1,474 publications from this institution
Movable antenna (MA) technology is a recent development that fully exploits the wireless channel spatial variation in a confined region by enabling local movement of the antenna. Specifically, the positions of antennas at the transmitter and/or receiver can be dynamically changed to obtain better channel conditions for improving the communication performance. In this article, we first provide an overview of the promising applications for MA-aided wireless communication. Then, we present the hardware architecture and channel characterization for MA systems, based on which the variation of the channel gain with respect to the MA's position is illustrated. Furthermore, we analyze the performance advantages of MAs over conventional fixed-position antennas, in terms of signal power improvement, interference mitigation, flexible beamforming, and spatial multiplexing. Finally, we discuss the main design challenges and their potential solutions for MA-aided communication systems.
Radio waves carry both energy and information simultaneously. Nevertheless, Radio-Frequency (RF) transmission of these quantities have traditionally been treated separately. Currently, we are experiencing a paradigm shift in wireless network design, namely unifying wireless transmission of information and power so as to make the best use of the RF spectrum and radiations as well as the network infrastructure for the dual purpose of communicating and energizing. In this paper, we review and discuss recent progress on laying the foundations of the envisioned dual purpose networks by establishing a signal theory and design for Wireless Information and Power Transmission (WIPT) and identifying the fundamental tradeoff between conveying information and power wirelessly. We start with an overview of WIPT challenges and technologies, namely Simultaneous Wireless Information and Power Transfer (SWIPT),Wirelessly Powered Communication Network (WPCN), and Wirelessly Powered Backscatter Communication (WPBC). We then characterize energy harvesters and show how WIPT signal and system designs crucially revolve around the underlying energy harvester model. To that end, we highlight three different energy harvester models, namely one linear model and two nonlinear models, and show how WIPT designs differ for each of them in single-user and multi-user deployments. Topics discussed include rate-energy region characterization, transmitter and receiver architecture, waveform design, modulation, beamforming and input distribution optimizations, resource allocation, and RF spectrum use. We discuss and check the validity of the different energy harvester models and the resulting signal theory and design based on circuit simulations, prototyping and experimentation. We also point out numerous directions that are promising for future research.
Recent advances in wireless power transfer (WPT) technology provide a cost-effective solution to charge wireless devices remotely without disruption to the use. In this paper, we propose an efficient wireless charging control method for exploiting the frequency diversity in multiuser broadband wireless networks, to reduce energy outage and keep the system operating in an efficient and sustainable state. In particular, we first analyze the impact of charging control method to the operating lifetime of a WPT-enabled broadband system. Based on the analysis, we then propose a multi-criteria charging control policy that optimizes the transmit power allocation over frequency by jointly considering the channel state information (CSI) and the battery state information (BSI) of wireless devices. For practical implementation, the proposed scheme is realized by a novel limited CSI estimation mechanism embedded with partial BSI, which significantly reduces the energy cost of CSI and BSI feedback. Simulation results show that the proposed method could significantly increase the network lifetime under stringent transmit power constraint. Reciprocally, it also consumes lower transmit power to achieve near-perpetual network operation than other single-criterion based charging control methods.
No abstract is provided for this article.
Digital modulation error parameters, such as error vector magnitude EVM, is important in test and measurement of information system. This paper introduces the technology research progress in the metrology of digital modulation error parameters. First, we point out the basic problems existing in the field, which is about traceability and parameter range of calibration, and describe the relevant research, such as the thinking and technology of the `RF waveform metrology'. Then, we highlight the research progress of our team: 1). The metrology method and system for digital demodulation error parameter based on CW combination, which fits BPSK, QPSK, 8PSK, 16QAM, 64QAM modulation: this method can achieve traceability and error setting ability in a wide range, when standard EvmRms is 1.585%, the expanded uncertainty (k=2) is 0.009%. 2). The metrology method and system for digital demodulation error parameter based on analog AM or PM. 3). The metrology method and system for digital demodulation error parameter based on IQ gain imbalance and phase imbalance. 4). The metrology method and system for digital demodulation error parameter based on analog PM in the aspect of GMSK and FSK modulation. 5). The metrology method and system for digital demodulation error parameter based on Baseband waveform design. Based on these methods, our proposal are given as follows: first, establish public metrology standard for digital modulation error parameters; second, develop a new type of instrument "vector signal analyzer calibrator".
