Publications

RSRP Measurement Based Channel Autocorrelation Estimation for IRS-Aided Wideband Communication

The passive and frequency-flat reflection of IRS, as well as the high-dimensional IRS-reflected channels, have posed significant challenges for efficient IRS channel estimation, especially in wideband communication systems with significant multi-path channel delay spread. To address these challenges, we propose a novel neural network (NN)-empowered framework for IRS channel autocorrelation matrix estimation in wideband orthogonal frequency division multiplexing (OFDM) systems. This framework relies only on the easily accessible reference signal received power (RSRP) measurements at users in existing wideband communication systems, without requiring additional pilot transmission. Based on the estimates of channel autocorrelation matrix, the passive reflection of IRS is optimized to maximize the average user received signal-to-noise ratio (SNR) over all subcarriers in the OFDM system. Numerical results verify that the proposed algorithm significantly outperforms existing powermeasurement-based IRS reflection designs in wideband channels.

Transforming Fading Channel From Fast to Slow: Intelligent Refracting Surface Aided High-Mobility Communication

Intelligent reflecting/refracting surface (IRS) has recently emerged as a promising solution to reconfigure wireless propagation environment for enhancing the communication performance by tuning passive signal reflection or refraction. In this paper, we study a new IRS-aided high-mobility communication system by employing the intelligent <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">refracting</i> surface with a high-speed vehicle to aid its passenger's communication with a remote base station (BS). Due to the environment's random scattering and vehicle's high mobility, a rapidly time-varying channel is typically resulted between the static BS and fast-moving IRS/user, which renders the channel estimation for IRS with a large number of passive refracting elements more challenging, as compared to that for the conventional slow fading IRS channels with low-mobility users. In order to reap the high IRS passive beamforming gain with low channel training overhead, we propose a new and efficient two-stage transmission protocol to achieve both IRS channel estimation and refraction optimization for data transmission. Specifically, by exploiting the quasi-static channel between the IRS and user both moving at the same high speed as well as the line-of-sight (LoS) dominant channel between the BS and IRS, the user first estimates the LoS component of the cascaded BS-IRS-user channel in Stage I, based on which IRS passive refraction is designed to maximize the corresponding IRS-refracted channel gain. Then, the user estimates the resultant IRS-refracted channel as well as the non-IRS-refracted channel in Stage II for setting an additional common phase shift at all IRS refracting elements so as to align these two channels for maximizing the overall channel gain for data transmission. Simulation results show that the proposed design can efficiently achieve the full IRS passive beamforming gain in the high-mobility communication scenario, which also converts the overall BS-user channel from fast to slow fading for more reliable transmission. The proposed on-vehicle IRS system is further compared with a baseline scheme of deploying fixed IRSs (intelligent reflecting surfaces) on the roadside to assist high-speed vehicular communications, which achieves significant rate improvement due to its greatly saved channel training time.

Publisher Correction: NINJ1 regulates plasma membrane fragility under mechanical strain

Distributed Wireless Power Transfer With Energy Feedback

Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless channels, they can be constructively combined at the energy receiver (ER) to achieve an EB gain that scales with the number of ETs. However, the optimal design of EB waveforms requires accurate channel state information (CSI) at the ETs, which is challenging to obtain practically, especially in a distributed system with ETs at separate locations. In this paper, we study practical and efficient channel training methods to achieve optimal EB in a distributed WET system. We propose two protocols with and without centralized coordination, respectively, where distributed ETs either sequentially or in parallel adapt their transmit phases based on a low-complexity energy feedback from the ER. The energy feedback only depends on the received power level at the ER, where each feedback indicates one particular transmit phase that results in the maximum harvested power over a set of previously used phases. Simulation results show that the two proposed training protocols converge very fast in practical WET systems even with a large number of distributed ETs, while the protocol with sequential ET phase adaptation is also analytically shown to converge to the optimal EB design with perfect CSI by increasing the training time. Numerical results are also provided to evaluate the performance of the proposed distributed EB and training designs as compared to other benchmark schemes.

