Mobile edge computing–space-air-ground integrated network (MEC-SAGIN) is emerging as a crucial component of future wireless systems. Despite its potential, addressing network fluctuations while ensuring continuous low-latency computing services in highly dynamic environments remains a significant challenge. To address this issue, this paper proposes a fluid antenna (FA)-assisted MEC-SAGIN system, which enhances channel transmission conditions and reduces uplink task offloading latency by flexibly adjusting the antenna ports of edge computing users equipped with FAs. Specifically, we aim to minimize the maximum total computational delay (TCD) of edge computing tasks for ground users (GUs) and the satellite user (SU) by jointly optimizing the task offloading strategies, computational resource allocation, FA port positions, unmanned aerial vehicle (UAV) location, and the receive beamforming matrix. To solve this non-convex problem, we employ the block coordinate descent (BCD) technique to decompose the original problem into four subproblems. The subproblems are optimized using a combination of low-complexity iterative algorithms and the projected gradient descent (PGD) method to refine communication and computation configurations as well as FA port selection. Simulation results demonstrate that the FA-assisted scheme significantly improves the TCD performance of the MEC-SAGIN system. It maintains transmission stability and reliability in dynamic environments while outperforming conventional fixed-position antennas (FPAs) and random-port antenna schemes.

This paper investigates physical-layer key generation (PLKG) in multi-antenna base station systems, by leveraging a fluid antenna system (FAS) to dynamically customize radio environments. Without requiring additional nodes or extensive radio frequency (RF) chains, the FAS effectively enables adaptive antenna port selection by exploiting channel spatial correlation to enhance the secret key rate (SKR) at legitimate nodes. To comprehensively evaluate the performance of the FAS in PLKG, we propose an FAS-assisted PLKG model that integrates transmit beamforming and sparse port selection under independent and identically distributed (i.i.d.) and spatially correlated channel models, respectively. Specifically, the PLKG utilizes reciprocal channel probing to derive an approximate SKR expression based on the mutual information between legitimate channel estimates, explicitly accounting for the Eve’s channel observation under spatially correlated channel scenarios. Nonconvex optimization problems for these scenarios are formulated to maximize the SKR subject to transmit power constraints and sparse port activation. We propose an iterative algorithm by capitalizing on successive convex approximation and Cauchy-Schwarz inequality to obtain a locally optimal solution. A reweighted ℓ1-norm-based algorithm is applied to advocate for the sparse port activation of FAS-assisted PLKG. To approximate the optimal activated ports obtained by exhaustive search, a low-complexity sliding window-based port selection is proposed to substitute reweighted ℓ1-norm method based on Rayleigh-quotient analysis. Simulation results demonstrate that the FAS-assisted PLKG scheme significantly outperforms fixed antenna-assisted PLKG schemes in both environments. It is shown that the FAS achieves higher SKR with fewer RF chains through dynamic sparse port selection, which effectively reduces the resource overhead. Also, the sliding window approach closely approximates the globally optimal port selection compared to the reweighted ℓ1-norm method, rendering it suitable for practical deployments.

Reconfigurable intelligent surface (RIS) has emerged as a promising technology for enhancing communication systems. This paper investigates a novel flexible-position RIS-assisted communication system, where the RIS is mounted on a slide rail, enabling spatial adaptability. Unlike traditional fixed-position RISs, the proposed system leverages both spatial flexibility and phase reconfigurability to optimize system performance while reducing overhead through strategic position adjustment. To characterize the spatial variations introduced by RIS movement, we propose a generalized RIS channel model that integrates a practical visibility region function with near-field spherical wave propagation. This model captures the spatial correlation characteristics influenced by multipath angular spread, scatterer distribution, and RIS positioning. Furthermore, we introduce a measurement scheme using a multi-state RIS hardware to analyze segmented channels across fixed-position and flexible-position scenarios. Our measurement reveals that the intra-cluster power angular spectrum follows a Gaussian distribution, and in strong scattering environments, spatial correlation exhibits an enhanced degree of freedom due to spatial non-stationarity effects. In particular, the experimental results demonstrate that the gain of the received power varies from 0.4 dB to 5.3 dB across different RIS positions, providing empirical evidence that spatial adaptability of RIS effectively resists channel non-stationarity. These findings highlight the potential of flexible-position RIS to enhance future wireless communication systems.

In this paper, a novel three dimensional (3D) positioning framework of fluid antenna system (FAS)-enabled unmanned aerial vehicles (UAVs) is developed. In the proposed framework, a set of controlled UAVs including an active UAV and four FAS-enabled passive UAVs cooperatively estimate the real-time 3D position of a target UAV. Here, the active UAV transmits a measurement signal to the passive UAVs via the reflection from the target UAV. Each passive UAV estimates the distance of the active-target-passive UAV link and selects an antenna port to share the distance information with the base station (BS), which calculates the real-time position of the target UAV. As the target UAV is moving due to its task operation, the controlled UAVs must optimize their trajectories and select optimal antenna port for transmitting the positioning information, aiming to estimate the real-time position of the target UAV. We formulate this problem as an optimization problem whose goal is to minimize the target UAV positioning error via optimizing the trajectories of all controlled UAVs and antenna port selection of passive UAVs. To address this problem, an attention-based recurrent multi-agent reinforcement learning (AR-MARL) scheme is proposed, which enables each controlled UAV to use the local Q function to determine its trajectory and antenna port while optimizing the target UAV positioning performance without knowing the trajectories and antenna port selections of other controlled UAVs. Different from current MARL methods that use feedforward neural networks to approximate Q functions, the proposed method uses a recurrent neural network (RNN) that incorporates historical state-action pairs of each controlled UAV, and an attention mechanism to analyze the importance of these historical state-action pairs, thus improving the global Q function approximation accuracy and the target UAV positioning accuracy. Simulation results show that the proposed scheme can reduce the average positioning error by up to 17.5% and 58.5% compared to the value decomposition based-MARL scheme with FAS and the proposed AR-MARL method without FAS.

Reconfigurable intelligent surface (RIS) technology has gained widespread recognition for its ability to significantly enhance communication performance between base stations (BS) and users in blind spot areas. This paper investigates the energy efficiency (EE) of an RIS-assisted multi-cell communication system, incorporating a measurement-based empirical RIS power consumption model. Exploiting only statistical channel state information (CSI), we aim to maximize the overall EE of the system. An alternating optimization (AO) algorithm is proposed for joint optimization of the transmit beamforming vectors at the BSs and the RIS phase shift matrix. To circumvent the challenges arising from the discrete relationship between the power consumption of positive-intrinsic-negative (PIN) diode-based reflecting elements and their phase shifts, we introduce a continuous function to approximate the relationship. With this approximation, the complex circle manifold (CCM) technique is applied to optimize the continuous RIS phase shifts, which are then quantized within a discrete set. Then, to further reduce the complexity of the AO algorithm, a sub-optimal algorithm is proposed. In this algorithm, the statistical maximum ratio transmission beamforming is employed at each BS, which decouples the design of BS beamforming vectors from the design of BS transmit power and RIS phase shifts. Given the BS beamforming vectors, the BS transmit power and RIS phase shifts are then designed using the quadratic transformation and CCM techniques. Simulation results show that the proposed algorithm achieves near-optimal EE while offering guidance on PIN diode encoding to balance phase resolution and power consumption in practical RIS design.

