CN1731693A - A multi-mode mobile communication terminal and its signal processing method - Google Patents

Abstract

Disclosed are a multi-mode mobile communication terminal and method for signal processing. The inventive terminal comprises transmitter and receiver, wherein the transmitter comprising terminals that can be re-deployed (1), communication module (2), D/A converter (3), communication mode selector (4), up converter (5), wide band amplifier (6) and intelligent antenna (15); the receiver comprises intelligent antenna (15), RF filter and amplifier (8), down converter (9), A/D converter (10), communication mode recognizer and mode converter (14) and terminals that can be re-deployed (1).

Description

A multi-mode mobile communication terminal and its signal processing method

technical field

The present invention designs a multifunctional terminal based on signal time-frequency analysis method, fuzzy neural network technology and software radio technology. Using the same set of hardware, the terminal can be used as a terminal of Bluetooth, Zigbee, IEEE802.11b and other systems by calling different software modules. It has the characteristics of multi-network communication and belongs to the field of wireless communication.

Background technique

The coexistence of multiple short-distance wireless interconnection standards has created obstacles to the interconnection and intercommunication of devices using different wireless interconnection technologies. With traditional hardware-based gateways, it is very difficult to communicate or upgrade between different systems and standards. Based on the above reasons, the present invention proposes a multifunctional terminal based on software radio, a radio system that adopts a fixed hardware platform and realizes its flexibility through software changes.

A software defined radio refers to a fully configurable radio system that can be programmed with software to reconfigure the physical hardware. In other words, by making specific combinations of hardware to suit upcoming applications. The radio system hardware can also be adjusted to perform different functions in different environments. With the parallel development of short-range networks such as Bluetooth, Zigbee, and IEEE 802.11b, the intercommunication between different network devices has become an urgent problem to be solved. Based on the analysis of the characteristics of the network with a working frequency of 2.4GHz, the present invention realizes that one terminal can access multiple different networks. Table 1 gives the parameter characteristics of Bluetooth, Zigbee and IEEE 802.11b. It can be seen from the table that the working frequency band of these three network technologies is 2.4GHz, so the conversion from RF to IF and from IF to RF may be realized with the same set of hardware.

Table 1 parameter Bluetooth Zigbee IEEE 802.11b frequency band 2.4GHz 2.4GHz 2.4GHz transmission technology GMSK, FH-CDMA O-QPSK, DS-CDMA DS-CDMA Transmission rate 172.8-723.2Kit/s 250Kbit/s 6～-7Mbit/s

Contents of the invention

Technical problem: the purpose of this invention is to provide a kind of multi-mode mobile communication terminal and its signal processing method, this device and its method realize a can and bluetooth network, Zigbee network, IEEE A multifunctional terminal for communicating with 802.11b network and other networks with working frequency of 2.4GHz (such as cordless telephone network, etc.) and an intelligent signal processing method thereof.

Technical solution: The multi-mode mobile communication terminal of the present invention is composed of a transmitter and a receiver. The transmitter is composed of a reconfigurable terminal, a communication module, a D/A converter, a communication mode selector, an up-converter, a broadband amplifier, Composed of smart antennas, the output of the communication mode selector is connected to the input of the reconfigurable terminal, the output of the reconfigurable terminal is connected to the input of the D/A converter, and the output of the D/A converter is connected to the up-converter The input terminal of the up-converter is connected to the input terminal of the broadband amplifier, and the output terminal of the broadband amplifier is connected to the input terminal of the smart antenna; the receiver is composed of a smart antenna, a radio frequency filter and amplifier, a down-converter, and an A/D converter , communication mode mode recognition, mode converter, and reconfigurable terminal. The output end of the smart antenna is connected to the input end of the RF filter and amplifier, and the output end of the RF filter and amplifier is connected to the input end of the down-converter. The output terminal of the device is connected to the input terminal of the A/D converter, the output terminal of the A/D converter is connected to the input terminal of the communication mode pattern recognition and mode converter and the reconfigurable terminal, and the output of the communication mode pattern recognition and mode converter The terminal is connected to the input end of the reconfigurable terminal; wherein, the reconfigurable terminal and the smart antenna are shared by the transmitter and the receiver. The communication mode pattern recognition and mode converter are composed of a Wigner time-frequency analysis module, a fuzzy neural network controller and a mode conversion module in series, and the reconfigurable terminal is composed of a group of communication modules. This group of communication modules consists of Bluetooth, Zigbee and IEEE 802.11b respective modulation, spread spectrum and despreading, demodulation and other modules. The communication method selector consists of a group of keys. When the terminal communicates as the initiator, the communication mode selector firstly selects the network to communicate with, and then calls the corresponding module to realize the transmitting terminal capable of communicating with the network. When the terminal is used as a receiving terminal, first use the following signal processing method to determine which network the signal comes from, and then send a control signal to call the corresponding module to realize the receiving terminal that can communicate with the network.

