Publications

Intelligent reflecting surface (IRS) is a revolutionary and transformative technology for achieving spectrum and energy efficient wireless communication cost-effectively in the future. Specifically, an IRS consists of a large number of low-cost passive elements each being able to reflect the incident signal independently with an adjustable phase shift so as to collaboratively achieve three-dimensional (3D) passive beamforming without the need of any transmit radio-frequency (RF) chains. In this paper, we study an IRS-aided single-cell wireless system where one IRS is deployed to assist in the communications between a multi-antenna access point (AP) and multiple single-antenna users. We formulate and solve new problems to minimize the total transmit power at the AP by jointly optimizing the transmit beamforming by active antenna array at the AP and reflect beamforming by passive phase shifters at the IRS, subject to users' individual signal-to-interference-plus-noise ratio (SINR) constraints. Moreover, we analyze the asymptotic performance of IRS's passive beamforming with infinitely large number of reflecting elements and compare it to that of the traditional active beamforming/relaying. Simulation results demonstrate that an IRS-aided MIMO system can achieve the same rate performance as a benchmark massive MIMO system without using IRS, but with significantly reduced active antennas/RF chains. We also draw useful insights into optimally deploying IRS in future wireless systems.

Wireless communication systems that include unmanned aerial vehicles (UAVs) promise to provide cost-effective wireless connectivity for devices without infrastructure coverage. Compared to terrestrial communications or those based on high-altitude platforms (HAPs), on-demand wireless systems with low-altitude UAVs are in general faster to deploy, more flexibly re-configured, and are likely to have better communication channels due to the presence of short-range line-of-sight (LoS) links. However, the utilization of highly mobile and energy-constrained UAVs for wireless communications also introduces many new challenges. In this article, we provide an overview of UAV-aided wireless communications, by introducing the basic networking architecture and main channel characteristics, highlighting the key design considerations as well as the new opportunities to be exploited.

We consider a spectrum sharing based cognitive radio wireless communications system which consists of a secondary transmitter (ST) and a secondary receiver (SR), both equipped with multiple antennas, and a single-antenna primary user (PU). ST is composed of an orthogonal space-time block code (OSTBC) followed by a linear precoder which acts as a multimode beamformer. Given a fixed OSTBC, our goal is to design a robust linear precoder, where the robustness assumes addressing the problem of imperfect channel state information (CSI) of ST to SR (ST-SR) MIMO link at ST. Channel correlation information of ST to PU (ST-PU) link is also available at ST. The imperfect channel knowledge of the ST-SR link is described by a specified uncertainty region, known to ST. The robust precoding design criterion is the maximization of the signal-to-noise ratio (SNR) for the worst-case Frobeneus norm-bounded CSI mismatch subject to the transmit-power constraint of ST and interference-power constraint of PU. The original robust precoder design problem is non-convex and does not have any close-form solution. Using a semidefinite relaxation (SDR) approach, we transform it to a convex form and find the approximate solution using standard numerical methods. Simulation results are presented to show the performance of the robust precoding scheme.

This paper presents a ring-based SDH optical core network design problem with odd-elegant. This essay presents a method of constructing ring-based SDH optical networks using <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n$</tex> isomorphic bipartite odd-elegant trees network topology T <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</inf> (i ∊ [1, n]). It confirms odd-elegant labellings of this generalized ring network topology and proves its odd-elegant feature. This method is demonstrated to be efficient and effective by theoretical proof and example results, and shows promise for tackling ring-based network design problems.

To address the limitations of conventional groove designs in groove flow control technique, this paper optimizes the groove flow control technique for an axial-flow pump combining the design of experiment (DOE), response surface methodology (RSM), and particle swarm optimization (PSO). The sample space is designed using a combination method (OD-LHS) of orthogonal design (OD) and Latin hypercube sampling (LHS). Performance prediction models for the axial-flow pump are established using RSM. Taking the multi-condition comprehensive evaluation function as the final optimization objective, PSO is used to find the optimum groove parameters. The results show that the proposed method is effective in solving multi-condition optimization problems for grooves in axial-flow pumps. The optimal groove length, depth, and distance from the center of the impeller are 0.8, 0.05, and 0.2 times the impeller diameter, respectively, and the number is three times the number of blades. In addition, the optimal grooves effectively improve the hydraulic performance of the axial-flow pump under stall conditions. This study sheds light on the design optimization of the groove flow control technique for axial-flow pumps and other types of hydraulic machinery.

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 SWIPT systems. We consider an IRS being deployed to assist a multi-antenna access point (AP) to serve multiple information decoding receivers (IDRs) and energy harvesting receivers (EHRs). We aim to maximize the weighted sum-power received by EHRs via jointly optimizing the transmit precoders at the AP and reflect phase shifts at the IRS, subject to the individual signal-to-interference-plus-noise ratio (SINR) constraints for IDRs. Since this problem is non-convex, we propose efficient algorithms to obtain suboptimal solutions for it. In particular, we prove that it is sufficient to send information signals only at the AP to serve both IDRs and EHRs regardless of their channel realizations. Moreover, simulation results show significant performance gains achieved by our proposed designs over benchmark schemes.

Network coding improves TCP's performance in lossy wireless networks. However, the complex congestion window evolution of network coded TCP (TCP-NC) makes the analysis of end-to-end throughput challenging. This paper analyzes the evolutionary process of TCP-NC against lossy links. An analytic model is established by applying a two-dimensional Markov chain. With maximum window size, end-to-end erasure rate and redundancy parameter as input parameters, the analytic model can reflect window evolution and calculate end-to-end throughput of TCP-NC precisely. The key point of our model is the novel definition for the states of Markov chain. It substantially reduces related states and much lower complexity is obtained. Our work helps understand the factors that affect TCP-NC's performance and lay the foundation of optimization. Extensive simulations on NS2 show that the analytic model features fairly high accuracy.