Fluid antenna system (FAS) technology can further improve the performance by changing the antenna position and shape over a given space dynamically. In this paper, a FAS-assisted orbital angular momentum (FAS-OAM) communication system is proposed, in which the base station (BS) transmits OAM signals with multiple modes to a receiver equipped with fluid antennas. In order to analyze the performance of the proposed system accurately, the block-correlation model is employed to construct the channel correlation of FAS with low complexity. Then, the outage probability and ergodic capacity are derived based on the assumption of the non-central chi-square distribution, and the Gauss-Laguerre quadrature method is adopted to obtain closed-form results. Simulation results show that the derived theoretical approximate and closed-form results of outage probability and ergodic capacity are consistent with corresponding simulation results. Compared with the conventional OAM and MIMO systems, the proposed FAS-OAM system exhibits significant performance advantages in terms of outage probability and ergodic capacity, and confirms the effectiveness of FAS-OAM over fading channels.

This paper investigates a new integrated sensing and communication (ISAC) scheme for underwater acoustic (UWA) networks based on deep reinforcement learning, referred to as Deep UWA-ISAC (DeepUSC). Specifically, we consider a UWA-ISAC system, where an autonomous underwater vehicle (AUV) transmits the collected environmental data to the buoy, while sensing the sea area to monitor the unauthorized mobile target. The expected communication rate over a given navigation period is maximized by jointly optimizing the AUV's beamforming and trajectory, subject to the constraints on the average signal-to-noise ratio requirement for target sensing as well as the navigation mission, collision avoidance, and maximum transmit power limit of the AUV. Three key challenges for DeepUSC are: (i) long propagation delays in the UWA-ISAC system may cause interference from the previous echo to the current ISAC signal; (ii) the mobility pattern of the target is unknown in advance; and (iii) the AUV navigation-oriented ISAC problem is a long-term optimization problem as the navigation mission typically lasts for a long period. To circumvent the above challenges, DeepUSC is developed based on a specific partially observable Markov decision process model termed episode task, where each navigation period is considered as an episode and the navigation mission corresponds to the episode task. Through judicious design of a reward function and action selection policy, DeepUSC can satisfy various preset constraints without requiring prior knowledge of the target's mobility. Besides, to enable efficient learning in episode tasks, we propose an episodic experience replay mechanism that dynamically prioritizes high-value recent experiences and utilizes all experiences generated within each episode to jointly train the neural network. Simulation results demonstrate that compared with benchmarks, DeepUSC yields a higher communication rate while satisfying all constraints, converges faster, and is more robust against different simulation setups.

In-band full-duplex (IBFD) systems are expected to double the spectral efficiency compared to half-duplex systems, provided that loopback self-interference (SI) can be effectively suppressed. The inherent interference mitigation capabilities of the emerging fluid antenna system (FAS) technology make it a promising candidate for addressing the SI challenge in IBFD systems. This paper thus proposes a FAS-assisted self-interference cancellation (SIC) framework, which leverages a receiver-side FAS to dynamically select an interference-free port. Analytical results include a lower bound and an approximation of the residual SI (RSI) power, both derived for rich-scattering channels by considering the joint spatial correlation amongst the FAS ports. Simulations of RSI power and forward link rates validate the analysis, showing that the SIC performance improves with the number of FAS ports. Additionally, simulations under practical conditions, such as finite-scattering environments and wideband integrated access and backhaul (IAB) channels, reveal that the proposed approach offers superior SIC capability and significant forward rate gains over conventional IBFD SIC schemes.

This paper presents a novel framework for enhancing physical-layer security in integrated sensing and communication (ISAC) systems by leveraging the reconfigurability of fluid antenna systems (FAS). We propose a joint precoding and port selection (JPPS) strategy that maximizes the sum secrecy rate while simultaneously ensuring reliable radar sensing. The problem is formulated using fractional programming (FP) and solved through an iterative algorithm that integrates FP transformations with successive convex approximation (SCA). To reduce computational complexity, we further develop low-complexity schemes based on zero-forcing (ZF) precoding, combined with greedy port selection and trace-inverse minimization. Simulation results show substantial improvements in both secrecy performance and sensing accuracy compared to conventional baselines, across a wide range of FAS port number, user loads, and sensing targets. These findings highlight the critical importance of FAS geometry optimization in enabling secure and efficient joint communication-sensing for next-generation wireless networks.

This paper presents channel measurement campaigns and spatial channel characterization of reconfigurable intelligent surface (RIS)-assisted millimeter-wave multiple-input multiple-output (MIMO) systems. Utilizing a channel sounder and an RIS, the RIS-assisted MIMO channels are constructed in an indoor non-line-of-sight scenario. By rotating a narrow-beam directional antenna (DA) in the azimuth angle domain, the spatial signal distributions are captured. Meanwhile, multiple comparative experiments, including: wideband vs narrowband (NB) and DA vs omnidirectional antenna, are conducted. The influence of RIS deployment and different coding schemes is considered. Based on such channel realizations, spatial channel metrics, including the power azimuth spectrum (PAS), root mean square angular spread (RMS AS), root mean square delay spread (RMS DS), spatial correlation coefficient (SCC), effective rank, and etc., are thoroughly investigated. Measurement results show that, using the DA, NB signal, and beamforming provided by the RIS contributes to a lower RMS DS, a higher SCC, and a lower effective rank. A truncated Laplacian function is used to describe the PAS, indicating prominent signal strength improvements in both the primary direction facing RIS and the opposite direction to RIS. The RMS ASs are well-fitted by a generalized extreme value distribution, which manifest a distance-dependent variation in the space domain.

This paper studies the use of multiple planar fluid antennas at a full-duplex base station (BS) for integrated sensing and communication (ISAC). In this model, the BS communicates with a downlink user, an uplink user, and performs target sensing simultaneously. Our objective is to maximize the communication sum-rate of the up and downlink users while meeting the sensing and power constraints. Given that the problem is non-convex, we first reformulate the problem using the fractional programming (FP) framework. After that, we iteratively optimize the beamforming vectors of the BS, the uplink transmit power from the user, and the antenna positions of both transmit and receive fluid antenna systems (FASs) at the BS. In particular, the transmit and receive beamforming vectors are optimized by utilizing the majorization-minimization (MM) framework, and a closed-form solution for the uplink transmit power is derived. To optimize the BS antenna positions, we transform the problems into convex quadratically constrained quadratic programs (QCQP) by using Taylor series expansion. The subproblems can then be solved based on the successive convex approximation (SCA). Simulation results show that FAS can greatly improve the communication rate compared to the traditional fixed-position antenna (FPA) system.