The method of signal processing is to process the signal received by the smart antenna through a radio frequency filter and amplifier, then send it to the down converter to become an intermediate frequency signal, and then pass through the A/D converter to obtain an intermediate frequency digital signal and send it to the mode recognition and mode of communication mode In the converter, the intermediate frequency signal is first input to the Wigner time-frequency analysis module to extract three characteristic quantities that mark different network signals: the standard deviation of instantaneous frequency, the phase composition characteristics of the signal duration, and the standard deviation of instantaneous bandwidth. After these three feature quantities are sent to the fuzzy neural network controller, a fuzzy value is output. According to the fuzzy discrimination rule, the size of the fuzzy value reflects which network the received signal comes from, so the mode conversion module sends a control signal to the reconfigurable The terminal invokes the corresponding communication module. Afterwards, the received data signal passes through the reconfigurable terminal to realize functions such as despreading and demodulation of the signal, and finally restores the information data.

Beneficial effects: This terminal combines the characteristics of the three networks of Bluetooth, Zigbee and IEEE 802.11b. First of all, they all work in the same frequency band of 2.4GHz, and the same down-conversion circuit and up-conversion circuit can be used to realize the change of signal frequency. It saves hardware resources; secondly, they all adopt the communication method of spread spectrum, which can extract the time-frequency features of the received signals according to the different characteristics of their respective pseudo-random sequence signals, and then input them into the fuzzy neural network controller, which is easy to judge It can find out which network the received signal comes from, so as to call the corresponding communication module for processing; in addition, the terminal can be connected to three kinds of networks, which not only saves resources, but also has the characteristics of versatility and convenience. In addition, this method can also be used for other networks operating at 2.4GHz.

Description of drawings

Fig. 1 is a functional structure block diagram of the present invention. It realizes that a terminal can access Bluetooth, Zigbee, IEEE802.11b, cordless phone and other networks whose operating frequency is 2.4GHz.

Fig. 2 is a structural composition diagram of the present invention. This part consists of two parts: transmitting and receiving. The transmitting part consists of a reconfigurable terminal 1, a communication module 2, a D/A converter 3, a communication mode selector 4, an up-conversion circuit 5, a broadband amplifier 6, and an intelligent transmitting antenna 15 The receiving part is composed of intelligent receiving antenna 15, radio frequency filter and amplifier 8, down converter 9, A/D converter 10, communication mode recognition and mode converter 14, and reconfigurable terminal 1. Wherein, the reconfigurable terminal 1 and the smart antenna 15 are shared by the transmitting part and the receiving part. The mode identification and mode converter 14 of the communication mode is composed of a Wigner time-frequency analysis module 11 , a fuzzy neural network controller 12 and a mode conversion module 13 .

Figure 3 is a structural diagram of the fuzzy neural network controller. The fuzzy identification process of the communication mode is realized.

Fig. 4 is a software structure diagram of a reconfigurable terminal. Illustrates the software hierarchy of the terminal.

Detailed ways

Below in conjunction with embodiment and accompanying drawing, the present invention will be further described.

The receiving process is as follows: the signal received by the smart antenna is filtered and amplified by radio frequency, and then converted into an intermediate frequency signal by a down-conversion circuit. After the intermediate frequency signal is converted by A/D, the time-domain feature quantity and frequency-domain feature quantity of the sampling signal are obtained by using the Wigner distribution time-frequency analysis method. The fuzzy neural network is trained according to the different time-frequency characteristic quantities of the pseudo-random sequence codes used in the three kinds of network spread spectrum. After training and learning, the trained fuzzy neural network controller can judge according to the time-frequency characteristics of the received signal Which network (Bluetooth network, Zigbee network, or IEEE 802.11b network) the received signal is sent from, and output a control signal to control the reconfigurable terminal to call the corresponding software module to realize the underlying protocol, despreading, demodulation and other functions , and finally output the information data.

