The reconstruction of sparse signal is an active area of research. Different from a typical i.i.d. assumption, this paper considers a non-independent prior of group structure. For this more practical setup, we propose EM-aided HyGEC, a new algorithm to address the stability issue and the hyper-parameter issue facing the other algorithms. The instability problem results from the ill condition of the transform matrix, while the unavailability of the hyper-parameters is a ground truth that their values are not known beforehand. The proposed algorithm is built on the paradigm of HyGAMP (proposed by Rangan et al.) but we replace its inner engine, the GAMP, by a matrix-insensitive alternative, the GEC, so that the first issue is solved. For the second issue, we take expectation-maximization as an outer loop, and together with the inner engine HyGEC, we learn the value of the hyper-parameters. Effectiveness of the proposed algorithm is also verified by means of numerical simulations.
The reconfigurable intelligent surface (RIS) has arose an upsurging research interest recently due to its promising outlook in 5G-and-beyond wireless networks. With the assistance of RIS, the wireless propagation environment is no longer static and could be customized to support diverse service requirements. In this paper, we will approach the rate maximization problems in RIS-aided wireless networks by considering the beamforming and reflecting design jointly. Three representative design problems from different system settings are investigated based on a proposed unified algorithmic framework…
This paper investigates multiple intelligent reflecting surfaces (IRSs) aided wireless network, where the IRSs are deployed to cooperatively assist communications between a multi-antenna base station (BS) and multiple single-antenna cell-edge users. We aim at maximizing the weighted sum rate of all the cell-edge users by jointly optimizing the BS's transmit beamforming and IRS's phase shifts. Especially, the beamforming is optimally solved by the Lagrangian method, and the phase shifts are obtained based on the Riemannian manifold conjugate gradient (RMCG) method. Numerical results show that a…
Reducing computational complexity is crucial in optimizing the phase shifts of Intelligent Reflecting Surface (IRS) systems since IRS-assisted communication systems are generally deployed with a large number of reflecting elements (REs). This letter proposes a low-complexity algorithm, designated as Dimension-wise Sinusoidal Maximization (DSM), to obtain the optimal IRS phase shifts that maximize the sum capacity of a MIMO network. The algorithm exploits the fact that the objective function for the optimization problem is sinusoidal w.r.t. the phase shift of each RE. The numerical results show…
This paper investigates full-duplex unmanned aerial vehicle (UAV) aided small cell wireless systems, where the UAV serving as the base station (BS) is designed to transmit data to the downlink users and receive data from the uplink users simultaneously. To maximize the total system capacity, including uplink and downlink capacity, the UAV trajectory, downlink/uplink user scheduling, and uplink user transmit power are alternately optimized. The resulting optimization problem is mixed-integer and non-convex, which is challenging to solve. To address it, the block coordinate descent method and su…
Reconfigurable intelligent surface (RIS) has recently drawn intensive attention due to its potential of simultaneously realizing high spectral and energy efficiency in a sustainable way. This paper focuses on the design of efficient transmission methods to maximize the uplink sum throughput in a RIS-aided multi-user multi-input multi-output (MU-MIMO) system. To provide an insightful basis, the channel capacity of RIS-aided MU-MIMO is theoretically analyzed. Then, the conventional transmission schemes based on orthogonal multiple access are presented as the baseline. From the information-theore…
Relay-aided transmission is envisioned as a key strategy to combat severe path loss and link blockages emerging as unique challenges in millimeter-wave (mmWave) communications. This work considers a relay-aided multiuser mmWave communications scenario aiming at maximizing the sum rate through optimal transmit and relay precoder design. We propose a novel joint precoder design strategy, which exploits weighted minimum mean-square error (WMMSE) using its equivalency to sum-rate maximization. We obtain closed form expressions of transmit and relay precoders, and propose to compute them through al…
This paper considers an active intelligent reflecting surface (IRS)-aided wireless powered communication network (WPCN), where devices first harvest energy and then transmit information to a hybrid access point (HAP). Different from the existing works on passive IRS-aided WPCNs, this is the first work that introduces the active IRS in WPCNs. To guarantee fairness, the problem is formulated as an amplifying power-limited weighted sum throughput (WST) maximization problem, which is solved by successive convex approximation technique and fractional programming alternatively. To balance the perfor…
In this paper, the novel simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS), which enables full-space coverage on users located on both sides of the surface, is investigated in the multi-user mobile edge computing (MEC) system. A computation rate maximization problem is formulated via the joint design of the STAR-RIS phase shifts, reflection and transmission amplitude coefficients, the receive beamforming vectors at the access point, and the users' energy partition strategies for local computing and offloading. Two operating protocols of STAR-RIS, namely…