With the development of the upcoming sixth-generation (6G) wireless networks, there is a pressing need for innovative technologies capable of satisfying heightened performance indicators. Fluid antenna system (FAS) is proposed recently as a promising technique to achieve higher data rates and more diversity gains by dynamically changing the positions of the antennas to form a more desirable channel. However, worries regarding the possibly harmful effects of electromagnetic (EM) radiation emitted by devices have arisen as a result of the rapid evolution of advanced techniques in wireless communication systems. Specific absorption rate (SAR) is a widely adopted metric to quantify EM radiation worldwide. In this paper, we investigate the SAR-aware multiuser multiple-input multiple-output (MIMO) communications assisted by FAS. In particular, a two-layer iterative algorithm is proposed to minimize the SAR value under signal-to-interference-plus-noise ratio (SINR) and FAS constraints. Moreover, the minimum weighted SINR maximization problem under SAR and FAS constraints is studied by finding its relationship with the SAR minimization problem. Simulation results verify that the proposed SAR-aware FAS design outperforms the adaptive backoff and fixed-position antenna designs.

This paper investigates fluid antenna systems (FASs) subject to finite-blocklength (FBL) constraints, motivated by the strict reliability-latency and ultra-massive connectivity requirements of future wireless networks. While FAS performance has been widely studied in the asymptotic regime, its behavior under FBL remains largely unexplored. Our objective is to develop a unified set of analytical tools for evaluating FASs under FBL that remains applicable across different spatial-correlation models. First, to establish accurate benchmarks for non-orthogonal finite-length user signature design, we characterize both the average and the worst-case correlation coefficients via extreme value theory (EVT) and derive closed-form predictions of the achievable correlation levels. Second, taking block error rate (BLER) as the fundamental FBL metric, we study joint detection and decoding in FAS-assisted links and derive a closed-form BLER expression that is universally applicable across channel models. Additionally, we revisit outage probability (OP) in the FBL regime and obtain tractable OP characterizations for both FASs and conventional multiple fixed-position antenna (FPA) systems. In order to reduce the computational burden for multi-fold integrals in correlated fading models, we further propose a Taylor-expansion-assisted mean value theorem for integrals (MVTI), thus enabling efficient performance evaluation with marginal accuracy loss. Numerical results validate the analysis and reveal that even single-antenna FASs can have superior spatial diversity relative to conventional multi-FPA systems. Moreover, under both FBL and interference-limited environments, FASs provide improved energy, spectral, and hardware efficiencies, hence highlighting FAS as a promising enabler for next-generation wireless networks.

This paper develops a comprehensive framework for the performance analysis of fluid antenna system (FAS)-enabled unmanned aerial vehicle (UAV) relaying networks operating in the finite blocklength regime. This work establishes a rigorous methodology for characterizing system reliability under diverse propagation environments. Closed-form expressions for the block error rate (BLER) are derived by employing a tractable eigenvalue-based approximation of the spatially correlated UAV-to-user link, whose underlying independent diversity components are modeled as Nakagami-mfading. This approach addresses both line-of-sight (LoS) dominant rural and probabilistic non-line-of-sight (NLoS) urban scenarios. Furthermore, a high signal-to-noise ratio (SNR) asymptotic analysis is developed, revealing the fundamental diversity order of the UAV-to-user link. Based on this, we further address the practical issue of energy efficiency. A realistic energy efficiency maximization problem is formulated, which explicitly accounts for the time and energy overhead in the FAS port selection process. An efficient hierarchical algorithm is then proposed to jointly optimize the key system parameters. Extensive numerical results validate the analysis and illustrate that while FASs can yield substantial power gains, the operational overhead introduces a non-trivial trade-off, leading to an optimal number of ports and fundamentally different UAV deployment strategies in rural versus urban environments. In summary, this work provides both foundational analysis and practical design guidelines for FAS-enabled UAV communications.

Fluid antenna systems (FAS) utilize position reconfigurability to improve spatial diversity in wireless communications. However, a rigorous framework for error probability analysis under spatially correlated channels remains absent. This paper fills this gap by deriving a closed-form asymptotic expression for the symbol error rate (SER). This mathematical expression establishes the fundamental scaling law between the error performance and the spatial correlation matrix. A key insight from our analysis is that the achievable diversity gain depends entirely on the effective rank of the spatial channel, rather than the total number of antenna ports. To quantify this effective rank, we propose a dual approach: a theoretical derivation and a geometry-based algorithm. Both methods rigorously prove that the effective rank converges to a fundamental limit of$2W+1$, where$W$denotes the normalized aperture width. Specifically, the geometry-based algorithm extracts distinct performance thresholds from the eigenvalue spectrum of the channel. These thresholds perfectly match the derived theoretical limit. Furthermore, the proposed effective rank model demonstrates higher accuracy than existing approaches in the literature. Based on this robust framework, we offer a complete characterization of diversity gains and coding gains. The analytical results reveal a definitive design principle: enlarging the physical aperture increases the effective rank and drives performance improvements, whereas simply increasing port density within a fixed aperture yields diminishing returns.

In this paper, we investigate a joint communication and computation resource allocation strategy for an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system employing fluid antenna (FA). Specifically, each user is equipped with an FA to offload the entire computation tasks to the MEC server deployed on the UAV. By dynamically selecting antenna ports, users can achieve latency-efficient edge computing services, especially advantageous in dynamic environments. To minimize the maximum execution delay of all the users, we jointly optimize the UAV location, FA port selection, and computation resource allocation, subject to computational capacity constraints. The original non-convex optimization problem is decomposed into three tractable subproblems within a block coordinate descent (BCD) algorithm. The optimal computing frequencies are derived in closed form, while the UAV location and FA port selection are optimized using low-complexity iterative algorithms based on successive convex approximation (SCA) and linear programming (LP) techniques. In addition to conventional benchmarks with fixed-position antennas (FPAs), we also introduce a reconfigurable intelligent surface (RIS)-assisted system as a comparative baseline. Simulation results demonstrate that the proposed FA-assisted scheme significantly outperforms both FPAs and RIS-assisted counterparts, with performance gains becoming more pronounced in multi-task and highly dynamic scenarios, establishing FA-assisted UAV-MEC as a promising solution for future deployments.

In this paper, the framework of fluid antenna system (FAS)-assisted three dimensional (3D) passive unmanned aerial vehicle (UAV) positioning is developed. In the proposed framework, a set of controlled UAVs including an active UAV and four FAS-assisted passive UAVs, as well as a ground base station (BS) cooperatively estimate the real-time 3D position of a target UAV. Here, the active UAV transmits a measurement signal to the passive UAVs. This signal is reflected via the target UAV and received by the passive UAVs. Each passive UAV estimates the distance of the active-target-passive UAV link and selects an antenna port to share the distance information with the BS. The BS calculates the real-time position of the target UAV. As the target UAV is moving due to its task operation, the controlled UAVs must optimize their trajectories and select optimal antenna port for transmitting the positioning information, aiming to estimate the real-time position of the target UAV. We formulate an optimization problem that optimizes the trajectories of all controlled UAVs and antenna port selection of passive UAVs with the aim of minimizing the target UAV positioning error. To address this problem, an attention-based recurrent multiagent reinforcement learning (AR-MARL) scheme is proposed. In the proposed method, a recurrent neural network (RNN) acts as a local Q function of each controlled UAV to capture its historical state-action pairs, and a transformer is used to analyze the importance of these historical state-action pairs, thus improving the global$\mathbf{Q}$function approximation accuracy, thereby further improving the positioning accuracy. Simulation results show that the proposed AR-MARL scheme can reduce the average positioning error by up to 17.5 % and 58.5 % compared to the VD-MARL scheme and the proposed method without FAS.