Intelligent reflecting surface (IRS) has emerged as a promising technique to control wireless propagation environment for enhancing the communication performance cost-effectively. However, the rapidly time-varying channel in high-mobility communication scenarios such as vehicular communication renders it challenging to obtain the instantaneous channel state information (CSI) efficiently for IRS with a large number of reflecting elements. In this paper, we propose a new roadside IRS-aided vehicular communication system to tackle this challenge. Specifically, by exploiting the symmetrical deployment of IRSs with inter-laced equal intervals on both sides of the road and the cooperation among nearby IRS controllers, we propose a new two-stage channel estimation scheme with off-line and online training, respectively, to obtain the static/time-varying CSI required by the proposed low-complexity passive beamforming scheme efficiently. The proposed IRS beamforming and online channel estimation designs leverage the existing uplink pilots in wireless networks and do not require any change of the existing transmission protocol. Moreover, they can be implemented by each of IRS controllers independently, without the need of any real-time feedback from the user's serving BS. Simulation results show that the proposed designs can efficiently achieve the high IRS passive beamforming gain and thus significantly enhance the achievable communication throughput for high-speed vehicular communications.
This paper studies a new and challenging wireless surveillance problem where a legitimate monitor attempts to eavesdrop two suspicious communication links simultaneously. To facilitate concurrent eavesdropping, our multi-antenna legitimate monitor employs a proactive eavesdropping via jamming approach, by selectively jamming suspicious receivers to lower the transmission rates of the target links. In particular, we are interested in characterizing the achievable eavesdropping rate region for the minimum-mean-squared-error (MMSE) receiver case, by optimizing the legitimate monitor's jamming transmit covariance matrix subject to its power budget. As the monitor cannot hear more than what suspicious links transmit, the achievable eavesdropping rate region is essentially the intersection of the achievable rate region for the two suspicious links and that for the two eavesdropping links. The former region can be purposely altered by the monitor's jamming transmit covariance matrix, whereas the latter region is fixed when the MMSE receiver is employed. Therefore, we first analytically characterize the achievable rate region for the two suspicious links via optimizing the jamming transmit covariance matrix and then obtain the achievable eavesdropping rate region for the MMSE receiver case. Furthermore, we also extend our study to the MMSE with successive interference cancellation (MMSE-SIC) receiver case and characterize the corresponding achievable eavesdropping rate region by jointly optimizing the time-sharing factor between different decoding orders. Finally, numerical results are provided to corroborate our analysis and examine the eavesdropping performance.
A compact triple‐band ground radiation antenna for GPS, WiFi 2.4 and 5 GHz band operations in mobile terminals is proposed. Within a considerably small area of 12 × 6 mm, by employing the inductive excitation concept of characteristic radiation modes on a mobile terminal chassis, impedance bandwidths of 21, 210, and 1820 MHz are achieved, covering the GPS, WiFi 2.4 and 5 GHz bands, respectively, at VSWR <2.
For MIMO multiuser systems, random beamforming asymptotically approaches each user's capacity limit through partial feedback. The convergence speed (the closeness of the achievable capacity of one particular user to its capacity limit in terms of the total number of users) and amount of training are two key factors when evaluating the performance of random beamforming, and they are dependent on the receiver design at the mobile stations (MSs). Two kinds of receivers are proposed, a MMSE-based receiver and a QR-based receiver. The new QR-based receiver provides the flexibility to calibrate the ESNRs when the power allocation used in the data transmission mode is different from that in the pilot mode. More importantly, for high the SNR region, when the QR-based receiver is applied, random beamforming approaches coherent beamforming, even when the number of users is small. Evaluation by computer simulation shows that the new receiver has faster convergence than existing receivers for both low and high SNR.
This paper studies the wireless spectrum sharing between a pair of distributed primary radio (PR) and cognitive radio (CR) links. Assuming that the PR link adapts its transmit power and/or rate upon receiving an interference signal from the CR and such transmit adaptations are observable by the CR, this results in a new form of feedback from the PR to CR, refereed to as hidden PR feedback, whereby the CR learns the PR's strategy for transmit adaptations without the need of a dedicated feedback channel from the PR. In this paper, we exploit the hidden PR feedback to design new learning and transmission schemes for spectrum sharing based CRs, namely active learning and supervised transmission. For active learning, the CR initiatively sends a probing signal to interfere with the PR, and from the observed PR transmit adaptations the CR estimates the channel gain from its transmitter to the PR receiver, which is essential for the CR to control its interference to the PR during the subsequent data transmission. This paper proposes a new transmission protocol for the CR to implement the active learning and the solutions to deal with various practical issues for implementation, such as time synchronization, rate estimation granularity, power measurement noise, and channel variation. Furthermore, with the acquired knowledge from active learning, the CR designs a supervised data transmission by effectively controlling the interference powers both to and from the PR, so as to achieve the optimum performance tradeoffs for the PR and CR links. Numerical results are provided to evaluate the effectiveness of the proposed schemes for CRs under different system setups.
No abstract is provided for this article.
