical beamforming effect of precoding more prominent.In consideration of the mmWave angle division multiple access (ADMA) system based on precoding, this paper investigates the influence of the angle distribution on system performance, which is denoted as the angular multiplexing gain.Furthermore, inspired by the above research, we transform the ADMA user grouping problem to maximize the system sum-rate into the inter-user angular spacing equalization problem.Then, the form of the optimal solution for the approximate problem is derived, and the corresponding grouping algorithm is proposed.The simulation results demonstrate that the proposed algorithm performs better than the comparison methods.Finally, a complexity analysis also shows that the proposed algorithm has extremely low complexity.

Abstract: The explosive growth of data results in more scarce spectrum resources. It is important to optimize the system performance under limited resources. In this paper, we investigate how to achieve weighted throughput (WTP) maximization for cell-free (CF) multiuser MIMO (MU-MIMO) multicarrier (MC) systems through resource allocation (RA), in the cases of finite blocklength (FBL) and infinite blocklength (INFBL) regimes. To ensure the quality of service (QoS) of each user, particularly for the block error rate (BLER) and latency in the FBL regime, the WTP gets maximized under the constraints of total power consumption and required QoS metrics. Since the channels vary in different subcarriers (SCs) and inter-user interference strengths, the WTP can be maximized by scheduling the best users in each time-frequency (TF) resource and advanced beamforming design, while the resources can be fully utilized. With this motivation, we propose a joint user scheduling (US) and beamforming design algorithm based on the successive convex approximation (SCA) and gene-aided (GA) algorithms, to address a mixed integer nonlinear programming (MINLP) problem. Numerical results demonstrate that the proposed RA outperforms the comparison schemes. And the CF system in our scenario is capable of achieving higher spectral efficiency than the centralized antenna systems (CAS).

Abstract: Compute-forward multiple access (CFMA) is a multiple access transmission scheme based on Compute-and-Forward (CF) which allows the receiver to first decode linear combinations of the transmitted signals and then solve for individual messages. This paper extends the CFMA scheme to a two-user Gaussian multiple-input multiple-output (MIMO) multiple access channel (MAC). We first derive the expression of the achievable rate pair for MIMO MAC with CFMA. We prove a general condition under which CFMA can achieve the sum capacity of the channel. Furthermore, this result is specialized to SIMO and 2-by-2 diagonal MIMO multiple access channels, for which more explicit sum capacity-achieving conditions on power and channel matrices are derived. Numerical results are also provided for the performance of CFMA on general MIMO multiple access channels.