The classic orthogonal frequency division multiple access (OFDMA) faces critical challenges in doubly-selective millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems, and excessive cyclic prefix (CP) overhead and stringent synchronization requirements substantially degrade spectral efficiency. To address these challenges, recent studies have explored delay alignment modulation (DAM), which exploits joint spatial-delay processing to mitigate inter-symbol interference (ISI) and reduce CP overhead without relying on conventional channel equalization structure in single-user systems. Building upon this concept, we leverage delay-Doppler alignment modulation (DDAM), which is a generalization of DAM suitable for doubly-selective channels, to enhance multi-user uplink OFDMA performance. Specifically, we propose a novel flexible synchronization multi-user uplink transmission framework based on DDAM-OFDMA, which integrates DDAM with OFDMA to jointly reduce CP overhead and relax synchronization constraints. First, we analyze the synchronization and CP overhead limitations of uplink OFDMA and highlight the potential of DDAM at the BS to mitigate these issues. To gain further insights, we first consider a DDAM-OFDMA system under the special case of a single-path channel model and derive its input-output relationship, illustrating how DDAM reduces CP overhead while enhancing synchronization robustness. We then formulate a joint optimization problem for time-domain and frequency-domain beamforming to maximize the sum rate and derive the closed-form expression. The proposed framework is then extended to multi-path scenarios by designing the perfect synchronization and the flexible synchronization. Specifically, the perfect synchronization is the extension of the single-path model. Then, the flexible synchronization additionally achieves the controllable channel delay spread, which is achieved through DDAM’s delay compensation and path-based beamforming. Simulation results validate that the proposed DDAM-OFDMA scheme outperforms various benchmark schemes in terms of spectral efficiency and bit error rate (BER).

Reconfigurable distributed antenna and reflecting surface (RDARS) is a new architecture for the sixth-generation (6G) millimeter wave (mmWave) communications. In RDARS-aided mmWave systems, the active and passive beamforming design and working mode configuration for reconfigurable elements are crucial for system performance. In this paper, we aim to maximize the weighted sum rate (WSR) in the RDARS-aided mmWave system. To take advantage of RDARS, we first design a reconfigurable codebook (RCB) in which the number and dimension of the codeword can be flexibly adjusted. Then, a low overhead beam training scheme based on hierarchical search is proposed. Accordingly, the active and passive beamforming for data transmission is designed to achieve the maximum WSR for both space-division multiple access (SDMA) and time-division multiple access (TDMA) schemes. For the TDMA scheme, the optimal number of RDARS transmit elements and the allocated power budget for WSR maximization are derived in closed form. Besides, the superiority of the RDARS is verified and the conditions under which RDARS outperforms RIS and DAS are given. For the SDMA scheme, we characterize the relationship between the number of RDARS connected elements and the user distribution, followed by the derivation of the optimal placement positions of the RDARS transmit elements. High-quality beamforming design solutions are derived to minimize the inter-user interference (IUI) at the base station and RDARS side respectively, which nearly leads to the maximal WSR. Finally, simulation results confirm our theoretical findings and the superiority of the proposed schemes.

Unmanned aerial vehicle (UAV) is regarded as a key enabling platform for low-altitude economy, due to its advantages such as three-dimensional (3D) maneuverability, flexible deployment, and line-of-sight (LoS) air-to-air/ground communication links. In particular, the intrinsic high mobility renders UAV especially suitable for operating as a movable antenna (MA) from the sky. In this paper, by exploiting the flexible mobility of UAV swarm and antenna position adjustment of MA, we propose a novel UAV swarm enabled two-level MA system, where UAVs not only individually deploy a local MA array, but also form a larger-scale MA system with their individual MA arrays via swarm coordination. We formulate a general optimization problem to maximize the minimum achievable rate over all ground user equipments (UEs), by jointly optimizing the 3D UAV swarm placement positions, their individual MAs’ positions (or local positions), and receive beamforming for different UEs. To gain useful insights, we first consider the special case where each UAV has only one antenna, under different scenarios of one single UE, two UEs, and arbitrary number of UEs. In particular, for the two-UE case, we derive the optimal UAV swarm placement positions in closed-form that achieves inter-UE interference (IUI)-free communication when the uniform plane wave (UPW) model holds, where the UAV swarm forms a uniform sparse array (USA) satisfying minimum safe distance constraint. While for the general case with arbitrary number of UEs, we propose an efficient alternating optimization algorithm to solve the formulated non-convex optimization problem. Then, we extend the results to the case where each UAV is equipped with multiple antennas. Numerical results verify that the proposed low-altitude UAV swarm enabled MA system significantly outperforms various benchmark schemes, thanks to the exploitation of two-level mobility to create more favorable channel conditions for multi-UE communications.