Wireless information surveillance, by which suspicious wireless communications are closely monitored by legitimate agencies, is an integral part of national security. To enhance the information surveillance capability, we propose in this paper a new proactive eavesdropping approach via a spoofing relay, where the legitimate monitor operates in a full-duplex manner with simultaneous eavesdropping and spoofing relaying to vary the source transmission rate in favor of the eavesdropping performance. To this end, a power splitting receiver is proposed, where the signal received at each antenna of the legitimate monitor is split into two parts for information eavesdropping and spoofing relaying, respectively. We formulate an optimization problem to maximize the achievable eavesdropping rate by jointly optimizing the power splitting ratios and relay precoding matrix at the multiantenna monitor. Depending on the suspicious and eavesdropping channel conditions, the optimal solution corresponds to three possible spoofing relay strategies, namely constructive relaying, jamming, and simultaneous jamming and destructive relaying. Numerical results show that the proposed technique significantly improves the eavesdropping rate of the legitimate monitor as compared to the existing passive eavesdropping and jamming-assisted eavesdropping schemes.
Wireless networks can be self-sustaining by harvesting energy from radio-frequency (RF) signals. Building on classic cognitive radio networks, we propose a novel method for network coexisting where mobiles from a secondary network, called secondary transmitters (STs), either harvest energy from transmissions by nearby transmitters from a primary network, called primary transmitters (PTs), or transmit information if PTs are sufficiently far away; STs store harvested energy in rechargeable batteries with finite capacity and use all available energy for subsequent transmission when batteries are fully charged. In this model, each PT is centered at a guard zone and a harvesting zone that are disks with given radiuses; a ST harvests energy if it lies in some harvesting zone, transmits fixed-power signals if it is outside all guard zones or else idles. Based on this model, the spatial throughput of the secondary network is maximized using a stochastic-geometry model where PTs and STs are modeled as independent homogeneous Poisson point processes (HPPPs), under the outage constraints for coexisting networks and obtained in a simple closed-form. It is observed from the result that the maximum secondary throughput decreases linearly with the growing PT density, and the optimal ST density is inversely proportional to the derived transmission probability for STs.
Microgrid is a key enabling solution to future smart grids by integrating distributed renewable generators and storage systems to efficiently serve the local demand. However, due to the random and intermittent characteristics of renewable energy, new challenges arise for the reliable operation of microgrids. To address this issue, we study in this paper the real-time energy management for a single microgrid system that constitutes a renewable generation system, an energy storage system, and an aggregated load. We model the renewable energy offset by the load over time, termed net energy profile, to be practically predictable, but with finite errors that can be arbitrarily distributed. We aim to minimize the total energy cost (modeled as sum of time-varying strictly convex functions) of the conventional energy drawn from the main grid over a finite horizon by jointly optimizing the energy charged/discharged to/from the storage system over time subject to practical load and storage constraints. To solve this problem in real time, we propose a new off-line optimization approach to devise the online algorithm. In this approach, we first assume that the net energy profile is perfectly predicted or known ahead of time, under which we derive the optimal off-line energy scheduling solution in closed-form. Next, inspired by the optimal off-line solution, we propose a sliding-window based online algorithm for real-time energy management under the practical setup of noisy predicted net energy profile with arbitrary errors. Finally, we conduct simulations based on the real wind generation data of the Ireland power system to evaluate the performance of our proposed algorithm, as compared with other heuristically designed algorithms, as well as the conventional dynamic programming based solution.
In this paper, we propose a new wireless sensing system equipped with the movable-antenna (MA) array, which can flexibly adjust the positions of antenna elements for improving the sensing performance over conventional antenna arrays with fixed-position antennas (FPAs). First, we show that the angle estimation performance in wireless sensing is fundamentally determined by the array geometry, where the Cramer-Rao bound (CRB) of the mean square error (MSE) for angle of arrival (AoA) estimation is derived as a function of the antennas' positions for both one-dimensional (1D) and two-dimensional (2D) MA arrays. Then, for the case of 1D MA array, we obtain a globally optimal solution for the MAs' positions in closed form to minimize the CRB of AoA estimation MSE. While in the case of 2D MA array, we aim to achieve the minimum of maximum (min-max) CRBs of estimation MSE for the two AoAs with respect to the horizontal and vertical axes, respectively. In particular, for the special case of circular antenna movement region, an optimal solution for the MAs' positions is derived under certain numbers of MAs and circle radii. Thereby, both the lower- and upper-bounds of the min-max CRB are obtained for the antenna movement region with arbitrary shapes. Moreover, we develop an efficient alternating optimization algorithm to obtain a locally optimal solution for MAs' positions by iteratively optimizing one between their horizontal and vertical coordinates with the other being fixed. Numerical results demonstrate that our proposed 1D/2D MA arrays can significantly decrease the CRB of AoA estimation MSE as well as the actual MSE compared to conventional uniform linear arrays (ULAs)/uniform planar arrays (UPAs) with different values of uniform inter-antenna spacing.