This paper studies the ergodic achievable rates of a primitive Gaussian diamond channel with Rayleigh fading. The system is modeled as a two-hop relay channel where a single user communicates with a central processor (CP) through two relays. These relays are agnostic to the user's codebooks and are considered “primitive” because the fronthaul links are error-free but have limited capacity. In this setup, the channel state information (CSI) is assumed to be available only at the relays and not at the CP. Despite the simplicity of this configuration, deriving an accurate characterization of the ergodic capacity is surprisingly challenging. To address this, we first establish an analytical rate upper bound, assuming that the relays can cooperate and that the CP has access to the CSI as well. In order to obtain lower bounds, we resort to specific analytically/numerically tractable achievability strategies. When designing such strategies, we need to take into account that the CP has no CSI and that each relay has only statistical knowledge of the CSI other relay. Under these constraints, we propose two achievable schemes employing different estimation and compression methods at relays. Simulation results show that these schemes achieve performance close to the derived upper bound over a wide range of system parameters.

Reconfigurable intelligent surface (RIS) has gained significant attention as an innovative solution for enhancing communication system performance. This paper proposes a novel fluid RIS-assisted communication system with spatial adaptability, where the RIS is mounted on a slide rail. By leveraging both spatial flexibility and phase reconfigurability, the proposed system overcomes the limitations of conventional fixed-position RIS. To characterize the spatial variations introduced by RIS movement, we establish a novel channel modeling framework that combines near-field spherical wave propagation with practical visibility region functions. Experimental results reveal that dynamic RIS position yields received power gain variations ranging from 0.4 dB to 5.3 dB. This empirical evidence strongly validates the capability of fluid RIS to counteract channel non-stationarity.

This paper examines the impact of emerging fluid antenna systems (FAS) on reconfigurable intelligent surface (RIS)-aided secure communications. Specifically, we consider a classic wiretap channel, where a fixed-antenna transmitter sends confidential information to an FAS-equipped legitimate user with the help of an RIS, while an FAS-equipped eavesdropper attempts to decode the message. To evaluate the proposed wireless scenario, we first introduce the cumulative distribution function (CDF) and probability density function (PDF) of the signal-to-noise ratio (SNR) at each node, using the central limit theorem and the Gaussian copula function. We then derive a compact analytical expression for the secrecy outage probability (SOP). Our numerical results reveal how the incorporation of FAS and RIS can significantly enhance the performance of secure communications.

Enabling Mobile edge computing (MEC) services with massive connectivity and low energy consumption is crucial for future Internet of Things (IoT) infrastructures. In this article, we investigate an IoT network, where MEC is adopted as the computing framework for complicated IoT services while nonorthogonal multiple access (NOMA) is introduced to enable the interdependent data input offloading from multiple IoT devices to an edge server. The MEC service frame consists of a communication phase and a computation phase, where the latter phase requires the complete data offloaded in the former one to complete a specific task. To minimize the weighted sum energy consumption of both users and the edge server, a joint resource allocation original problem is formulated, which is unfortunately nonconvex. To tackle the difficulty, we first decompose the problem into subproblems, and characterize the structure of optimal solution to the subproblems. Following the characterization, the original problem is reformulated into a tractable one. We then develop a Branch-Reduce-and-Bound (BRB) based algorithm to obtain the optimal solution. Additionally, to further investigate the MEC scenario with the offloading of multiple users, we apply the state-of-the-art hybrid NOMA (H-NOMA) scheme to evaluate its benefits to multiuser MEC. We rigorously prove that, with interdependent user data inputs, pure NOMA (P-NOMA) is not only a special case but also an optimal case of H-NOMA. Via simulation, the analytical findings and the proposed algorithm are validated and evaluated.

Fluid antenna system (FAS) is an emerging technology that uses the new form of shape- and position-reconfigurable antennas to empower the physical layer for wireless communications. Prior studies on FAS were however limited to narrowband channels. Motivated by this, this paper addresses the integration of FAS in the fifth generation (5G) orthogonal frequency division multiplexing (OFDM) framework to address the challenges posed by wideband communications. We propose the framework of the wideband FAS-OFDM system that includes a novel port selection matrix. Then we derive the achievable rate expression and design the adaptive modulation and coding (AMC) scheme based on the rate. Extensive link-level simulation results demonstrate striking improvements of FAS in the wideband channels, underscoring the potential of FAS in future wireless communications.

This paper investigates a multiuser millimeter-wave (mmWave) uplink system in which each user is equipped with a multi-antenna fluid antenna system (FAS) while the base station (BS) has multiple fixed-position antennas. Our primary objective is to maximize the system capacity by optimizing the transmit covariance matrices and the antenna position vectors of the users jointly. To gain insights, we start by deriving upper bounds and approximations for the capacity. Then we delve into the capacity maximization problem. Beginning with the simple scenario of a single user equipped with a single-antenna FAS, we demonstrate that a closed-form optimal solution exists when there are only two propagation paths between the user and the BS. In the case where multiple propagation paths are present, a near-optimal solution can also be obtained through a one-dimensional search method. Expanding our focus to multiuser cases, in which users are equipped with either single- or multi-antenna FAS, we show that the original capacity maximization problems can be reformulated into distinct rank-one programmings. Then, we propose alternating optimization algorithms to deal with the transformed problems. Simulation results indicate that FAS can improve the capacity of the multiple access channel (MAC) greatly, and the proposed algorithms outperform all the benchmarks.

Fluid antenna system (FAS) is gaining attention as an innovative technology for boosting diversity and multiplexing gains. As a key innovation, it presents the possibility to overcome interference by position reconfigurability on one radio frequency (RF) chain, giving rise to the concept of fluid antenna multiple access (FAMA). While FAMA is originally designed to deal with interference mainly by position change and treat interference as noise, this is not rate optimal, especially when suffering from a strong interference channel (IC) where all positions have strong interference. To tackle this, this paper considers a two-user strong IC where FAMA is used in conjunction with simultaneous non-unique decoding (SND). Specifically, we analyze the key statistics for the signal-to-noise ratio (SNR) and interference-to-noise ratio (INR) for a canonical two-user IC setup, and subsequently derive the delay outage rate (DOR), outage probability (OP) and ergodic capacity (EC) of the FAMA-IC. Our numerical results illustrate huge benefits of FAMA with SND over traditional fixed-position antenna systems (TAS) with SND in the fading IC.

