Secrecy Wireless Information and Power Transfer in Fading Wiretap Channel

Simultaneous wireless information and power transfer (SWIPT) has recently drawn significant interests for its dual use of radio signals to provide wireless data and energy access at the same time. However, a challenging secrecy communication issue arises as the messages sent to the information receivers (IRs) may be eavesdropped by the energy receivers (ERs), which are presumed to harvest energy only from the received signals. To tackle this problem, we propose in this paper an artificial noise (AN) aided transmission scheme to facilitate the secrecy information transmission to IRs and yet meet the energy harvesting requirement for ERs, under the assumption that the AN can be cancelled at IRs but not at ERs. Specifically, the proposed scheme splits the transmit power into two parts, to send the confidential message to the IR and an AN to interfere with the ER, respectively. Under a simplified three-node wiretap channel setup, the transmit power allocations and power splitting ratios over fading channels are jointly optimized to minimize the outage probability for delay-limited secrecy information transmission, or to maximize the average rate for no-delay-limited secrecy information transmission, subject to a combination of average and peak power constraints at the transmitter as well as an average energy harvesting constraint at the ER. Both the secrecy outage probability minimization and average rate maximization problems are shown to be non-convex, for each of which we propose the optimal solution based on the dual decomposition as well as suboptimal solution based on the alternating optimization. Furthermore, two benchmark schemes are introduced for comparison. Finally, the performances of proposed schemes are evaluated by simulations in terms of various trade-offs for wireless (secrecy) information versus energy transmissions.Comment: to appear in IEEE Transactions on Vehicular Technolog

Optimal Throughput Fairness Trade-offs for Downlink Non-Orthogonal Multiple Access over Fading Channels

Recently, non-orthogonal multiple access (NOMA) has attracted considerable interest as one of the 5G-enabling techniques. However, users with better channel conditions in downlink communications intrinsically benefits from NOMA thanks to successive decoding, judicious designs are required to guarantee user fairness. In this paper, a two-user downlink NOMA system over fading channels is considered. For delay-tolerant transmission, the average sum-rate is maximized subject to both average and peak power constraints as well as a minimum average user rate constraint. The optimal resource allocation is obtained using Lagrangian dual decomposition under full channel state information at the transmitter (CSIT), while an effective power allocation policy under partial CSIT is also developed based on analytical results. In parallel, for delay-limited transmission, the sum of delay-limited throughput (DLT) is maximized subject to a maximum allowable user outage constraint under full CSIT, and the analysis for the sum of DLT is also performed under partial CSIT. Furthermore, an optimal orthogonal multiple access (OMA) scheme is also studied as a benchmark to prove the superiority of NOMA over OMA under full CSIT. Finally, the theoretical analysis is verified by simulations via different trade-offs for the average sum-rate (sum-DLT) versus the minimum (maximum) average user rate (outage) requirement.Comment: 35 pages, 10 figures, 3 tables, the longer version of the paper with the same titl

An online monitoring, diagnosis and control system based on virtual instrument for CNC spindle

In the field of precision machining, the spindle is the “heart component” of the machining center. The dynamic performance of the spindle will directly affect the performance of the machine and the machining accuracy of the products. In order to avoid the above problems, an online monitoring, diagnosis and control system based on virtual instrument is designed for spindle. The system can monitor the operation condition of CNC electric spindle in real-time. Some classic signal processing and analysis methods are adopted such as time domain waveform, envelope spectrum and spectral kurtosis etc. The system is developed by LabVIEW language and on 107Z data acquisition system. The experiment platform for the system is a horizontal machining center of Dongyu CMV-1100A. The program is effective after preliminary test verification

Joint Task Assignment and Wireless Resource Allocation for Cooperative Mobile-Edge Computing

This paper studies a multi-user cooperative mobile-edge computing (MEC) system, in which a local mobile user can offload intensive computation tasks to multiple nearby edge devices serving as helpers for remote execution. We focus on the scenario where the local user has a number of independent tasks that can be executed in parallel but cannot be further partitioned. We consider a time division multiple access (TDMA) communication protocol, in which the local user can offload computation tasks to the helpers and download results from them over pre-scheduled time slots. Under this setup, we minimize the local user's computation latency by optimizing the task assignment jointly with the time and power allocations, subject to individual energy constraints at the local user and the helpers. However, the joint task assignment and wireless resource allocation problem is a mixed-integer non-linear program (MINLP) that is hard to solve optimally. To tackle this challenge, we first relax it into a convex problem, and then propose an efficient suboptimal solution based on the optimal solution to the relaxed convex problem. Finally, numerical results show that our proposed joint design significantly reduces the local user's computation latency, as compared against other benchmark schemes that design the task assignment separately from the offloading/downloading resource allocations and local execution.Comment: 6 pages, 4 figures, accepted by IEEE International Conference on Communications (ICC), Kansas City, MO, USA, 201