Multi-Satellite MIMO Systems for Direct User-Satellite Communications: A Survey

Advancements in satellite technology have made direct-to-device connectivity a viable solution for ensuring global access. This method is designed to provide internet connectivity to remote, rural, or underserved areas where traditional cellular or broadband networks are lacking or insufficient. This paper is a survey providing an in-depth review of multi-satellite Multiple Input Multiple Output (MIMO) systems as a potential solution for addressing the link budget challenge in direct user-satellite communication. Special attention is given to works considering multi-satellite MIMO systems, both with and without satellite collaboration. In this context, collaboration refers to sharing data between satellites to improve the performance of the system. This survey begins by explaining several fundamental aspects of satellite communications (SatComs), which are vital prerequisites before investigating the multi-satellite MIMO systems. These aspects encompass satellite orbits, the structure of satellite systems, SatCom links, including the inter-satellite links (ISL) which facilitate satellite cooperation, satellite frequency bands, satellite antenna design, and satellite channel models, which should be known or estimated for effective data transmission to and from multiple satellites. Furthermore, this survey distinguishes itself by providing more comprehensive insights in comparison to other surveys. It specifically delves into the Orthogonal Time Frequency Space (OTFS) within the channel model section. It goes into detail about ISL noise and channel models, and it extends the ISL section by thoroughly investigating hybrid FSO/RF ISLs. Furthermore, analytical comparisons of simulation results from these works are presented to highlight the advantages of employing multi-satellite MIMO systems.

An Efficient Algorithm for Sum-Rate Maximization in Fluid Antenna-Assisted ISAC System

In this letter, we investigate the fluid antenna (FA)-assisted integrated sensing and communication (ISAC) system, where communication and radar sensing employ the co-waveform design. Specifically, we focus on the beamformer design and antenna position configuration to realize a higher communication rate while guaranteeing the minimum radar probing power. Different from existing beamformer algorithms, we propose an efficient proximal distance algorithm (PDA) to solve the multiuser sum-rate maximization problem with radar sensing constraint to obtain the closed-form beamforming vector. In addition, we develop an extrapolated projected gradient (EPG) algorithm to obtain a better antenna location configuration for FA to enhance the ISAC performance. Numerical results show that the considered FA-assisted ISAC system enjoys a higher sum-rate by the proposed algorithm, compared with that in existing non-FA ISAC systems.

Knowledge and Data Dual-Driven Channel Estimation and Feedback for Ultra-Massive MIMO Systems under Hybrid Field Beam Squint Effect

Acquiring accurate channel state information (CSI) at an access point (AP) is challenging for wideband millimeter wave (mmWave) ultra-massive multiple-input and multiple-output (UMMIMO) systems, due to the high-dimensional channel matrices, hybrid near- and far- field channel feature, beam squint effects, and imperfect hardware constraints, such as low-resolution analog-to-digital converters, and in-phase and quadrature imbalance. To overcome these challenges, this paper proposes an efficient downlink channel estimation (CE) and CSI feedback approach based on knowledge and data dual-driven deep learning (DL) networks. Specifically, we first propose a data-driven residual neural network de-quantizer (ResNet-DQ) to pre-process the received pilot signals at user equipment (UEs), where the noise and distortion brought by imperfect hardware can be mitigated. A knowledge-driven generalized multiple measurement vector learned approximate message passing (GMMV-LAMP) network is then developed to jointly estimate the channels by exploiting the approximately same physical angle shared by different subcarriers. In particular, two wideband redundant dictionaries (WRDs) are proposed such that the measurement matrices of the GMMV-LAMP network can accommodate the far-field and near-field beam squint effect, respectively. Finally, we propose an encoder at the UEs and a decoder at the AP by a data-driven CSI residual network (CSI-ResNet) to compress the CSI matrix into a low-dimensional quantized bit vector for feedback, thereby reducing the feedback overhead substantially. Simulation results show that the proposed knowledge and data dual-driven approach outperforms conventional downlink CE and CSI feedback methods, especially in the case of low signal-to-noise ratios.

Near-Space Communications: The Last Piece of 6G Space-Air-Ground-Sea Integrated Network Puzzle

This article presents a comprehensive study on the emerging near-space communications (NS-COM) within the context of space-air-ground-sea integrated network (SAGSIN). Specifically, we firstly explore the recent technical developments of NS-COM, followed by the discussions about motivations behind integrating NS-COM into SAGSIN. To further demonstrate the necessity of NS-COM, a comparative analysis between the NS-COM network and other counterparts in SAGSIN is conducted, covering aspects of deployment, coverage and channel characteristics. Afterwards, the technical aspects of NS-COM, including channel modeling, random access, channel estimation, array-based beam management and joint network optimization, are examined in detail. Furthermore, we explore the potential applications of NS-COM, such as structural expansion in SAGSIN communications, remote and urgent communications, weather monitoring and carbon neutrality. Finally, some promising research avenues are identified, including near-space-ground direct links, reconfigurable multiple input multiple output (MIMO) array, federated learning assisted NS-COM, maritime communication and free space optical (FSO) communication. Overall, this paper highlights that the NS-COM plays an indispensable role in the SAGSIN puzzle, providing substantial performance and coverage enhancement to the traditional SAGSIN architecture.