Delay alignment modulation (DAM) is recently proposed as an effective technique to address the inter-symbol interference (ISI) issue, which circumvents the conventional channel equalization and multi-carrier transmission. Moreover, wireless communications are vulnerable to malicious eavesdropping and attacks due to their inherent open and broadcast nature. In particular, DAM not only eliminates the ISI at the desired receiver but may also introduce ISI to other locations, and thus is quite promising for secure communications. This paper considers the near-field secure wireless communication with DAM. To gain useful insights, it is first shown that when the antenna number of Alice is much larger than the number of multipaths for Bob and Eve, the delay compensation and low-complexity path-based maximal-ratio transmission (MRT) beamforming achieve a communication free of ISI and information leakage, owing to the asymptotically orthogonal property brought by the near-field nonuniform spherical wave (NUSW). The secrecy rate performance of path-based zero-forcing (ZF) beamforming toward ISI-free communication is then evaluated. Furthermore, the path-based optimized DAM beamforming scheme is proposed to maximize the secrecy rate, by considering the general case in the presence of some tolerable ISI. As a comparison, the benchmarking scheme of the artificial noise (AN) based orthogonal frequency-division multiplexing (OFDM) is considered. Simulation results show that DAM achieves a higher secrecy rate and lower peak-to-average-power ratio (PAPR) than the AN-based OFDM.

Passive metal reflectors for communication enhancement have appealing advantages such as ultra low cost, zero energy expenditure, maintenance-free operation, long life span, and full compatibility with legacy wireless systems. To unleash the full potential of passive reflectors for wireless communications, this paper proposes a new passive reflector architecture, termedflexible reflector(FR), for enabling the flexible adjustment of beamforming direction via the FR placement and rotation optimization. We consider the multi-FR aided area coverage enhancement and aim to maximize the minimum expected receive power over all locations within the target coverage area, by jointly optimizing the placement positions and rotation angles of multiple FRs. To gain useful insights, the special case of movable reflector (MR) with fixed rotation is first studied to maximize the expected receive power at a target location, where the optimal single-MR placement positions for electrically large and small reflectors are derived in closed-form, respectively. It is shown that the reflector should be placed at the specular reflection point for electrically large reflector. While for area coverage enhancement, the optimal placement is obtained for the single-MR case and a sequential placement algorithm is proposed for the multi-MR case. Moreover, for the general case of FR, joint placement and rotation design is considered for the single-/multi-FR aided coverage enhancement, respectively. Numerical results are presented which demonstrate significant performance gains of FRs over various benchmark schemes under different practical setups in terms of receive power enhancement.

Recent studies on deep ensembles have identified the sharpness of the local minima of individual learners and the diversity of the ensemble members as key factors in improving test-time performance. Building on this, our study investigates the interplay between sharpness and diversity within deep ensembles, illustrating their crucial role in robust generalization to both in-distribution (ID) and out-of-distribution (OOD) data. We discover a trade-off between sharpness and diversity: minimizing the sharpness in the loss landscape tends to diminish the diversity of individual members within the ensemble, adversely affecting the ensemble's improvement. The trade-off is justified through our rigorous theoretical analysis and verified empirically through extensive experiments. To address the issue of reduced diversity, we introduce SharpBalance, a novel training approach that balances sharpness and diversity within ensembles. Theoretically, we show that our training strategy achieves a better sharpness-diversity trade-off. Empirically, we conducted comprehensive evaluations in various data sets (CIFAR-10, CIFAR-100, TinyImageNet) and showed that SharpBalance not only effectively improves the sharpness-diversity trade-off but also significantly improves ensemble performance in ID and OOD scenarios.

