The invention provides a real-time location method based on a ZigBee network and belongs to the technical field of wireless sensor network location. A system utilized in the method is composed of a reference node, a mobile node, a gateway node and an embedded Web server. In the method, a certain amount of reference nodes are arranged in a monitoring region firstly, wherein the reference nodes can be used as reference points in the location process and do not participate in the location; the mobile node is a location node and can determine self position according to the reference nodes; the gateway node is used for configuring the position information of the reference nodes and simultaneously receiving the position information of the mobile node and then sending the position information to the Web server; and the Web server can realize remote access and control after accessing the network. The invention also provides a real-time location method which can be used for realizing real-time accurate location according to an RSSI (received signal strength indicator) value transmitted among the ZigBee nodes. Compared with other location algorithms and implementations, the method provided by the invention has the advantages of high accuracy and low power consumption, and is safe and reliable in operation.

Real-time location method based on ZigBee network

Embodiments include methods and apparatuses for providing access to a network slice in a communication system In an embodiment, a network server that implements a Control Plane (CP) Network Function (NF) may receive a Non-Access Stratum (NAS) message from a wireless transmit and receive unit (WTRU) The NAS message comprises a Mobility Management (MM) message for registration and a Session Management (SM) messages for a specific service provided by the network slice After selecting the network slice, the network server may transmit the SM message to another CP NF in the network slice to establish a communication link between the WTRU and the network slice

Methods for service slice selection and separation

Various methods, apparatuses and/or articles of manufacture are provided which may be implemented to support mobile device positioning through the use of adaptive passive scanning and/or adaptive active probing techniques. For example, a mobile device may acquire signals from wireless transceivers, identify wireless transceivers based, at least in part, on the acquired signal(s), determine a received signal strength measurement for each of the wireless transceivers based, at least in part, on the acquired signal(s), and determine a transmission power of a probe signal to be transmitted to at least one of the wireless transceivers based, at least in part, on at least one of the received signal strength measurements.

Adaptive passive scanning and/or active probing techniques for mobile device positioning

In order to deal with the problem when the bandwidth of the passive radars and wideband digital receivers are getting bigger and bigger, causing that the traditional signal detection methods need a high sampling rate and a large number of sampling points. This paper extends the modulated wideband converter (MWC) which is recently proposed compressed sensing techniques to discrete-time domain in order to construct a wideband digital receiver. The MWC compressed sampling structure is applied to get the sub-Nyquist compressed sampling signal to detect whether the interesting signal exists or not. Then we can get eigenvalue decomposition of the covariance matrix of the compressed sampling data. According to linear distribution characteristics of Gaussian white noise covariance matrix eigenvalues, we can use the correlation coefficients of these eigenvalues to construct signal detection criterion. The simulation results show that the proposed signal detection method in this paper obtains a higher signal detection success rate in low signal to noise ratio (SNR) with fewer sampling data compared with conventional signal detection method.

Compressed sampling signal detection method based on modulated wideband converter

The invention is applicable to the technical field of positioning, and provides an indoor positioning device. The indoor positioning device comprises a base, a light source, a rotating member, a rotating shell and a controller, wherein the rotating shell is divided into a plurality of coding rings, each coding ring is divided into a plurality of coding bits, an angle of each coding bit is 360/N degrees in the latitudinal direction, and the coding bits of different coding rings are different in configuration mode; a plurality of coding bits of the coding rings are of a light transmitting state, more than two continuous light-proof coding bits do not exist, and a plurality of coding bits, which are configured in a specific mode, form a start bit and a stop bit; each coding ring comprises a special coding bit; and the base is further provided with an optical coupler, the side, which faces to the base, of the rotating member is provided with a light blocking piece, and frequency hopping occurs every time when the rotating member drives the light blocking piece to penetrate through a clamping slot. The indoor positioning device realizes positioning by being combined with light signal sensing of a receiving terminal through the special rotating shell and the hopping light source, the structure is simple, and the positioning method is novel, accurate, good in stability and low in cost, thereby being suitable for indoor high-precision positioning.

