1,474 publications from this institution
Currently the articles about pricing strategy and business operation of cloud computing are rare, and most of these articles focus on the discussion of the prices given by industry leaders or the improvement in these prices, which cannot reflect market sup...
The exposure possibility of keys poses a great threat to almost all modern cryptography, especially in wireless communications. From the adversary's point of view, a cryptographic key can be considered as a random variable in its key space, whose security level can be measured in terms of randomness. In this article, we propose a highly exposure-resilient framework, which incorporates redundant randomness of key sources into the design of cryptographic systems to resist key exposure in encrypted communications. As hardware costs continue to decrease, the deployment of redundant randomness at the same time to achieve a better security level is affordable in the future. The framework offers a way to protect the privacy of a single key by fusing multiple redundant keys. Analysis and results demonstrate that the proposed scheme can dramatically reduce the secrecy outage probability, and provides an extensible way to enhance the encrypted communication system's resistance to unknown eavesdropping or key exposure.
We consider the use of energy harvesters, in place of conventional batteries with fixed energy storage, for point-to-point wireless communications. In addition to the challenge of transmitting in a channel with time selective fading, energy harvesters provide a perpetual but unreliable energy source. In this paper, we consider the problem of energy allocation over a finite horizon, taking into account channel conditions and energy sources that are time varying, so as to maximize the throughput. Two types of side information (SI) on the channel conditions and harvested energy are assumed to be available: causal SI (of the past and present slots) or full SI (of the past, present and future slots). We obtain structural results for the optimal energy allocation, via the use of dynamic programming and convex optimization techniques. In particular, if unlimited energy can be stored in the battery with harvested energy and the full SI is available, we prove the optimality of a water-filling energy allocation solution where the so-called water levels follow a staircase function.
A compact and easy to fabricate decoupling method is proposed to yield high isolation for the multiple‐input and multiple‐output (MIMO) ground radiation antenna (GradiAnt) system. The proposed MIMO antenna system is comprised of two symmetrical, closely spaced, loop‐type (GradiAnts) with a ground‐coupled loop‐type isolator inserted between them. The isolator can be seen as a series resonant circuit which is connected with lumped components to control decoupling. In the proposed MIMO GradiAnt system, a coupling null is induced due to the ground‐coupled isolator, which effectively can be used for isolation enhancement between two GradiAnts. Within WLAN band, a minimum 14 dB isolation with a peak value of 42 dB at 2.42 GHz is achieved. In this manuscript, the decoupling principle and controlling mechanisms are first explained, then the antenna performances and tuning mechanisms are discussed in detail. The simulation and the measurement of the MIMO antenna, including the scattering parameters, efficiency, radiation patterns, peak gains and envelope correlation coefficients are conducted to verify the performance of the proposed MIMO system.
Intelligent reflecting surface (IRS) is regarded as a promising technique to control wireless channels for improving the communication and/or sensing performance of wireless systems. In this paper, we propose a new target-mounted IRS approach for wireless sensing, where IRS is mounted on the outer/echo surface of a target for either enhancing the IRS/target reflected signal towards the legitimate radar station (LRS) to facilitate its detection of the target, or suppressing that towards the unauthorized radar station (URS) to prevent its detection of the target, by flexibly tuning the IRS reflection. To this end, we assume that sensors are installed along with the reflecting elements at IRS to detect the angles of arrival (AoA) of radar signals from the LRS/URS, based on which IRS reflection is designed to achieve signal enhancement/suppression in the angle of departure (AoD) towards the LRS/URS, respectively. Simulation results are presented to verify the performance of the proposed controllable wireless sensing approach with target-mounted IRS, as compared to various benchmark schemes.
In terrestrial communication networks without fixed infrastructure, unmanned aerial vehicle (UAV)-mounted mobile base stations (MBSs) provide an efficient solution to achieve wireless connectivity. This letter aims to minimize the number of MBSs needed to provide wireless coverage for a group of distributed ground terminals (GTs), ensuring that each GT is within the communication range of at least one MBS. We propose a polynomial-time algorithm with successive MBS placement, where the MBSs are placed sequentially starting on the area perimeter of the uncovered GTs along a spiral path towards the center, until all GTs are covered. Each MBS is placed to cover as many uncovered GTs as possible, with higher priority given to the GTs on the boundary to reduce the occurrence of outlier GTs that each may require one dedicated MBS for its coverage. Numerical results show that the proposed algorithm performs favorably compared to other schemes in terms of the total number of required MBSs and/or time complexity.