In this paper, we consider an unmanned aerial vehicle (UAV) aided mobile relaying system under a buffer constraint. We propose a new relaying protocol employing mixed free-space optical/radio frequency (FSO/RF) communication, i.e., the source-relay and relay-destination links utilize FSO and RF links, respectively, under the buffer constraint at the UAV relay node. Taking the conditions of an imbalance in transmission rate between RF and FSO links into consideration, we study the trajectory optimization problem of buffer-constrained UAV relay node in order to maximize the end-to-end data throu…
In this paper, the problem of sum-rate maximization for an active reconfigurable intelligent surface (RIS) assisted downlink rate-splitting multiple access (RSMA) transmission system is studied. In the considered model, the active RIS is deployed to overcome severe power attenuation, which is caused by the cumulative product of RIS incidence path loss and the reflection path loss. Since the active RIS can adjust both the phase and the amplitude of the incident signal simultaneously, the RIS control scheme requires delicate design to improve RSMA communication performance. To address this issue…
This paper investigates unmanned aerial vehicle (UAV)-aided backscatter communication (BackCom) networks, where the UAV is leveraged to help the backscatter device (BD) forward signals to the receiver. Based on the presence or absence of a direct link between BD and receiver, two protocols, namely transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR) protocol, are proposed to utilize the UAV to assist the BD. In particular, we formulate the system throughput maximization problems for the two protocols by jointly optimizing the time allocation, reflection coefficient and UAV t…
In this work, two problems associated with a downlink multi-user system are considered with the aid of intelligent reflecting surface (IRS): weighted sum-rate maximization and weighted minimal-rate maximization. For the first problem, a novel DOuble Manifold ALternating Optimization (DOMALO) algorithm is proposed by exploiting the matrix manifold theory and introducing the beamforming matrix and reflection vector using complex sphere manifold and complex oblique manifold, respectively, which incorporate the inherent geometrical structure and the required constraint. A smooth double manifold al…
A two-user downlink network aided by a reconfigurable intelligent surface is considered. The weighted sum signal to interference plus noise ratio maximization and the sum rate maximization models are presented, where the precoding vectors and the RIS matrix are jointly optimized. Since the optimization problem is non-convex and difficult, new approximation models are proposed. The upper bounds of the corresponding objective functions are derived and maximized. Two new algorithms based on the alternating direction method of multiplier are proposed. It is proved that the proposed algorithms conv…
This paper studies an intelligent reflecting surface (IRS)-aided multiple-input-multiple-output (MIMO) full-duplex (FD) wireless-powered communication network (WPCN), where a hybrid access point (HAP) operating in FD broadcasts energy signals to multiple devices for their energy harvesting (EH) in the downlink (DL) and meanwhile receives information signals from devices in the uplink (UL) with the help of an IRS. Taking into account the practical finite self-interference (SI) and the non-linear EH model, we formulate the weighted sum throughput maximization optimization problem by jointly opti…
In this paper, we investigate opportunistic relaying and jamming techniques and develop relay selection algorithms that maximize the secrecy rate for multiuser buffer-aided relay networks. We develop an approach to maximize the secrecy rate of relay systems that does not require the channel state information (CSI) of the eavesdroppers. We also devise relaying and jamming function selection (RJFS) algorithms to select multiple relay nodes as well as multiple jamming nodes to assist the transmission. In the proposed RJFS algorithms inter-relay interference cancellation (IC) is taken into account…
Reconfigurable intelligent surface (RIS) has the potential to significantly enhance the network secure transmission performance by reconfiguring the wireless propagation environment. However, due to the passive nature of eavesdroppers and the cascaded channel brought by the RIS, the eavesdroppers' channel state information is imperfectly obtained at the base station. Under the channel uncertainty, the optimal phase-shift, power allocation, and transmission rate design for secure transmission is currently unknown due to the difficulty of handling the probabilistic constraint with coupled variab…
This paper investigates a reconfigurable intelligent surface (RIS)-aided multi-user multiple-input multiple-output (MIMO) system by considering only the statistical channel state information (CSI) at the base station (BS). We aim to maximize its sum-rate via the joint optimization of beamforming at the BS and phase shifts at the RIS. However, the multi-user MIMO transmissions and the spatial correlations make the optimization cumbersome. For tractability, a deterministic approximation is derived for the sum-rate under a large number of the reflecting elements. By adopting the approximate sum-r…
An unsupervised learning approach based on expectation maximization is proposed to obtain the parameters of a soft decision forward error correction decoding metric for probabilistic shaping. The algorithm depends only on the channel observations and does not require transmitted data.