Recent work on pruning large language models (LLMs) has shown that one can eliminate a large number of parameters without compromising performance, making pruning a promising strategy to reduce LLM model size. Existing LLM pruning strategies typically assign uniform pruning ratios across layers, limiting overall pruning ability; and recent work on layerwise pruning of LLMs is often based on heuristics that can easily lead to suboptimal performance. In this paper, we leverage Heavy-Tailed Self-Regularization (HT-SR) Theory, in particular the shape of empirical spectral densities (ESDs) of weight matrices, to design improved layerwise pruning ratios for LLMs. Our analysis reveals a wide variability in how well-trained, and thus relatedly how prunable, different layers of an LLM are. Based on this, we propose AlphaPruning, which uses shape metrics to allocate layerwise sparsity ratios in a more theoretically-principled manner. AlphaPruning can be used in conjunction with multiple existing LLM pruning methods. Our empirical results show that AlphaPruning prunes LLaMA-7B to 80% sparsity while maintaining reasonable perplexity, marking a first in the literature on LLMs.

Intelligent reflecting surface (IRS) is an emerging technology for wireless communications, thanks to its powerful capability to engineer the radio environment. However, in practice, this benefit is attainable only when the passive IRS is of sufficiently large size, for which the conventional uniform plane wave (UPW)-based far-field model may become invalid. In this paper, we pursue a near-field modelling and performance analysis for wireless communications with extremely large-scale IRS (XL-IRS). By taking into account the directional gain pattern of IRS’s reflecting elements and the variations in signal amplitude across them, we derive both the lower- and upper-bounds of the resulting signal-to-noise ratio (SNR) for the generic uniform planar array (UPA)-based XL-IRS. Our results reveal that, instead of scaling quadratically and unboundedly with the number of reflecting elementsMas in the conventional UPW-based model, the SNR under the new non-uniform spherical wave (NUSW)-based model increases withMwith a diminishing return and eventually converges to a certain limit. To gain more insights, we further study the special case of uniform linear array (ULA)-based XL-IRS, for which a closed-form SNR expression in terms of the IRS size and locations of the base station (BS) and the user is derived. Our result shows that the SNR is mainly determined by the two geometric angles formed by the BS/user locations with the IRS, as well as the dimension of the IRS. Numerical results validate our analysis and demonstrate the necessity of proper near-field modelling for wireless communications aided by XL-IRS.

Delay alignment modulation(DAM) is an emerging technique for achieving inter-symbol interference (ISI)-free wideband communications using spatial-delay processing, without relying on channel equalization or multi-carrier transmission. However, existing works on DAM only consider multiple-input single-output (MISO) communication systems and assume time-invariant channels. In this paper, by extending DAM to time-variant frequency-selective multiple-input multiple-output (MIMO) channels, we propose a novel technique termeddelay-Doppler alignment modulation(DDAM). Specifically, by leveragingdelay-Doppler compensationandpath-based beamforming, the Doppler effect of each multi-path can be eliminated and all multi-path signal components may reach the receiver concurrently and constructively. We first show that by applying path-based zero-forcing (ZF) precoding and receive combining, DDAM can transform the original time-variant frequency-selective channels into time-invariant ISI-free channels. The necessary and/or sufficient conditions to achieve such a transformation are derived. Then an asymptotic analysis is provided by showing that when the number of base station (BS) antennas is much larger than that of channel paths, DDAM enables time-invariant ISI-free channels with the simple delay-Doppler compensation and path-based maximal-ratio transmission (MRT) beamforming. Furthermore, for the general DDAM design with some tolerable ISI, the path-based transmit precoding and receive combining matrices are optimized to maximize the spectral efficiency. Numerical results are provided to compare the proposed DDAM technique with various benchmarking schemes, including MIMO-orthogonal time frequency space (OTFS), MIMO-orthogonal frequency-division multiplexing (OFDM) without or with carrier frequency offset (CFO) compensation, and beam alignment along the dominant path.