No abstract is provided for this article.

In this letter, the achievable rate maximization problem is considered for intelligent reflecting surface (IRS) assisted multiple-input multiple-output (MIMO) systems in an underlay spectrum sharing scenario, subject to interference power constraints at the primary users. The formulated non-convex optimization problem is challenging to solve due to its non-convexity as well as coupling design variables in the constraints. Different from existing works that are mostly based on alternating optimization (AO), we propose a penalty dual decomposition based gradient projection (PDDGP) algorithm to solve this problem. We also provide a convergence proof and a complexity analysis for the proposed algorithm. We benchmark the proposed algorithm against two known solutions, namely a minimum mean-square error based AO algorithm and an inner approximation method with block coordinate descent. Specifically, the complexity of the proposed algorithm grows linearly with respect to the number of reflecting elements at the IRS, while that of the two benchmark methods grows with the third power of the number of IRS elements. Moreover, numerical results show that the proposed PDDGP algorithm yields considerably higher achievable rate than the benchmark solutions.

This paper is concerned with spectrum sharing cognitive radio networks, where a secondary user (SU) or cognitive radio link communicates simultaneously over the same frequency band with an existing primary user (PU) link. It is assumed that the SU transmitter has the perfect channel state information (CSI) on the fading channels from SU transmitter to both PU and SU receivers (as usually assumed in the literature), as well as the fading channel from PU transmitter to PU receiver (a new assumption). With the additional PU CSI, we study the optimal power control for the SU over different fading states to maximize the SU ergodic capacity subject to a new proposed constraint to protect the PU transmission, which limits the maximum ergodic capacity loss of the PU resulted from the SU transmission. It is shown that the proposed SU power-control policy is superior over the conventional policy under the constraint on the maximum tolerable interference power/interperferecne temperature at the PU receiver, in terms of the achievable ergodic capacities of both PU and SU.

By applying tunable phase shifts to incident waves via passive signal reflection, intelligent reflecting surface (IRS) can offer significant performance improvement for wireless communication systems. To reap such performance gain, channel knowledge for IRS-cascaded links is generally required, which is practically challenging to acquire due to their high-dimensional and time-varying characteristics. Conventional pilot-based channel estimation incurs excessive overhead due to the large number of reflecting elements, thus undermining the IRS efficiency, especially for wideband systems with frequency-selective fading channels. To tackle this issue, we propose in this letter a power-measurement-based channel autocorrelation matrix estimation and coverage enhancement approach for IRS-aided orthogonal frequency division multiplexing (OFDM) systems. Specifically, by estimating equivalent channel autocorrelation matrices of IRS-cascaded OFDM channels based on receive signal power and optimizing the IRS reflection vector based on them, the average coverage performance in the IRS-aided region is enhanced without the need for frequent reconfiguration of IRS reflection coefficients based on user instantaneous channels. Simulation results validate the effectiveness of the proposed approach for improving the average channel gain over the coverage region.

In this paper, the design of a wireless communication device relying exclusively on energy harvesting is considered. Due to the inability of rechargeable energy sources to charge and discharge at the same time, a constraint we term the energy half-duplex constraint, two rechargeable energy storage devices (ESDs) are assumed so that at any given time, there is always one ESD being recharged. The energy harvesting rate is assumed to be a random variable that is constant over the time interval of interest. A save-then-transmit (ST) protocol is introduced, in which a fraction of time ρ (dubbed the save-ratio) is devoted exclusively to energy harvesting, with the remaining fraction 1-ρ used for data transmission. The ratio of the energy obtainable from an ESD to the energy harvested is termed the energy storage efficiency, η. We address the practical case of the secondary ESD being a battery with η <; 1, and the main ESD being a super-capacitor with η = 1. Important properties of the optimal save-ratio that minimizes outage probability are derived, from which useful design guidelines are drawn. In addition, we compare the outage performance of random power supply to that of constant power supply over the Rayleigh fading channel. The diversity order with random power is shown to be the same as that of constant power, but the performance gap can be large. Finally, we extend the proposed ST protocol to wireless networks with multiple transmitters. It is shown that the system-level outage performance is critically dependent on the number of transmitters and the optimal save-ratio for single-channel outage minimization.

Cloud radio access network (CRAN), in which remote radio heads (RRHs) are deployed to serve users in a target area, and connected to a central processor (CP) via limited-capacity links termed the fronthaul, is a promising candidate for the next-generation wireless communication systems. Due to the content-centric nature of future wireless communications, it is desirable to cache popular contents beforehand at the RRHs, to reduce the burden on the fronthaul and achieve energy saving through cooperative transmission. This motivates our study in this paper on the energy efficient transmission in an orthogonal frequency division multiple access (OFDMA)-based CRAN with multiple RRHs and users, where the RRHs can prefetch popular contents. We consider a joint optimization of the user-SC assignment, RRH selection and transmit power allocation over all the SCs to minimize the total transmit power of the RRHs, subject to the RRHs' individual fronthaul capacity constraints and the users' minimum rate constraints, while taking into account the caching status at the RRHs. Although the problem is non-convex, we propose a Lagrange duality based solution, which can be efficiently computed with good accuracy. We compare the minimum transmit power required by the proposed algorithm with different caching strategies against the case without caching by simulations, which show the significant energy saving with caching.