Intelligent reflecting surface (IRS) is a promising technology to extend the wireless signal coverage and support the high performance communication. By intelligently adjusting the reflection coefficients of a large number of passive reflecting elements, the IRS can modify the wireless propagation environment in favour of signal transmission. Different from most of the prior works which did not consider any cooperation between IRSs, in this work we propose and study a cooperative double-IRS aided multiple-input multiple-output (MIMO) communication system under the line-of-sight (LoS) propagati…
Multiuser massive multiple-input multiple-output (MU-MIMO) systems can be used to meet high throughput requirements of 5G and beyond networks. In an uplink MUMIMO system, a base station is serving a large number of users, leading to a strong multi-user interference (MUI). Designing a high performance detector in the presence of a strong MUI is a challenging problem. This work proposes a novel detector based on the concepts of expectation propagation (EP) and graph neural network, referred to as the GEPNet detector, addressing the limitation of the independent Gaussian approximation in EP. The …
Adopting one-bit analog-to-digital convertors (ADCs) for massive multiple-input multiple-output (MIMO) implementations has great potential in reducing the hardware cost and power consumption. However, distortions caused by quantization raise great challenges. In MIMO orthogonal frequency-division modulation (OFDM) detection, coarse quantization renders the orthogonal separation among subcarriers inapplicable, forcing us to deal with a problem that has a very large problem size. In this paper we study the expectation-maximization (EM) approach for one-bit MIMO-OFDM detection. The idea is to ite…
This paper studies unmanned aerial vehicle (UAV) aided wireless communication systems where a UAV supports uplink communications of multiple ground nodes (GNs) while flying over the area of the interest. In this system, the propulsion energy consumption at the UAV is taken into account so that the UAV's velocity and acceleration should not exceed a certain threshold. We formulate the minimum average rate maximization problem and the energy efficiency (EE) maximization problem by jointly optimizing the trajectory, velocity, and acceleration of the UAV and the uplink transmit power at the GNs. A…
This paper investigates unmanned aerial vehicle (UAV)-aided wireless powered communication network (WPCN) systems where a mobile access point (AP) at the UAV serves multiple energy-constrained ground terminals (GTs). Specifically, the UAVs first charge the GTs by transmitting the wireless energy transfer (WET) signals in the downlink. Then, by utilizing the harvested wireless energy from the UAVs, the GTs send their uplink wireless information transmission (WIT) signals to the UAVs. In this paper, depending on the operations of the UAVs, we adopt two different scenarios, namely integrated UAV …
The low efficiency of far-field wireless power transfer (WPT) limits the fundamental rate-energy (R-E) performance trade-off of the simultaneous wireless information and power transfer (SWIPT) system. To address this challenge, we propose in this letter a new SWIPT system aided by the emerging intelligent reflecting surface (IRS) technology. By leveraging massive low-cost passive elements that are able to reflect the signals with adjustable phase shifts, IRS achieve a high passive beamforming gain, which is appealing for drastically enhancing the WPT efficiency and thereby the R-E trade-off of…
In a directional modulation network, a general power iterative (GPI) based beamforming scheme is proposed to maximize the secrecy rate (SR), where there are two optimization variables required to be optimized. The first one is the useful precoding vector of transmitting confidential messages to the desired user while the second one is the artificial noise (AN) projection matrix of forcing more AN to eavesdroppers. In such a secure network, the paramount problem is how to design or optimize the two optimization variables by different criteria. To maximize the SR (Max-SR), an alternatively itera…
Channel modeling is a critical issue when designing or evaluating the performance of reconfigurable intelligent surface (RIS)-assisted communications. Inspired by the promising potential of learning-based methods for characterizing the radio environment, we present a general approach to model the RIS end-to-end equivalent channel using the unsupervised expectation-maximization (EM) learning algorithm. We show that an EM-based approximation through a simple mixture of two Nakagami-$m$ distributions suffices to accurately approximating the equivalent channel, while allowing for the incorporation…
Generalized Vector Approximate Message Passing (GVAMP) is an efficient iterative algorithm for approximately minimum-mean-squared-error estimation of a random vector $\mathbf{x}\sim p_{\mathbf{x}}(\mathbf{x})$ from generalized linear measurements, i.e., measurements of the form $\mathbf{y}=Q(\mathbf{z})$ where $\mathbf{z}=\mathbf{Ax}$ with known $\mathbf{A}$, and $Q(\cdot)$ is a noisy, potentially nonlinear, componentwise function. Problems of this form show up in numerous applications, including robust regression, binary classification, quantized compressive sensing, and phase retrieval. In s…
We study the problem of downlink channel estimation in multi-user massive multiple input multiple output (MIMO) systems. To this end, we consider a Bayesian compressive sensing approach in which the clustered sparse structure of the channel in the angular domain is employed to reduce the pilot overhead. To capture the clustered structure, we employ a conditionally independent identically distributed Bernoulli-Gaussian prior on the sparse vector representing the channel, and a Markov prior on its support vector. An expectation propagation (EP) algorithm is developed to approximate the intractab…