Two-timescale Beamforming Optimization for Intelligent Reflecting Surface Enhanced Wireless Network

Intelligent reflecting surface (IRS) has drawn a lot of attention recently as a promising new solution to achieve high spectral and energy efficiency for future wireless networks. Prior works on IRS mainly rely on the instantaneous channel state information (I-CSI), which, however, is practically difficult to obtain for IRS-associated links due to its passive operation and large number of elements. To overcome this difficulty, we propose in this paper a new two-timescale (TTS) transmission protocol to maximize the achievable average sum-rate for an IRS-aided multiuser system. Specifically, the passive IRS phase-shifts are first optimized based on the statistical CSI (S-CSI) of all links, which varies much slowly as compared to their I-CSI, while the transmit beamforming/precoding vectors at the access point (AP) are then designed to cater to the I-CSI of the users' effective channels with the optimized IRS phase-shifts, thus significantly reducing the channel training overhead and passive beamforming complexity over the existing schemes based on the I-CSI of all channels. Simulation results are presented to validate the effectiveness of our proposed algorithm.

Cellular Sensing via Cooperative Intelligent Reflecting Surfaces

Intelligent reflecting surface (IRS) can effectively improve the performance of wireless communications and target sensing by passive beamforming/searching. In this correspondence, we consider IRS-aided target sensing in cellular networks by deploying an IRS near each base station (BS) and leveraging two IRSs' cooperative passive beam searching. Specifically, we propose a new three-stage sensing protocol by controlling the ON/OFF state of each IRS, thereby efficiently acquiring the essential angle information between the IRSs and the target. Based on the obtained angle information, the location of the target is estimated by applying the least-square method. Simulation results are provided to show the efficacy of the proposed cellular sensing scheme with practical half-duplex BSs as compared to other baseline schemes requiring full-duplex BSs.

Multiuser Communications with Movable-Antenna Base Station Via Antenna Position Optimization

This paper studies the deployment of multiple movable antennas (MAs) at the base station (BS) for enhancing the multiuser communication performance. First, we model the multiuser channel in the uplink to characterize the wireless channel variation caused by MAs' movement at the BS. Then, an optimization problem is formulated to maximize the minimum achievable rate among multiple users for MA-aided uplink multiuser communications by jointly optimizing the MAs' positions, their receive combining at the BS, and the transmit power of users, under the constraints of finite moving region of MAs, minimum inter-MA distance, and maximum transmit power of each user. To solve this challenging non-convex optimization problem, a two-loop iterative algorithm is proposed by leveraging the particle swarm optimization (PSO) method. Specifically, the outer-loop updates the positions of a set of particles, where each particle's position represents one realization of the antenna positioning vector (APV) of all MAs. The inner-loop implements the fitness evaluation for each particle in terms of the max-min achievable rate of multiple users with its corresponding APV, where the receive combining matrix of the BS and the transmit power of each user are optimized by applying the block coordinate descent (BCD) technique. Simulation results show that the antenna position optimization for MAs-aided BS can significantly improve the rate performance as compared to conventional BS with fixed-position antennas (FPAs).

Computer-aided design algorithms and tools for nanotechnologies

The famous Moore's Law states that chip density doubles almost every 18 months. The Semiconductor Industries Association (SIA) roadmap predicts that complementary metal-oxide semiconductor (CMOS) chips will continue to fuel the need for high-performance systems for another 10--15 years. However, new devices and technologies must be introduced to continue the scaling of chips beyond that time-frame. With rapid advancements in electronic materials and devices, many new nanoscale devices have been created, such as resonant tunneling diode (RTD), quantum cellular automata (QCA), single electron transistor (SET), single electron box (SEB), and tunneling phase logic (TPL), which have novel structures and properties. Such devices offer the opportunity to further improve the compactness and speed of very large scale integrated (VLSI) systems. While it is easier to implement Boolean gates using CMOS, it is easier for many nanoscale devices to implement threshold and majority gates. As progress is made in the material and physical understanding of nanoscale devices, research must be done at the logic level to fully harness the potential offered by these devices. The main purpose of the work in this dissertation is to bridge the current wide gap between research on nanoscale devices and research on synthesis methodologies for generating optimized networks utilizing these devices. We present the first comprehensive threshold network synthesis methodology for multi-output multi-level threshold networks starting from Boolean descriptions. It does threshold logic synthesis through binate and unate splitting and by calling a linear program solver. We have implemented the methodology in a tool called TELS, on top of an existing logic synthesis tool, and validated it with a large number of benchmarks. We also present a methodology for efficient majority/minority network synthesis of arbitrary multi-output Boolean functions, which is based on the concept of admissible patterns of majority gates. We have implemented this methodology in a tool called MALS, on top of the same existing logic synthesis tool. We expanded our research from combinational circuits to sequential circuits by addressing the problem of state encoding of finite-state machines targeting threshold/majority logic based implementations. We propose a methodology for state encoding based on an evolutionary algorithm. Besides solving the logic synthesis and state encoding problems for threshold and majority circuits, we also evaluated several factorization methods, targeting threshold/majority logic circuits specifically. Nanotechnology-based circuits are usually more vulnerable to both permanent and transient faults. Therefore, we evaluated threshold/majority totally self-checking (TSC) circuits to impart concurrent error detection capability to such circuits. We establish the efficacy of all the above methods through experimental results on a large number of benchmarks.