Fluid antenna multiple access (FAMA), enabled by the fluid antenna system (FAS), offers a new and straightforward solution to massive connectivity. Previous results on FAMA were primarily based on narrowband channels. This paper studies the adoption of FAMA within the fifth-generation (5G) orthogonal frequency division multiplexing (OFDM) framework, referred to as OFDM-FAMA, and evaluate its performance in broadband multipath channels. We first design the OFDM-FAMA system, taking into account 5G channel coding and OFDM modulation. Then the system’s achievable rate is analyzed, and an algorithm to approximate the FAS configuration at each user is proposed based on the rate. Extensive link-level simulation results reveal that OFDM-FAMA can significantly improve the multiplexing gain over the OFDM system with fixed-position antenna (FPA) users, especially when robust channel coding is applied and the number of radio-frequency (RF) chains at each user is small.

Fluid antenna system (FAS) has recently surfaced as a promising technology for the upcoming sixth generation (6G) wireless networks. Unlike traditional antenna system (TAS) with fixed antenna location, FAS introduces a flexible component in which the radiating element can switch its position within a predefined space. This capability allows FAS to achieve additional diversity and multiplexing gains. Nevertheless, to fully reap the benefits of FAS, obtaining channel state information (CSI) over the predefined space is crucial. In this paper, we study the system with a transmitter equipped with a traditional fixed antenna and a receiver with a fluid antenna by considering an electromagnetic-compliant channel model. We address the challenges of channel estimation and reconstruction using Nyquist sampling and maximum likelihood estimation (MLE) methods. Our analysis reveals a fundamental tradeoff between the accuracy of the reconstructed channel and the number of estimated channels, indicating that half-wavelength sampling is insufficient for perfect reconstruction and that oversampling is essential to enhance accuracy. Despite its advantages, oversampling can introduce practical challenges. Consequently, we propose a suboptimal sampling distance that facilitates efficient channel reconstruction. In addition, we employ the MLE method to bound the channel estimation error by$\epsilon $, with a specific confidence interval (CI). Our findings enable us to determine the minimum number of estimated channels and the total number of pilot symbols required for efficient channel reconstruction in a given space. Lastly, we investigate the rate performance of FAS and TAS and demonstrate that FAS with imperfect CSI can outperform TAS with perfect CSI. In contrast to existing works, we also show that there is an optimal fluid antenna size that maximizes the achievable rate when considering the energy and bandwidth overheads for full CSI acquisition.

This paper investigates the capacity performance of an uplink fluid antenna system (FAS), in which the base station (BS) is equipped with multiple fluid antennas and each user has a single fluid antenna. We aim to maximize the capacity of the system by optimizing the transmit power, and the user and BS antenna positions. Beginning with simple cases where the number of paths or the number of BS antennas is small, we reveal that the capacity is independent of the antenna positions. Then we give an upper bound on the capacity for the case where the BS has a single fluid antenna. After that, we show that in the optimal case, all users should transmit at the maximum power. Moreover, we propose an alternative algorithm to iteratively optimize the antenna positions at the BS and user sides. When keeping the user antenna positions fixed, the BS antenna positions are updated alternatively using a discrete exhaustive search in the single-user case. By transforming the capacity maximization problem into a difference-of-convex (DC) form, the majorization-minimization (MM) algorithm can also be applied to jointly optimize the BS antenna positions when there is a single user in the system. For the multiuser scenario, the antenna positions at the BS side are optimized utilizing the gradient descent method. We show that the user antenna positions can also be optimized using the discrete exhaustive search or the MM algorithm. Simulation results show that FAS can greatly improve the system capacity compared to traditional fixed-position antenna systems.

With the development of the upcoming sixth-generation (6G) wireless networks, there is a pressing need for innovative technologies capable of satisfying heightened performance indicators. Fluid antenna system (FAS) is proposed recently as a possible technique to achieve higher data rates and more diversity gains by dynamically changing the positions of the antennas to form a more desirable channel. However, worries regarding the possibly harmful effects of electromagnetic (EM) radiation emitted by devices have arisen due to the rapid evolution of advanced techniques in wireless communication systems. Specific absorption rate (SAR) is a widely adopted metric to quantify EM radiation worldwide. In this paper, we investigate the FAS-assisted multiuser multiple-input multiple-output (MIMO) communications with SAR constraints. In particular, an efficient algorithm is proposed to maximize the minimum weighted signal-to-interference-plus-noise ratio (SINR) under SAR and FAS constraints. Simulation results verify that the proposed SAR-aware FAS design outperforms the adaptive backoff and fixed-position antenna designs.

In this paper, we consider a remote source coding problem with binary phase shift keying (BPSK) modulation sources, where observations are corrupted by additive white Gaussian noise (AWGN). An intermediate node, such as a relay, receives these observations and performs further compression to find the optimal trade-off between complexity and relevance. This problem can be formulated as an information bottleneck (IB) problem with Bernoulli sources and Gaussian mixture observations, for which no closed-form solution is known. To address this challenge, we propose a unified achievable scheme that employs three different compression strategies for intermediate node processing, i.e., two-level quantization, multi-level deterministic quantization, and soft quantization with tanh function. Comparative analyses with existing methods, such as the Blahut-Arimoto (BA) algorithm and the Information Dropout approach, are performed through numerical evaluations. The proposed analytic scheme is observed to consistently approach the (numerically) optimal performance over a range of signal-to-noise ratios (SNRs), confirming its effectiveness in the considered setting.

This paper considers a Gaussian multi-input multi-output (MIMO) wiretap channel with a legitimate transmitter, a legitimate receiver (Bob), an eavesdropper (Eve), and a cooperative jammer. All nodes may be equipped with multiple antennas. Traditionally, the jammer transmits Gaussian noise (GN) to enhance the security. However, using this approach, the jamming signal interferes not only with Eve but also with Bob. In this paper, besides the GN strategy, we assume that the jammer can also choose to use the encoded jammer (EJ) strategy, i.e., instead of GN, it transmits a codeword from an appropriate codebook. In certain conditions, the EJ scheme enables Bob to decode the jamming codeword and thus cancel the interference, while Eve remains unable to do so even if it knows all the codebooks. We first derive an inner bound on the system’s secrecy rate under the strong secrecy metric, and then consider the maximization this bound through precoder design in a computationally efficient manner. In the single-input multi-output (SIMO) case, we prove that although non-convex, the power control problems can be optimally solved for both GN and EJ schemes. In the MIMO case, we propose to solve the problems using the matrix simultaneous diagonalization (SD) technique, which requires quite a low computational complexity. Simulation results show that by introducing a cooperative jammer with coding capability, and allowing it to switch between the GN and EJ schemes, a dramatic increase in the secrecy rate can be achieved. In addition, the proposed algorithms can significantly outperform the current state of the art benchmarks in terms of both secrecy rate and computation time.