Delay alignment modulation (DAM) is a promising technology to achieve inter-symbol interference (ISI)-free single-carrier communication, by leveragingdelay compensationandpath-based beamforming, rather than the conventional channel equalization or multi-carrier transmission. In particular, when there exist a few strong time-dispersive channel paths, DAM is able to effectively align different propagation delays and achieve their constructive superposition, thus especially appealing for intelligent reflecting surfaces (IRSs)-aided communications with controllable multi-paths. In this paper, we apply single-carrier DAM to multi-IRS aided communication and study its design and achievable performance. We first provide an asymptotic analysis showing that when the number of base station (BS) antennas is much larger than the number of IRSs, an ISI-free channel can be established from the BS to the user with appropriate delay pre-compensation and the simple path-based maximal-ratio transmission (MRT) beamforming. We then consider the general system setup and study the problem of joint path-based beamforming design at the BS and phase shifts design at the IRSs for DAM transmission, by considering the three classical beamforming techniques on a per-path basis, namely the low-complexity path-based MRT beamforming to maximize the desired signal power, the path-based zero-forcing (ZF) beamforming for ISI-free DAM communication, and the optimal path-based minimum mean-square error (MMSE) beamforming to maximize the signal-to-interference-plus-noise ratio (SINR). As a comparison, orthogonal frequency-division multiplexing (OFDM)-based multi-IRS aided communication is considered for benchmarking. Simulation results are provided which demonstrate the significant performance gain of DAM over OFDM, in terms of spectral efficiency and bit error rate (BER), as well as its lower peak-to-average-power ratio (PAPR).

Delay alignment modulation (DAM) is a novel wideband communication technique, which exploits the high spatial resolution and multi-path sparsity of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems to mitigate inter-symbol interference (ISI), without relying on conventional techniques like channel equalization or multi-carrier transmission. In this paper, we extend the DAM technique to multi-user mmWave massive MIMO communication systems. We first provide asymptotic analysis by showing that when the number of base station (BS) antennas is much larger than the total number of channel paths, DAM is able to eliminate both ISI and inter-user interference (IUI) with the simple delay pre-compensation and per-path-based maximal ratio transmission (MRT) beamforming. We then study the general multi-user DAM design by considering the three classical transmit beamforming strategies in a per-path basis, namely MRT, zero-forcing (ZF) and regularized zero-forcing (RZF). Simulation results demonstrate that multi-user DAM can significantly outperform the bench-marking single-carrier ISI mitigation technique that only uses the strongest channel path of each user.

The evolution of mobile communication networks has always been accompanied by the advancement of inter-symbol interference (ISI) mitigation techniques, from equalization in the second-generation (2G), spread spectrum and RAKE receiver in the third generation (3G), to orthogonal frequency-division multiplexing (OFDM) in the fourth-generation (4G) and fifth-generation (5G). Looking forward towards the sixth-generation (6G), by exploiting the high spatial resolution brought by large antenna arrays and the multi-path sparsity of millimeter wave (mmWave) and Terahertz channels, a novel ISI mitigation technique termed delay alignment modulation (DAM) was recently proposed. However, existing works only consider the single-carrier perfect DAM, which is feasible only when the number of base station (BS) antennas is no smaller than that of channel paths, so that all multi-path signal components can be aligned for arriving at the receiver simultaneously and constructively. This imposes stringent requirements on the number of BS antennas and multi-path sparsity. In this paper, we propose a generic DAM technique to manipulate the channel delay spread via spatial-delay processing, thus providing a flexible framework to combat channel time dispersion for efficient single- or multi-carrier transmissions. To gain some insights, we first show that when the number of BS antennas is much larger than that of channel paths, perfect delay alignment can be achieved to transform the time-dispersive channel to time non-dispersive channel with the simple delay pre-compensation and path-based maximal-ratio transmission (MRT) beamforming. When perfect DAM is infeasible or undesirable, the proposed generic DAM technique can be applied to significantly reduce the channel delay spread. Based on such results, we further propose the novel DAM-OFDM technique, which is able to save the cyclic prefix (CP) overhead or mitigate the peak-to-average-power ratio (PAPR) issue suffered by conventional OFDM. We show that the proposed DAM-OFDM involves joint frequency- and time-domain beamforming optimization, for which a closed-form solution is derived. Simulation results show that the proposed DAM-OFDM achieves significant performance gains over the conventional OFDM, in terms of spectral efficiency, bit error rate (BER) and PAPR.