Rotatable Antenna-Enhanced Cell-Free Communication

Rotatable antenna (RA) is a promising technology that can exploit new spatial degrees-of-freedom (DoFs) by flexibly adjusting the three-dimensional (3D) boresight direction of antennas. In this letter, we investigate an RA-enhanced cell-free system for downlink transmission, where multiple RA-equipped access points (APs) cooperatively serve multiple single-antenna users over the same time-frequency resource. Specifically, we aim to maximize the sum rate of all users by jointly optimizing the AP-user associations and the RA boresight directions. Accordingly, we propose a two-stage strategy to solve the AP-user association problem, and then employ fractional programming (FP) and successive convex approximation (SCA) techniques to optimize the RA boresight directions. Numerical results demonstrate that the proposed RA-enhanced cell-free system significantly outperforms various benchmark schemes.

Multi-Active/Passive-IRS Enabled Wireless Information and Power Transfer: Active IRS Deployment and Performance Analysis

Intelligent reflecting surfaces (IRSs), active and/or passive, can be densely deployed in complex environments to significantly enhance wireless network coverage for both wireless information transfer (WIT) and wireless power transfer (WPT). In this letter, we study the downlink WIT/WPT from a multi-antenna base station to a single-antenna user over a multi-active/passive IRS (AIRS/PIRS)-enabled wireless link. In particular, we aim to optimize the location of the AIRS with those of the other PIRSs being fixed to maximize the received signal-to-noise ratio (SNR) and signal power at the user in the cases of WIT and WPT, respectively. We derive the optimal solutions for these two cases in closed-form, which reveals that the optimal AIRS deployment is generally different for WIT versus WPT. Furthermore, both analytical and numerical results are provided to show the conditions under which the proposed AIRS deployment strategy yields superior performance to other baseline deployment strategies as well as the conventional all- PIRS enabled WIT/WPT.

Refined Nonlinear Rectenna Modeling and Optimal Waveform Design for Multi-User Multi-Antenna Wireless Power Transfer

In this paper, we study the optimal waveform design for wireless power transfer (WPT) from a multi-antenna energy transmitter (ET) to multiple single-antenna energy receivers (ERs) simultaneously in multi-path frequency-selective channels. First, we propose a refined nonlinear current-voltage model of the diode in the ER rectifier, and accordingly derive new expressions for the output direct current (DC) voltage and corresponding harvested power at the ER. Leveraging this new rectenna model, we first consider the single-ER case and study the multisine-based power waveform design based on the wireless channel to maximize the harvested power at the ER. We propose two efficient algorithms for finding high-quality suboptimal solutions to this non-convex optimization problem. Next, we extend our formulated waveform design problem to the general multi-ER case for maximizing the weighted sum of the harvested powers by all ERs, and propose an efficient difference-of-convex-functions programming (DCP)-based algorithm for solving this problem. Finally, we demonstrate the superior performance of our proposed waveform designs based on the new rectenna model over existing schemes/models via simulations.

Technical Program Committee

No abstract is provided for this article.

Wireless power charging control in multiuser broadband networks

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.