This paper investigates the achievable region of a K-user discrete memoryless (DM) multiple access wiretap (MAC-WT) channel, where each user transmits both secret and open (i.e., non-confidential) messages. All these messages are intended for the legitimate receiver (Bob), while the eavesdropper (Eve) is only interested in the secret messages. In the achievable coding strategy, the confidential information is protected by open messages and also by the introduction of auxiliary messages. When introducing an auxiliary message, one has to ensure that, on one hand, its rate is large enough for protecting the secret message from Eve and, on the other hand, the resulting sum rate (together with the secret and open message rate) does not exceed Bob’s decoding capability. This yields an inequality structure involving the rates of all users’ secret, open, and auxiliary messages. To obtain the rate region, the auxiliary message rates must be eliminated from the system of inequalities. A direct application of the Fourier-Motzkin elimination procedure is elusive since a) it requires that the number of users K is explicitly given, and b) even for small$K = 3, 4, \ldots $, the number of inequalities becomes extremely large. We prove the result for general K through the combined use of Fourier-Motzkin elimination procedure and mathematical induction. This paper adopts the strong secrecy metric, characterized by information leakage. To prove the achievability under this criterion, we analyze the resolvability region of a K-user DM-MAC channel (not necessarily a wiretap channel). In addition, we show that users with zero secrecy rate can play different roles and use different strategies in encoding their messages. These strategies yield non-redundant (i.e., not mutually dominating) rate inequalities. By considering all possible coding strategies, we provide a new achievable region for the considered channel, and show that it strictly improves those already known in the existing literature by considering a specific example.

This paper investigates the performance of physical layer security (PLS) in fluid antenna-aided communication systems under arbitrary correlated fading channels. In particular, it is considered that a single fixed-antenna transmitter aims to send confidential information to a legitimate receiver equipped with a planar fluid antenna system (FAS), while an eavesdropper, also taking advantage of a planar FAS, attempts to decode the desired message. For this scenario, we first present analytical expressions of the equivalent channel distributions at the legitimate user and eavesdropper by using copula, so that the obtained analytical results are valid for any arbitrarily correlated fading distributions. Then, with the help of Gauss-Laguerre quadrature, we derive compact analytical expressions for the average secrecy capacity (ASC), the secrecy outage probability (SOP), and the secrecy energy efficiency (SEE) for the FAS wiretap channel. Moreover, for exemplary purposes, we also obtain the compact expression of ASC, SOP, and SEE by utilizing the Gaussian copula under correlated Rayleigh fading channels as a special case. Eventually, numerical results indicate that applying the fluid antenna with only one activated port to PLS can guarantee more secure and reliable transmission, when compared to traditional antenna systems (TAS) exploiting maximal ratio combining (MRC) and antenna selection (AS) under selection combining (SC).

To enable innovative applications and services, both industry and academia are exploring new technologies for sixth generation (6G) communications. One of the promising candidates is fluid antenna system (FAS). Unlike existing systems, FAS is a novel communication technology where its antenna can freely change its position and shape within a given space. Compared to the traditional systems, this unique capability has the potential of providing higher diversity and interference-free communications. Nevertheless, the performance limits of FAS remain unclear as its system properties are difficult to analyze. To address this, we approximate the outage probability and diversity gain of FAS in closed-form expressions. We then propose a suboptimal FAS with$N^{\ast}$ports, where a significant gain can be obtained over FAS with$N^{\ast}-1$ports whilst FAS with$N^{\ast}+1$ports only yields marginal improvement over the proposed suboptimal FAS. In this paper, we also provide analytical and simulation results to unfold the key factors that affect the performance of FAS. Limited to systems with one active radio frequency (RF)-chain, we show that the proposed suboptimal FAS outperforms single-antenna (SISO) system and selection combining (SC) system in terms of outage probability. Interestingly, when the given space is$\frac {\lambda }{2}$, the outage probability of the proposed suboptimal FAS with one active RF-chain achieves near to that of the maximal ratio combining (MRC) system with multiple active RF-chains.

Multiple-input multiple-output (MIMO) system has been the defining mobile communications technology in recent generations. With the ever-increasing demands looming towards the sixth generation (6G), we are in need of additional degrees of freedom that deliver further gains beyond MIMO. To this goal, fluid antenna system (FAS) has emerged as a new way to obtain spatial diversity using reconfigurable position-switchable antennas. Considering the case with more than one ports activated on a 2D fluid antenna surface at both ends, we take the information-theoretic approach to study the achievable performance limits of the MIMO-FAS. First of all, we propose a suboptimal scheme, referred to as QR MIMO-FAS, to maximize the rate at high signal-to-noise ratio (SNR) via joint port selection, transmit and receive beamforming and power allocation. We then derive the optimal diversity and multiplexing tradeoff (DMT) of MIMO-FAS. From the DMT, we highlight that MIMO-FAS outperforms traditional MIMO antenna systems. Further, we introduce a new metric, namelyq-outage capacity, which can jointly consider rate and outage probability. Through this metric, our results indicate that MIMO-FAS surpasses traditional MIMO greatly.

Fluid antenna system (FAS) is a new flexible antenna technology that offers a new approach to multiple access, referred to as fluid antenna multiple access (FAMA). The performance of FAMA has been investigated but previous results were based on simplified spatial correlation models. In this paper, we will revisit FAMA for the two-user case and study the outage probability by characterizing the joint spatial correlation among the ports. We first derive a closed-form lower bound on the outage probability and reveal that in the absence of spatial correlation, the outage probability of the system decreases exponentially as the number of ports increases. We then show that the channel model can be greatly simplified by focusing upon a limited number of channel variables, allowing us to derive the outage probability using the approximate model. To gain insight, we further approximate the channel model and provide another approximation of the outage probability that is easier to compute. Simulation results validate the approximations and demonstrate that the outage probability decreases with the number of ports but has an error floor unless the antenna size is increased. Also, when the number of ports is fixed, the outage probability initially decreases exponentially with the size but eventually approaches the lower bound.

Fluid antenna system (FAS) represents all forms of movable and non-movable position-flexible antenna system, and opens up the possibility of a new form of modulation schemes. In this paper, we investigate the design of position index modulation (PIM) for FAS for decreasing the bit error rate (BER) while taking advantage of the rate gain in index modulation. We further derive the BER and data rate expressions to assess the achievable performance of PIM. Simulation results are provided to illustrate the performance and some insights are drawn into the impact of both channel estimation accuracy and transmission power.

Fluid antenna system (FAS) is an emerging flexible antenna technology that provides a new way for multiple access. In fluid antenna multiple access (FAMA), each user switches its fluid antenna to the location (i.e., port) in which the interfering users suffer from a deep fade for interference-free communication. Previous work has attempted to understand the interference immunity of FAMA but the results are limited to simplified spatial correlation models. In this paper, we revisit the FAMA system with only two users by characterizing the joint spatial correlation amongst all the ports. Using this model, however, the number of variables determining each channel coefficient scales with that of ports, hence making the analysis intractable. To tackle this, we first show that the channel model could be considerably simplified by taking into account only a few variables, and then derive the outage probability for the considered FAMA system by using the approximated model. Simulation results show that the simplified channel model can quickly approach the exact one and that the outage probability decreases with the number of ports but has an error floor unless the size of fluid antenna is increased.

