A Comparison between the Metric Dimension and Zero Forcing Number of Trees and Unicyclic Graphs

The metric dimension dim（G） of a graph G is the minimum number of vertices such that every vertex of G is uniquely determined by its vector of distances to the chosen vertices. The zero forcing number Z（G） of a graph G is the minimum eardinality of a set S of black vertices （whereas vertices in V（G）／S are colored white） such that V（G） is turned black after finitely many applications of ＂the color-change rule＂： a white vertex is converted black if it is the only white neighbor of a black vertex. We show that dim（T） ≤Z（T） for a tree T, and that dim（G）≤Z（G）＋I if G is a unicyclic graph; along the way, we characterize trees T attaining dim（T） = Z（T）. For a general graph G, we introduce the ＂cycle rank conjecture＂. We conclude with a proof of dim（T） - 2 ≤ dim（T ＋ e） ≤dim（T） ＋ 1 for e∈ E（T）.

IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.

Resource allocation with CCI suppression for multiuser MIMO-OFDM downlink in correlated channels

To minimize the overall transmit power while maintaining a constant data rate and target BER, a downlink adaptive resource allocation algorithm with jointing the exclusive manner and the shared manner is proposed for multiuser MIMO-OFDM system in correlated channels. The algorithm allocates all the subcarriers to different users according to their spatial correlations. The users with high spatial correlation are allocated in the same group and the exclusive manner is applied. The shared manner with an improved null broadening method, which improves the performance of co-channel interference （CCI） suppression and decreases the number of transmit antennas required, is applied between the different group users. As the user＇s direction of departure （DOD） changes very slowly, a looking up table method is used to reduce the computational complexity. The simulation results show that despite the angle spread of DOD, when compared with the exclusive manner, the proposed algorithm improves the spectral efficiency, and when compared with the TDMA-ZF （zero forcing） shared manner, the proposed algorithm decreases the total transmit power by at least 1 dB.

Performance Analysis of ZF and RZF in Low-Resolution ADC/DAC Massive MIMO Systems

Large number of antennas and higher bandwidth usage in massive multiple-input-multipleoutput(MIMO)systems create immense burden on receiver in terms of higher power consumption.The power consumption at the receiver radio frequency(RF)circuits can be significantly reduced by the application of analog-to-digital converter(ADC)of low resolution.In this paper we investigate bandwidth efficiency(BE)of massive MIMO with perfect channel state information(CSI)by applying low resolution ADCs with Rician fadings.We start our analysis by deriving the additive quantization noise model,which helps to understand the effects of ADC resolution on BE by keeping the power constraint at the receiver in radar.We also investigate deeply the effects of using higher bit rates and the number of BS antennas on bandwidth efficiency(BE)of the system.We emphasize that good bandwidth efficiency can be achieved by even using low resolution ADC by using regularized zero-forcing(RZF)combining algorithm.We also provide a generic analysis of energy efficiency(EE)with different options of bits by calculating the energy efficiencies(EE)using the achievable rates.We emphasize that satisfactory BE can be achieved by even using low-resolution ADC/DAC in massive MIMO.

Study on Control Technology of Tendon Bionic Driving Robot System

Although traditional position-controlled industrial robots can be competent for most assembly tasks,they cannot complete complex tasks that frequently interact with the external environment.The current research on exoskeleton robots also has problems such as excessive inertia of exoskeleton robots,poor system integration and difficult human–computer interaction control.To solve these problems,this paper independently develops a tendon driving robotic system composed of a tendon driving robotic arm and an upper limb exoskeleton,and studies its control technology.First,the robot system is selected,configured,and constructed.Second,the kinematics of the robot is analyzed,and then the dynamics are studied,and the parameter identification experiment of single degree of freedom is completed.Finally,the research on zero-force control and impedance control of the robot has effectively improved the robot’s human–machine integration ability,ensured the flexibility and compliance in the process of human–computer interaction.The compliant control problem expands the usage scenarios and application scope of robots and contributes to the realization of complex operations of this group of robots in unstructured environments.

Transmit correlation effect on SIC-ZF receiver for V-BLAST system

It has been shown that transmit correlation causes a signal-to-noise ratio （SNR） loss in the zero forcing （ZF） receiver for V-BLAST （Vertical Bell LAbs LAyered Space-Time） system. In this paper, we investigate the transmit correlation effect on the ZF receiver with successive interference cancellation （SIC）. We show that such an unfavorable condition leads to twofold effects on the performance degradation. In addition to the immediate SNR loss, the transmit correlation can increase the propagation factor to spread decision error significantly. These two effects are evaluated analytically. We derive the probability density function （pdf） of the effective SNR at each decoded stream, and hence accurately quantify the SNR loss. We also calculate the decision error propagation factor in terms of its second moment. In particular, we show that transmit correlation can cause a stable component of error propagation which does not decline during the SIC procedure. Finally, we conduct the simulation to verify the analytical results.

Multi-user selection based on particle swarm optimization and power control scheme in the uplink CoMP-MU-MIMO system

Orthogonal frequency division multiplexing （OFDM） which has been adopted in the long-term evolution （LTE） system can improve the system capacity obviously. However, it also brings about severe inter-cell interference （ICI） for cell-edge users （CEUs）. To tackle this problem, multi-user selection and power control （MuS-PC） is proposed as an efficient scheme in uplink coordinated multi-point multi-user multi-input multi-output （CoMP-MU-MIMO） transmission/reception. This paper jointly considers user＇s signal to interference plus noise ratio （S1NR） and proportional fairness （PF） to maximize the total channel capacity in multi-user selection by formulating a penalty function. To simplify the penalty function＇s computation, particle swarm optimization （PSO） algorithm is introduced. In addition, power control is adopted to maximize overall energy efficiency. Simulation results demonstrate that the MuS-PC scheme can not only obtain the optimal total channel capacity while guarantee each user＇s quality of service （QoS） and PF, but also largely reduce computational complexity and improve energy efficiency. As a result, the poor communication quality of CEUs can be enhanced.

Low complexity detection algorithm based on optimized Neumann series for massive MIMO system

An optimized Neumann series（NS） approximation is described based on Frobenius matrix decomposition, this method aims to reduce the high complexity, which caused by the large matrix inversion of detection algorithm in the massive multiple input multiple output（MIMO） system. The large matrix in the inversion is decomposed into the sum of the hollow matrix and a Frobenius matrix, and the Frobenius matrix has the diagonal elements and the first column of the large matrix. In order to ensure the detection performance approach to minimum mean square error（MMSE） algorithm, the first three terms of the series approximation are needed, which results in high complexity as O（K;）, where K is the number of users. This paper further optimize the third term of the series approximation to reduce the computational complexity from O（K;） to O（K;）. The computational complexity analysis and simulation results show that the performance of proposed algorithm can approach to MMSE algorithm with low complexity O（K;）.