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Jianming Zhou

Publications and source records attributed to Jianming Zhou.

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Analytic Formulas for Quantum Discord of Special Families of N-Qubit States

Quantum discord, a key indicator of non-classical correlations in bipartite systems, has been recently extended to multipartite scenarios [Phys. Rev. Lett. 2020, 124:110401]. We present exact analytic formulas for the quantum discord of special families of N-qubit states, including generalized class of GHZ states. Our formulations span $2$, $3$, $4n$, $4n+1$, $4n+2$, and $4n+3$-qubit configurations where $n\in 1, 2, \ldots$, which refine the assessment of quantum correlations and provide an analytical tool in quantum computation. Moreover, we uncover a ``discord freezing'' in even-qubit systems under phase flip decoherence which provides a means for preserving quantum coherence in environmental perturbations.

quant-ph

On super quantum discord for high-dimensional bipartite state

By quantifying the difference between quantum mutual information through weak measurement performed on a subsystem one is led to the notion of super quantum discord. The super version is also known to be difficult to compute as the quantum discord which was captured by the projective (strong) measurements. In this paper, we give effective bounds of the super quantum discord with or without phase damping channels for higher-dimensional bipartite quantum states, and found that the super version is always larger than the usual quantum discord as in the 2-dimensional case.

quant-ph

Quantum discords of tripartite quantum systems

The quantum discord of bipartite systems is one of the best-known measures of non-classical correlations and an important quantum resource. In the recent work appeared in [Phys. Rev. Lett 2020, 124:110401], the quantum discord has been generalized to multipartite systems. In this paper, we give analytic solutions of the quantum discord for tripartite states with fourteen parameters.

quant-ph

A DoA Estimation Based Robust Beam Forming Method for UAV-BS Communication

High data rate communication with Unmanned Aerial Vehicles (UAV) is of growing demand among industrial and commercial applications since the last decade. In this paper, we investigate enhancing beam forming performance based on signal Direction of Arrival (DoA) estimation to support UAV-cellular network communication. We first study UAV fast moving scenario where we found that drone's mobility cause degradation of beam forming algorithm performance. Then, we propose a DoA estimation algorithm and a steering vector adaptive receiving beam forming method. The DoA estimation algorithm is of high precision with low computational complexity. Also it enables a beam former to timely adjust steering vector value in calculating beam forming weight. Simulation results show higher SINR performance and more stability of proposed method than traditional method based on Multiple Signal Classification (MUSIC) DoA estimation algorithm.

eess.SP

Quantum discord of certain two-qubit states

Quantum discord is an effective measure of quantum correlation introduced by Olliver and Zurek. We evaluate analytically the quantum discord for a large family of non-X-states. Exact solutions of the quantum discord are obtained of the four parametric space for non-X-states. Dynamic behavior of the quantum discord is also explored under the action of the Kraus operator.

quant-ph

Energy Efficiency Optimization for UAV-assisted Backscatter Communications

Future Internet-of-Things (IoT) has high demand for energy-saving communications, especially in remote areas and smart cities. To meet this demand, we propose novel Unmanned Aerial Vehicle-assisted backscatter communications, where a UAV first collects data from multiple terrestrial backscattering tags via time division multiple access, and then flies into the coverage region of a terrestrial base station to upload its collected data to its associated base station. To determine the optimal UAV data collection location, we first analyze the system average outage probability, and then optimize the energy efficiency with the optimal backscattering location through Golden Section method under UAV energy constraint. Our analytical and simulation results illustrate that there is a trade-off between UAV data collection location and the outage probability, and the optimal UAV data collection location to achieve maximum energy efficiency needs to be closer to the tags for lower UAV transmit power.

eess.SP

A Convex Hull Based Approach for MIMO Radar Waveform Design with Quantized Phases

In this letter, we focus on designing constant-modulus waveform with discrete phases for the multi-input multi-output (MIMO) radar, where the signal-to-interference-plus-noise ratio (SINR) is maximized in the presence of both the signal-dependent clutter and the noise. Given the NP-hardness of the formulated problem, we propose to relax the original optimization as a sequence of continuous quadratic programming (QP) subproblems by use of the convex hull of the discrete feasible region, which yields approximated solutions with much lower computational costs. Finally, we assess the effectiveness of the proposed waveform design approach by numerical simulations.

eess.SP

MIMO radar waveform design with practical constraints: A low-complexity approach

In this letter, we consider the multiple-input multiple-output (MIMO) radar waveform design in the presence of signal-dependent clutters and additive white Gaussian noise. By imposing the constant modulus constraint (CMC) and waveform similarity constraint (SC), the signal-to-interference-plus-noise (SINR) maximization problem is non-convex and NP-hard in general, which can be transformed into a sequence of convex quadratically constrained quadratic programming (QCQP) subproblems. Aiming at solving each subproblem efficiently, we propose a low-complexity method termed Accelerated Gradient Projection (AGP). In contrast to the conventional IPM based method, our proposed algorithm achieves the same performance in terms of the receive SINR and the beampattern, while notably reduces computational complexity.

eess.SP

Interference Exploitation for Radar and Cellular Coexistence: The Power-Efficient Approach

We propose a novel approach to enable the coexistence between Multi-Input-Multi-Output (MIMO) radar and downlink multi-user Multi-Input-Single-Output (MU-MISO) communication system. By exploiting the constructive multi-user interference (MUI), the proposed approach trades-off useful MUI power for reducing the transmit power, to obtain a power efficient transmission. This paper focuses on two optimization problems: a) Transmit power minimization at the base station (BS) while guaranteeing the receive signal-to-interference-plus-noise ratio (SINR) level of downlink users and the interference-to-noise ratio (INR) level to radar; b) Minimization of the interference from BS to radar for a given requirement of downlink SINR and transmit power budget. To reduce the computational overhead of the proposed scheme in practice, an algorithm based on gradient projection is designed to solve the power minimization problem. In addition, we investigate the trade-off between the performance of radar and communication, and analytically derive the key metrics for MIMO radar in the presence of the interference from the BS. Finally, a robust power minimization problem is formulated to ensure the effectiveness of the proposed method in the case of imperfect Channel State Information (CSI). Numerical results show that the proposed method achieves a significant power saving compared to conventional approaches, while obtaining a favorable performance-complexity trade-off.

cs.IT