This paper considers the distributed information bottleneck (D-IB) problem for a primitive Gaussian diamond channel with two relays and MIMO Rayleigh fading. The channel state is an independent and identically distributed (i.i.d.) process known at the relays but unknown to the destination. The relays are oblivious, i.e., they are unaware of the codebook and treat the transmitted signal as a random process with known statistics. The bottleneck constraints prevent the relays to communicate the channel state information (CSI) perfectly to the destination. To evaluate the bottleneck rate, we provide an upper bound by assuming that the destination node knows the CSI and the relays can cooperate with each other, and also two achievable schemes with simple symbol-by-symbol relay processing and compression. Numerical results show that the lower bounds obtained by the proposed achievable schemes can come close to the upper bound on a wide range of relevant system parameters.

This paper investigates the information-theoretic secrecy problem for a K-user discrete memoryless (DM) multiple-access wiretap (MAC-WT) channel. Instead of using the weak secrecy criterion characterized by information leakage rate, we adopt the strong secrecy metric defined by information leakage to better protect the confidential information. We provide an achievable rate region and prove its achievability by providing a coding scheme and analyzing the output statistics in terms of (average) variational distance. We show that the rate region obtained in previous works on the subject is a special case of ours. We also show that the achievability proof in such works is incomplete, because it is assumed that certain inequalities hold while they may not in some cases. We solve this problem by constructing an inequality structure for the rates of all users’ secret and redundant messages, and analyzing the conditions required to maintain this structure.

This paper considers the distributed information bottleneck (D-IB) problem for a primitive Gaussian diamond channel with two relays and Rayleigh fading. Due to the bottleneck constraint, it is impossible for the relays to inform the destination node of the perfect channel state information (CSI) in each realization. To evaluate the bottleneck rate, we provide an upper bound by assuming that the destination node knows the CSI and the relays can cooperate with each other, and also three achievable schemes with simple symbol-by-symbol relay processing and compression. Numerical results show that the lower bounds obtained by the proposed achievable schemes can come close to the upper bound on a wide range of relevant system parameters.

This paper investigates the secrecy achievable region of multiple access wiretap (MAC-WT) channels where, besides confidential messages, the users have also open messages to transmit. All these messages are intended for the legitimate receiver (or Bob for brevity) but only the confidential messages need to be protected from the eavesdropper (Eve). We first consider a discrete memoryless (DM) MAC-WT channel where both Bob and Eve jointly decode their interested messages. By using random coding, we find an achievable rate region, within which perfect secrecy can be realized, i.e., all users can communicate with Bob with arbitrarily small probability of error, while the confidential information leaked to Eve tends to zero. Due to the high implementation complexity of joint decoding, we also consider the DM MAC-WT channel where Bob simply decodes messages independently while Eve still applies joint decoding. We then extend the results in the DM case to a Gaussian vector (GV) MAC-WT channel. Based on the information theoretic results, we further maximize the sum secrecy rate of the GV MAC-WT system by designing precoders for all users. Since the problems are non-convex, we provide iterative algorithms to obtain suboptimal solutions. Simulation results show that compared with existing schemes, secure communication can be greatly enhanced by the proposed algorithms, and in contrast to the works which only focus on the network secrecy performance, the system spectrum efficiency can be effectively improved since open messages can be simultaneously transmitted.

This paper considers the information bottleneck (IB) problem of a Rayleigh fading multiple-input multiple-out (MIMO) channel. Due to the bottleneck constraint, it is impossible for the oblivious relay to inform the destination node of the perfect channel state information (CSI) in each channel realization. To evaluate the bottleneck rate, we provide an upper bound by assuming that the destination node can get the perfect CSI at no cost and two achievable schemes with simple symbol-by-symbol relay processing and compression. Numerical results show that the lower bounds obtained by the proposed achievable schemes can come close to the upper bound on a wide range of relevant system parameters.

In this paper, the implementation of a distributed primal-dual learning algorithm over realistic wireless networks is investigated. In the considered model, the users and one base station (BS) cooperatively perform a distributed primal-dual learning algorithm for controlling and optimizing wireless networks. In particular, each user must locally update the primal and dual variables and send the updated primal variables to the BS. The BS aggregates the received primal variables and broadcasts the aggregated variables to all users. Since all of the primal and dual variables as well as aggregated variables are transmitted over wireless links, the imperfect wireless links will affect the solution achieved by the distributed primal-dual algorithm. Therefore, it is necessary to study how wireless factors such as transmission errors affect the implementation of the distributed primal-dual algorithm and how to optimize wireless network performance to improve the solution achieved by the distributed primal-dual algorithm. To address these challenges, the convergence rate of the primal-dual algorithm is provided in a closed form while considering the impact of wireless factors such as data transmission errors. Simulation results show that the proposed distributed primal-dual algorithm can reduce the gap between the target and obtained solution compared to the distributed primal-dual learning algorithm without considering imperfect wireless transmission.

In this paper, we study the robust secure unmanned aerial vehicle (UAV) communication system, where a UAV with full-duplex (FD) capability simultaneously receives the information signal from a ground unit (GU) and transmits jamming signal to degrade the wiretap capability of potential multiple ground eavesdroppers (Eves). With the consideration of estimation error of Eves' locations, we aim to maximize the average worst secrecy rate inside a certain flight period of the UAV by jointly optimizing the transmit power of the GU and UAV as well as the trajectory of the UAV. The resulting problem is intractable due to its non-convex nature and strongly coupled variables. Furthermore, the estimation error of Eves' locations results in an infinite number of constraints, which makes the problem even more difficult. To tackle this difficulty, we first propose an iterative algorithm based on the Schur complement lemma and successive inner approximation method to efficiently solve the problem suboptimally under the estimated Eves' locations. Then, in order to cope with the of Eves' location errors, we develop a cutting-set method, which solves the problem by alternating between optimal power-trajectory design and worst-case Eves' locations analysis. Via simulation, we show the improvement of the proposed algorithm compared to other benchmark algorithms under high FD self-interference cancellation levels.

This paper investigates the capacity region of a discrete memoryless (DM) multiple access wiretap (MAC-WT) channel where, besides confidential messages, the users have also open messages to transmit. All these messages are intended for the legitimate receiver but only the confidential messages need to be protected from the eavesdropper. By using random coding, we find an achievable secrecy rate region, within which perfect secrecy can be realized, i.e., all users can communicate with the legitimate receiver with arbitrarily small probability of error, while the confidential information leaked to the eavesdropper tends to zero.