Direct asymmetric three-component Mannich reaction involving simple ketones (such as cyclohexanone, acetone, and acetophenone) as donors and catalyzing by silver tartaric acid-derived phosphate was realized to afford a series of optically active β-amino-ketone derivatives in high yields (up to 96%) and good-to-high enantioselectivities (up to 97%) with moderate-to-good diastereoselectivities. This is the first example of direct catalytic asymmetric three-component Mannich reaction via a chiral counteranion-directed strategy.
Random beamforming (RBF) is a practically favourable transmission scheme for multiuser multi-antenna downlink systems since it requires only partial channel state information (CSI) at the transmitter. Under the conventional single-cell setup, RBF is known to achieve the optimal sum-capacity scaling law as the number of users goes to infinity, thanks to the multiuser diversity enabled transmission scheduling that virtually eliminates the intra-cell interference. In this paper, we extend the study of RBF to a more practical multi-cell downlink system with single-antenna receivers subject to the additional inter-cell interference (ICI). First, we consider the case of finite signal-to-noise ratio (SNR) at each receiver. We derive a closed-form expression of the achievable sum-rate with the multi-cell RBF, based upon which we show an asymptotic sum-rate scaling law as the number of users goes to infinity. Next, we consider the high-SNR regime and for tractable analysis assume that the number of users in each cell scales in a certain order with the per-cell SNR. Under this setup, we characterize the achievable degrees of freedom (DoF) for the single-cell case with RBF. Then we extend the analysis to the multi-cell RBF case by characterizing the DoF region. It is shown that the DoF region characterization provides useful guideline on how to design a cooperative multi-cell RBF system to achieve optimal throughput tradeoffs among different cells. Furthermore, our results reveal that the multi-cell RBF scheme achieves the "interference-free DoF" region upper bound for the multi-cell system, provided that the per-cell number of users has a sufficiently large scaling order with the SNR. Our result thus confirms the optimality of multi-cell RBF in this regime even without the complete CSI at the transmitter, as compared to other full-CSI requiring transmission schemes such as interference alignment.
Intelligent reflecting surface (IRS) can be densely deployed in complex environment to create cascaded line-of-sight (LoS) paths between multiple base stations (BSs) and users via tunable IRS reflections, thereby significantly enhancing the coverage performance of wireless networks. To achieve this goal, it is vital to optimize the deployed locations of BSs and IRSs in the wireless network, which is investigated in this paper. Specifically, we divide the coverage area of the network into multiple non-overlapping cells and decide whether to deploy a BS/IRS in each cell given a total number of BSs/IRSs available. We show that to ensure the network coverage/communication performance, i.e., each cell has a direct/cascaded LoS path with at least one BS, as well as such LoS paths have the average number of IRS reflections less than a given threshold, there is a fundamental trade-off with the deployment cost or the number of BSs/IRSs needed. To optimally characterize this trade-off, we formulate a joint BS and IRS deployment problem based on graph theory, which, however, is difficult to be optimally solved due to the combinatorial optimization involved. To circumvent this difficulty, we first consider a simplified problem with given BS deployment and propose the optimal as well as an efficient suboptimal IRS deployment solution to it, by applying the branch-and-bound method and iteratively removing IRSs from the candidate locations, respectively. Next, an efficient sequential update algorithm is proposed for solving the joint BS and IRS deployment problem. Numerical results are provided to show the efficacy of the proposed design approach and optimization algorithms for the joint BS and IRS deployment. The trade-off between the network coverage performance and the number of deployed BSs/IRSs with different cost ratios is also unveiled.