Index Modulation for Fluid Antenna-Assisted MIMO Communications: System Design and Performance Analysis

In this paper, we propose a transmission mechanism for fluid antennas (FAs) enabled multiple-input multiple-output (MIMO) communication systems based on index modulation (IM), named FA-IM, which incorporates the principle of IM into FAs-assisted MIMO system to improve the spectral efficiency (SE) without increasing the hardware complexity. In FA-IM, the information bits are mapped not only to the modulation symbols, but also the index of FA position patterns. Additionally, the FA position pattern codebook is carefully designed to further enhance the system performance by maximizing the effective channel gains. Then, a low-complexity detector, referred to efficient sparse Bayesian detector, is proposed by exploiting the inherent sparsity of the transmitted FA-IM signal vectors. Finally, a closed-form expression for the upper bound on the average bit error probability (ABEP) is derived under the finite-path and infinite-path channel condition. Simulation results show that the proposed scheme is capable of improving the SE performance compared to the existing FAs-assisted MIMO and the fixed position antennas (FPAs)-assisted MIMO systems while obviating any additional hardware costs. It has also been shown that the proposed scheme outperforms the conventional FA-assisted MIMO scheme in terms of error performance under the same transmission rate.

Design and Performance Analysis of Index Modulation Empowered AFDM System

In this letter, we incorporate index modulation (IM) into affine frequency division multiplexing (AFDM), called AFDM-IM, to enhance the bit error rate (BER) and energy efficiency (EE) performance. In this scheme, the information bits are conveyed not only by $M$-ary constellation symbols, but also by the activation of the chirp subcarriers (SCs) indices, which are determined based on the incoming bit streams. Then, two power allocation strategies, namely power reallocation (PR) strategy and power saving (PS) strategy, are proposed to enhance BER and EE performance, respectively. Furthermore, the average bit error probability (ABEP) is theoretically analyzed. Simulation results demonstrate that the proposed AFDM-IM scheme achieves better BER performance than the conventional AFDM scheme.

Integrated Robotics Networks with Co-optimization of Drone Placement and Air-Ground Communications

Terrestrial robots, i.e., unmanned ground vehicles (UGVs), and aerial robots, i.e., unmanned aerial vehicles (UAVs), operate in separate spaces. To exploit their complementary features (e.g., fields of views, communication links, computing capabilities), a promising paradigm termed integrated robotics network emerges, which provides communications for cooperative UAVs-UGVs applications. However, how to efficiently deploy UAVs and schedule the UAVs-UGVs connections according to different UGV tasks become challenging. In this paper, we propose a sum-rate maximization problem, where UGVs plan their trajectories autonomously and are dynamically associated with UAVs according to their planned trajectories. Although the problem is a NP-hard mixed integer program, a fast polynomial time algorithm using alternating gradient descent and penalty-based binary relaxation, is devised. Simulation results demonstrate the effectiveness of the proposed algorithm.

Enhancing Signal Space Diversity for SCMA Over Rayleigh Fading Channels

Sparse code multiple access (SCMA) is a promising technique for the enabling of massive connectivity in future machine-type communication networks, but it suffers from a limited diversity order which is a bottleneck for significant improvement of error performance. This paper aims for enhancing the signal space diversity of sparse code multiple access (SCMA) by introducing quadrature component delay to the transmitted codeword of a downlink SCMA system in Rayleigh fading channels. Such a system is called SSD-SCMA throughout this work. By looking into the average mutual information (AMI) and the pairwise error probability (PEP) of the proposed SSD-SCMA, we develop novel codebooks by maximizing the derived AMI lower bound and a modified minimum product distance (MMPD), respectively. The intrinsic asymptotic relationship between the AMI lower bound and proposed MMPD based codebook designs is revealed. Numerical results show significant error performance improvement in the both uncoded and coded SSD-SCMA systems.

Transformer-based Joint Source Channel Coding for Textual Semantic Communication

The Space-Air-Ground-Sea integrated network calls for more robust and secure transmission techniques against jamming. In this paper, we propose a textual semantic transmission framework for robust transmission, which utilizes the advanced natural language processing techniques to model and encode sentences. Specifically, the textual sentences are firstly split into tokens using wordpiece algorithm, and are embedded to token vectors for semantic extraction by Transformer-based encoder. The encoded data are quantized to a fixed length binary sequence for transmission, where binary erasure, symmetric, and deletion channels are considered for transmission. The received binary sequences are further decoded by the transformer decoders into tokens used for sentence reconstruction. Our proposed approach leverages the power of neural networks and attention mechanism to provide reliable and efficient communication of textual data in challenging wireless environments, and simulation results on semantic similarity and bilingual evaluation understudy prove the superiority of the proposed model in semantic transmission.

Secure Transmission for THz-Empowered RIS-Assisted Non-Terrestrial Networks

The non-terrestrial networks (NTNs) are recognized as a key component to provide cost-effective and high-capacity ubiquitous connectivity in the future wireless communications. In this paper, we investigate the secure transmission in a terahertz (THz)-empowered reconfigurable intelligent surface (RIS)-assisted NTN (T-RANTN), which is composed of a low-Earth orbit satellite transmitter, an RIS-installed high-altitude platform (HAP) and two unmanned aerial vehicle (UAV) receivers, only one of which is trustworthy. An approximate ergodic secrecy rate (ESR) expression is derived when the atmosphere turbulence and pointing error due to the characteristics of THz as well as the phase errors resulting from finite precision of RIS and imperfect channel estimation are taken into account simultaneously. Furthermore, according to the statistical and perfect channel state information of the untrustworthy receiver, we optimize the phase shifts of RIS to maximize the lower bound of secrecy rate (SR) and instantaneous SR, respectively, by using semidefinite relaxation method. Simulation results show that both the approximate expression for the ESR and the optimization algorithms are serviceable, and even when the jitter standard variance of the trustworthy receiver is greater than that of the untrustworthy one, a positive SR can still be guaranteed.