This paper investigates the secrecy rate performance of a device-to-device (D2D) underlaid cellular network with an eavesdropper. Both the base station (BS) and the eavesdropper are assumed to have multiple antennas and apply minimum mean-square error (MMSE) receivers for detection. Different from the literature, mainly focused on enhancing the security of cellular communication using D2D jammers while neglected the secrecy performance of D2D communication, this paper aims to maximize the instantaneous weighted sum secrecy rate (IWSSR) of both cellular and D2D users. The maximization of IWSSR with respect to the transmit power of mobile users is a non-convex problem with non-differentiable objective function. In order to obtain efficient feasible solutions, we transform the IWSSR maximization problem to a min-max problem, relax the non-negative operator in secrecy rate expressions and then propose an alternative algorithm to solve the remaining problem. Simulation results show that the IWSSR of the network can be effectively increased by the proposed algorithm and, compared with exhaustive search (ES), the proposed algorithm performs very close to ES and involves much less computational complexity.

This paper investigates the dynamic access point (AP) clustering and precoding problem in the downlink of user-centric virtual cell networks. The goal is to maximize the weighted sum spectral efficiency (SE) while satisfying the power constraints and AP clustering constraints in adjacent time slots (TSs). By adopting the random walk mobility to model the mobile user equipments' movement behaviors, we consider dynamic and time-varying channel conditions. Therefore, the weighted sum SE maximization programming takes the form of discrete-time sequence of mixed-integer non-convex optimization problems. In this paper, we propose to solve this sequential problem in two stages. In the first stage, a dynamic AP clustering approach based on discrete particle swarm optimization is developed. This approach takes the advantage of the channel correlation by exploiting the relationship between AP clustering solutions in adjacent TSs to improve the SE performance and reduce complexity. In the second stage, given the AP clustering solution obtained in the first stage, a distributed precoding algorithm is devised via applying the weighted minimum mean square error method. By combining these two stages, we propose a novel dynamic AP clustering and precoding algorithm (DAPC-Pre). The effectiveness of the proposed DAPC-Pre algorithm is verified by the simulation results. In particular, the proposed algorithm converges fast and significantly outperforms benchmark algorithms in terms of sum SE under different dynamic environments.

This paper analyzes the ergodic capacity of a user-centric virtual cell (VC) dense network, where multiple access points (APs) form a VC for each user equipment (UE) and transmit data cooperatively over millimeter wave (mmWave) channels. Different from traditional microwave radio communications, blockage phenomena have an important effect on mmWave transmissions. Accordingly, we adopt a distance-dependent line- of-sight (LOS) probability function and model the locations of the LOS and non-line-of-sight (NLOS) APs as two independent non-homogeneous Poisson point processes (PPP). Invoking this model in a VC dense network, new expressions are derived for the downlink ergodic capacity, accounting for: blockage, small-scale fading and AP cooperation. In particular, we compare the ergodic capacity for different types of fading distributions, including Rayleigh and Nakagami. Numerical results validate our analytical expressions and show that AP cooperation can provide notable capacity gain, especially in low- AP-density regions.

This paper investigates the physical layer security issue of a device-to-device (D2D) underlaid cellular system with a multi-antenna base station (BS) and a multi-antenna eavesdropper. To investigate the potential of D2D communication in improving network security, the conventional network without D2D users (DUs) is first considered. It is shown that the problem of maximizing the sum secrecy rate (SR) of cellular users (CUs) for this special case can be transformed to an assignment problem and optimally solved. Then, a D2D underlaid network is considered. Since the joint optimization of resource block (RB) allocation, CU-DU matching and power control is a mixed integer programming, the problem is difficult to handle. Hence, the RB assignment process is first conducted by ignoring D2D communication, and an iterative algorithm is then proposed to solve the remaining problem. Simulation results show that the sum SR of CUs can be greatly increased by D2D communication, and compared with the existing schemes, a better secrecy performance can be obtained by the proposed algorithms.

In this paper, we consider the network utility maximization problem with various user priorities via jointly optimizing user association, load distribution, and power control in a load-coupled heterogeneous network. In order to tackle the nonconvexity of the problem, we first analyze the problem by obtaining the optimal resource allocation strategy in closed form and characterizing the optimal base station load distribution pattern. Both observations are shown essential in simplifying the original problem and making it possible to transform the nonconvex load distribution and power control problem into convex reformulation via exponential variable transformation. An iterative algorithm with low complexity is accordingly presented to obtain a suboptimal solution to the joint optimization problem. Simulation results show that the proposed algorithm achieves better performance than conventional approaches.

Full‐duplex relay‐assisted device‐to‐device (D2D) communication underlaying fifth generation cellular networks allow devices to exchange information directly and extend coverage via relay strategy. In this study, the authors consider such a scenario, where the D2D communications assisted by fixed‐location full‐duplex relays in interference existing circumstance. Different from previous works, they assume that there are two types of users, cellular users and D2D users. They investigate power control problem and coverage probability performance in the previously assumed situation. Therefore, an effective power control scheme is of great importance to suppress interference between D2D and cellular communications, which can improve the total system throughput and spectral efficiency. To describe it, they formulate a power control optimisation problem for cellular communication and propose a simple on–off power control algorithm for D2D communication. They also obtain an analytic expression for the coverage probability of the cellular link using stochastic geometry according to the proposed algorithm. Simulation results follow to show the rates of both cellular and D2D links in the various numbers of D2D transceivers.

This paper studies pilot reuse and data transmit power control in a D2D underlay massive MIMO system over fading channels. In order to reduce the length of pilots, we propose to reuse a set of orthogonal pilots among DUEs, and the graph coloring based pilot allocation (GCPA) algorithm is utilized to allocate pilots to DUEs. Linear minimum mean square error (LMMSE) filters are used for signal detection. We then derive the lower bound of D2D links' average signal-to-interference-plus-noise ratio (SINR), and formulate a power control problem to minimize D2D links' data transmit power under the target SINR constraints. An iterative method converging to the unique optimal solution is proposed. Simulation results show that the analytical lower bound of the average SINR closely matches the simulated average SINR. What's more, pilot resources can be saved greatly by pilot reuse, and the effect of pilot contamination to the system can be almost neglected by allocating proper number of pilots to DUEs and applying GCPA algorithm.

In this paper, we consider the problem of maximizing the sum energy efficiency (EE) for LTE networks where the interferences occur between cells. Cell load, transmit rate and transmit power, where cell load demonstrates the average resource usage in a cell, are considered in the signal-to- interference-and-noise-ratio (SINR) model. Exploiting the properties of sum EE, we prove that operating at full load is optimal and provide a distributed power control algorithm. With all other powers fixed, we transform the original nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form. In high SINR situation, the transformed problem in subtractive form is proved a convex problem. Numerical results demonstrate the remarkable improvements in terms of EE.

This paper exploits the noncentral communication architecture for increasing system throughput with popular video files cached in user equipments, and transmitted through D2D links under control of base station. A cell is divided into equilateral hexagon clusters among which frequency resources are reused. In order to reduce inter-cluster interference, we propose to limit the transmit power of each user and adopt relay-assisted D2D communication when direct D2D link can not be established in a cluster. Simulation results show that the proposed scheme can achieve higher spectral efficiency without much degradation in system throughput when compared with the scenario where different frequency resources are used by different clusters.