Wireless communications with extremely large-scale array (XL-array) correspond to systems whose antenna sizes are so large that conventional modeling assumptions, such as uniform plane wave (UPW) impingement, are no longer valid. This paper studies the mathematical modeling and performance analysis of XL-array communications. By deviating from the conventional modeling approach that treats the array elements as sizeless points, we explicitly model their physical area/aperture, which enables a unified modeling for the classical discrete antenna arrays and the emerging active continuous surfaces. As such, a generic array/surface model that accurately takes into account the variations of signal phase, amplitude and projected aperture across array elements is proposed. Based on the proposed model, a closed-form expression of the resulting signal-to-noise ratio (SNR) with the optimal single-user maximum ratio combining/transmission (MRC/MRT) beamforming is derived. The expression reveals that instead of scaling linearly with the antenna number$M$as in conventional UPW modeling, the SNR with the more generic model increases with$M$with diminishing return, which is governed by the collective properties of the array, such as thearray occupation ratioand the physical sizes of the array along each dimension, while irrespective of the properties of the individual array element. In addition, we have derived an alternative insightful expression for the optimal SNR in terms of theverticalandhorizontal angular spans, which are fully determined by the geometric angles formed by the array/surface and user location. Furthermore, we also show that our derived results include the far-field UPW modeling as a special case. One important finding during the study of far-field approximation is the necessity to introduce a new distance criterion to complement the classical Rayleigh distance, termeduniform-power distance(UPD), which concerns the signal amplitude/power variations across array elements, instead of phase variations as for Rayleigh distance. Extensive numerical results are provided to demonstrate the necessity of proper modeling for XL-array communications by comparing the proposed model with various benchmark models.

Extremely large-scale multiple-input multiple-output (XL-MIMO) communications correspond to systems whose antenna size is so large that conventional assumptions, such as uniform plane wave (UPW) impingement, are no longer valid. This paper studies the channel modelling and performance analysis of XL-MIMO communication based on the generic spherical wavefront propagation model. First, for the single-user uplink/downlink communication with the optimal maximum ratio combining/transmission (MRC/MRT), we rigorously derive a new closed-form expression for the resulting signal-to-noise ratio (SNR), which includes the conventional SNR expression based on UPW assumption as a special case. Our result shows that instead of scaling linearly with the base station (BS) antenna number M, the SNR with the more generic spherical wavefront model increases with M with diminishing return, governed by a new parameter called angular span. One important finding from our derivation is the necessity to introduce a new distance criterion, termed critical distance, to complement the classical Rayleigh distance for separating the near- and far-field propagation regions. While Rayleigh distance is based on the phase difference across array elements and hence depends on the electrical size of the antenna, the critical distance cares about the amplitude/power difference and only depends on its physical size. We then extend the study to the multi-user XL-MIMO communication system, for which we demonstrate that inter-user interference (IUI) can be mitigated not just by angle separation, but also by distance separation along the same direction. This offers one new degree of freedom (DoF) for interference suppression with XL-MIMO.

Intelligent reflecting surface (IRS) is a promising technology to reconfigure wireless channels, which brings a new degree of freedom for the design of future wireless networks. This article proposes a new three-dimensional (3D) wireless system architecture enabled by aerial IRS (AIRS). Compared to the conventional terrestrial IRS, AIRS enjoys more deployment flexibility as well as wider-view signal reflection, thanks to its high altitude and thus more likelihood of establishing line-of-sight (LoS) links with ground source/destination nodes. We aim to maximize the worst-case signal-to-noise ratio (SNR) over all locations in a target area by jointly optimizing the transmit beamforming for the source node, as well as the placement and 3D passive beamforming for the AIRS. The formulated problem is non-convex and difficult to solve. To gain useful insights, we first consider the special case of maximizing the SNR at a given target location, for which the optimal solution is obtained in closed-form. The result shows that the optimal horizontal AIRS placement only depends on the ratio between the source-destination distance and the AIRS altitude. Then for the general case of AIRS-enabled area coverage, we propose an efficient solution by decoupling the AIRS passive beamforming design to maximize the worst-case array gain, from its placement optimization by balancing the resulting angular span and the cascaded channel path loss. Our proposed solution is based on a novel 3D beam broadening and flattening technique, where the passive array of the AIRS is divided into sub-arrays of appropriate size, and their phase shifts are designed to form a flattened beam pattern with adjustable beamwidth catering to the size of the coverage area. Both uniform linear array (ULA)-based and uniform planar array (UPA)-based AIRSs are considered in our design, which enable two-dimensional (2D) and 3D passive beamforming, respectively. Numerical results show that the proposed designs achieve significant performance gains over the benchmark schemes.