Control method for communication information transmission rate in passive cluster vehicles of vehicular networking

Aiming at the problems of high energy consumption and packet loss rate, long delay and poor fault tolerance of existing information transmission rate control methods, a practical vehicle-based passive vehicle communication information transmission rate control method is proposed. The average relative speed of vehicles and the number of neighbour vehicle nodes are selected as input parameters. The cluster head is selected by using fuzzy logic, and the cluster stability is set to the long duration of the cluster. The effective connection time model of the cluster vehicles' communication link is constructed. Taking the effective connection time model and channel capacity as constraints, the Shannon information concept and the maximum utility function are used to obtain the optimal information transmission rate of the current node. Experimental results show that the proposed method has lower-energy consumption and delay, less packet loss, and better fault-tolerant performance than the current research results.

Integrating Base Station with Intelligent Surface for 6G Wireless Networks: Architectures, Design Issues, and Future Directions

Intelligent surface (IS) is envisioned as a promising technology for the sixth-generation (6G) wireless networks, which can effectively reconfigure the wireless propagation environment via dynamically controllable signal reflection/transmission. In particular, integrating passive intelligent surface (IS) into the base station (BS) is a novel solution to enhance the wireless network throughput and coverage both cost-effectively and energyefficiently. In this article, we provide an overview of IS-integrated BSs for wireless networks, including their motivations, practical architectures, and main design issues. Moreover, numerical results are presented to compare the performance of different IS-integrated BS architectures as well as the conventional BS without IS. Finally, promising directions are pointed out to stimulate future research on IS-BS/terminal integration in wireless networks.

Multi-target channel inversion power control for block-fading channels with multiple antennas

This paper studies the capacities of block-fading (BF) additive white Gaussian noise (AWGN) channels with multiple transmit and receive antennas, under the assumption that perfect channel state information is available at both the transmitter (CSIT) and the receiver (CSIR). We study both ergodic capacity under no transmission delay constraint and delay-limited capacity for delay-constrained case, and consider the tradeoff between capacity and complexity. Optimal power allocation schemes to achieve ergodic and delay-limited capacities are known as variants of standard water-filling algorithms, which usually requires large computational complexity at the transmitter side. In this paper, we propose a new sub-optimal power allocation scheme, so-called multi-target channel inversion (MT-CI), which can be easily implemented at the transmitter and still asymptotically achieve the performance of optimal schemes. Furthermore, MT-CI transforms the original fading channel into parallel AWGN channels and hence greatly reduces the receiver complexity. In addition, the proposed scheme is shown to be also suitable for simultaneous transmission of multimedia services which may require different levels of quality of service (QOS).

Fast Beam Training for IRS-Assisted Multiuser Communications

In this letter, we consider an intelligent reflecting surface (IRS)-assisted multiuser communication system, where an IRS is deployed to provide virtual line-of-sight (LoS) links between an access point (AP) and multiple users. We consider the practical codebook-based IRS passive beamforming and study efficient design for IRS reflect beam training, which is challenging due to the large number of IRS reflecting elements. In contrast to the conventional single-beam training, we propose a new multi-beam training method by dividing the IRS reflecting elements into multiple sub-arrays and designing their simultaneous multi-beam steering over time. By simply comparing the received signal power over time, each user can detect its optimal IRS beam direction with a high probability, even without searching over all possible beam directions as the single-beam training. Simulation results show that our proposed multi-beam training significantly reduces the training time of conventional single-beam training and yet achieves comparable IRS passive beamforming performance for data transmission.

Sensitive determination of adenine on poly(amidosulfonic acid)-modified glassy carbon electrode

Research on the assessment Method for the safety of Flight Procedure based on Time-space Diagram

In view of the lack of more practical automatic allocation tools for flight interval allocation, this paper proposes a concept of aircraft operation diagram, provides the drawing method of aircraft operation diagram, abstracting the operation time and space position of aircraft, and representing the operation state and future trend of each aircraft on the same diagram. A flight interval increment algorithm is proposed in combination with the operation diagram to evaluate whether the current operation trend meets the requirements of operation safety, realize automatic monitoring and automatic optimization of flight interval deployment, and provide a feasible and practical method for future control monitoring.