The recent advance in radio-frequency (RF) wireless energy transfer (WET) has motivated the study of wireless powered communication network (WPCN) in which distributed wireless devices are powered via dedicated WET by the hybrid access-point (H-AP) in the downlink (DL) for uplink (UL) wireless information transmission (WIT). In this paper, by utilizing the cognitive radio (CR) technique, we study a new type of CR enabled secondary WPCN, called cognitive WPCN, under spectrum sharing with the primary wireless communication system. In particular, we consider a cognitive WPCN, consisting of one single H-AP with constant power supply and distributed wireless powered users, shares the same spectrum for its DL WET and UL WIT with an existing primary communication link, where the WPCN's WET/WIT and the primary link's WIT may interfere with each other. Under this new setup, we propose two coexisting models for spectrum sharing of the two systems, namely underlay and overlay-based cognitive WPCNs, depending on different types of knowledge on the primary user transmission available for the cognitive WPCN. For each model, we maximize the sum-throughput of the cognitive WPCN by optimizing its transmission under different constraints applied to protect the primary user transmission. Analysis and simulation results are provided to compare the sum-throughput of the cognitive WPCN versus the achievable rate of the primary user under two proposed coexisting models. It is shown that the overlay based cognitive WPCN outperforms the underlay based counterpart, thanks to its fully co-operative WET/WIT design with the primary WIT, while also requiring higher complexity for implementation.
Cognitive beamforming (CB) is a promising technique for efficient spectrum sharing between primary users (PUs) and secondary users (SUs) in a cognitive radio network. With CB, the multi-antenna SU transmitter is able to suppress the interference to the PU receiver and maximize the SU link throughput. Existing designs on CB assume that the SU transmitter either has prior knowledge of the interference channel to the PU receiver or can acquire this knowledge by observing the PU transmission. Both assumptions may be impractical. In this paper, we propose a new and practical design paradigm for CB based on finite-rate cooperative feedback from the PU receiver to the SU transmitter. Specifically, for the case of multiple-input single-output (MISO) SU channel and single- input single-output (SISO) PU channel, the PU receiver collaboratively communicates to the SU transmitter the channel direction information (CDI), namely the quantized shape of the SU- to-PU MISO channel, and the interference power control (IPC) signal, which specifies the maximum transmit power of the SU given the interference margin at the PU receiver. We present a CB algorithm for the SU transmitter based on the finite-rate CDI and IPC feedback. The resulting outage probability of the SU MISO channel is derived and shown to be lower-bounded by a function of the number of feedback bits, which is independent of the signal- to-noise ratio. Moreover, the optimal tradeoff between CDI and IPC feedback is analyzed.
Dispatching unmanned aerial vehicles (UAVs) to harvest sensing-data from distributed sensors is expected to significantly improve the data collection efficiency in conventional wireless sensor networks (WSNs). In this paper, we consider a UAV-enabled WSN, where a flying UAV is employed to collect data from multiple sensor nodes (SNs). Our objective is to maximize the minimum average data collection rate from all SNs subject to a prescribed reliability constraint for each SN by jointly optimizing the UAV communication scheduling and three-dimensional (3D) trajectory. Different from the existing works that assume the simplified line-of-sight (LoS) UAV-ground channels, we consider the more practically accurate angle-dependent Rician fading channels between the UAV and SNs with the Rician factors determined by the corresponding UAV-SN elevation angles. However, the formulated optimization problem is intractable due to the lack of a closed-form expression for a key parameter termed effective fading power that characterizes the achievable rate given the reliability requirement in terms of outage probability. To tackle this difficulty, we first approximate the parameter by a logistic (“S” shape) function with respect to the 3D UAV trajectory by using the data regression method. Then, the original problem is reformulated to an approximate form, which, however, is still challenging to solve due to its non-convexity. As such, we further propose an efficient algorithm to derive its suboptimal solution by using the block coordinate descent technique, which iteratively optimizes the communication scheduling, the UAV’s horizontal trajectory, and its vertical trajectory. The latter two subproblems are shown to be non-convex, while locally optimal solutions are obtained for them by using the successive convex approximation technique. Finally, extensive numerical results are provided to evaluate the performance of the proposed algorithm and draw new insights on the 3D UAV trajectory under the Rician fading as compared to conventional LoS channel models.