Indoor positioning device and indoor positioning method

Improved weighting trilateral positioning method based on RSSI (received signal strength indicator) in wireless sensor network

The invention provides a method for Bayes compressed sensing signal recovery based on a self-adaptive measurement matrix and relates to the field of the information and communication technology The method aims at solving the problem that an existing compressed sensing signal recovery method is low in accuracy Based on the design of the self-adaptive measurement matrix in compressed sensing and combined with the Bayes compressed sensing algorithm, a design scheme of the compressed sensing method is obtained The method is characterized in that the designed measurement matrix can be generated in a self-adaptive mode according to different signals, the purposes of determinacy and storage of the matrix are both achieved, and combined with the Bayes compressed sensing recovery algorithm of a relevant vector machine, the priority of a layered structure is introduced The design scheme passes simulation verification, it is confirmed that the good signal recovery effect can be obtained, and the error range of recovered signals can be evaluated The method is suitable for wireless signal transmission occasions in the information and communication technology

Method for Bayes compressed sensing signal recovery based on self-adaptive measurement matrix

The invention provides a signal efficient sampling and reconstruction method based on FRI time-frequency domain comprehensive analysis and relates to the technical field of information and communication. The signal efficient sampling and reconstruction method based on FRI time-frequency domain comprehensive analysis aims to lower Nyquist sampling frequency of signals and improve the sampling accuracy of the signals. In a frequency domain, a frequency spectrum line is used for recording information of high-frequency components of the signals, and the frequency is subjected to logarithm taking and normalized, so that the frequency domain is further compressed. In a time domain, a line segment fitting method is proposed, and time-frequency signals with low frequency are compressed. Since the signals are sampled efficiently in the frequency domain and the time domain, the requirement for the signal sampling quantity is substantially lowered; the signals are processed and recovered in the time domain and the frequency domain according to the FRI theory; meanwhile, the types of the signals capable of being processed according to he FRI theory are expanded, so discrete Dirac flow and continuous signals with high frequency can be both processed according to the FRI theory. The signal efficient sampling and reconstruction method based on FRI time-frequency domain comprehensive analysis is applicable to the signal sampling and reconstruction process.

Signal efficient sampling and reconstruction method based on FRI time-frequency domain comprehensive analysis

The invention relates to the technical field of information and communication, specifically to an optimal forbidden zone width method combining spectrum effectiveness and interference suppression in a cognition satellite and ground integrated system, and aims to solve the problem of same frequency interference of ground components and satellite components. A system model built by the method comprises a multi-beam satellite, a plurality of complementary ground components (CGCs) and an earth station, and mainly directs at analysis of a scene where an earth station within a spot beam causes interference to an uplink of a ground user within an adjacent spot beam. To reduce interference to which a CGC of a spot beam edge is subjected, the method adopts a forbidden zone principle, utilizes an improved frequency division multiplexing scheme to perform theoretical analysis and simulation verification on same frequency interference and spectral effectiveness in a cognition satellite and ground integrated system, and at the same time, the method considers spectrum effectiveness and interference suppression in a combined manner, and proposes an optical EA strategy capable of enabling a system to realize maximum spectrum effectiveness under an acceptable interference level.

Optimal forbidden zone width method combining spectrum effectiveness and interference suppression in cognition satellite and ground integrated system

The invention discloses a multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method, which relates to the technical field of information and communication. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method is provided for solving the problem of recovering an original multiband signal from multiple observed value vectors with unknown sparsity after continuous-limited module conversion through sampling by a modulated broadband converter under an Xampling framework. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method comprises the steps of: conducting self-adaptive estimation on sparsity of a signal; updating the sparsity with a given step length factor through repeated iteration so that the sparsity gradually approaches the actual sparsity of the signal; correcting a support set through a backtracking thought and a minimum mean square criterion; stopping iteration until an residual error is less than a set threshold value; and finally reconstructing an original multiband signal through pseudo inverse operation by utilizing the obtained complete support set. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method can achieve the analog reconstruction of the multiband signal based on compressed sensing.

Multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method

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