The transmission process is as follows: first select the network to be communicated through the communication mode selector, and then the reconfigurable terminal calls the corresponding communication module to perform a series of processing such as spread spectrum and modulation on the information data, and becomes an intermediate frequency analog after D/A conversion. The signal, after passing through an up-converter and a broadband amplifier, becomes a radio frequency signal that is easy to transmit, and is transmitted through a smart antenna.

The multi-mode mobile communication terminal is composed of a transmitter and a receiver. The transmitter consists of a reconfigurable terminal 1, a communication module 2, a D/A converter 3, a communication mode selector 4, an up-converter 5, a broadband amplifier 6, Composed of a smart antenna 15, the output terminal of the communication mode selector 4 is connected to the input terminal of the reconfigurable terminal 1, the output terminal of the reconfigurable terminal 1 is connected to the input terminal of the D/A converter 3, and the input terminal of the D/A converter 3 The output terminal is connected to the input terminal of the up-converter 5, and the output terminal of the up-converter 5 is connected to the input terminal of the broadband amplifier 6, and the output terminal of the broadband amplifier 6 is connected to the input terminal of the smart antenna 15; the receiver is composed of the smart antenna 15, the radio frequency filter and amplifier 8, down-converter 9, A/D converter 10, communication pattern recognition and mode converter 14, reconfigurable terminal 1, the output of the smart antenna 15 is connected to the radio frequency filter and the input of the amplifier 8 , the output terminal of the radio frequency filter and amplifier 8 is connected to the input terminal of the down converter 9, the output terminal of the down converter 9 is connected to the input terminal of the A/D converter 10, and the output terminal of the A/D converter 10 is connected to the communication mode The input end of the identification and mode converter 14 and the reconfigurable terminal 1, the output end of the communication mode identification and mode converter 14 is connected to the input end of the reconfigurable terminal 1; wherein, the reconfigurable terminal 1 and the smart antenna 15 are composed of Transmitter and receiver share. The communication mode pattern recognition and mode converter 14 is composed of a Wigner time-frequency analysis module 11 , a fuzzy neural network controller 12 and a mode conversion module 13 in series, and the reconfigurable terminal 1 is composed of a group of communication modules 2 . This group of communication modules consists of Bluetooth, Zigbee and IEEE 802.11b respective modulation and spread spectrum, despreading and demodulation modules. The communication method selector consists of a group of keys. When the terminal communicates as the initiator, the communication mode selector first selects the network to communicate with, and then invokes the corresponding module to realize the transmitting terminal capable of communicating with the network. For example, if the terminal wants to communicate with a certain device in the Bluetooth network, it first sends a control signal through a button in the communication mode selector, ordering the reconfigurable terminal to call a module related to Bluetooth to perform a series of processing operations, such as Spread spectrum, modulation, encryption, etc. on the signal. When the terminal is used as a receiving terminal, first run the following signal processing method to determine which network the signal comes from, and then send a control signal to call the corresponding module to realize the receiving terminal capable of communicating with the network.

The process of receiving signals is shown in Figure 2. First, the radio frequency signal received by the antenna passes through the radio frequency filter and amplifier, and then becomes an intermediate frequency signal through the down converter. Since Bluetooth, Zigbee and IEEE 802.11b networks all work in the same frequency band (2.4GHz ISM band), so these three networks all use the same down-conversion circuit, which saves hardware resources. The intermediate frequency analog signal becomes a digital signal after A/D conversion. Next, according to the time-frequency characteristic quantity of the sampled signal, it is judged which network the signal is sent from, that is, how to process the signal. This is the core part of the present invention. The process is described in detail below.

Firstly, the time-frequency analysis method is used to extract the features of the sampled signal. The time-frequency analysis method is a simple and visual analysis method for signals from two aspects of time domain and frequency domain. For this reason, the time-frequency analysis method has a high signal recognition ability. In the present invention, the Wigner distribution analysis method is adopted, which has better real-time characteristics. The Wigner distribution can be represented by Expression (1).

$\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; \&omega;</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;</span>}}{<span\; class="notranslate">\; \&Integral;</span>}_{<span\; class="notranslate">\; -</span><span\; class="notranslate">\; \&infin;</span>}^{<span\; class="notranslate">\; +</span><span\; class="notranslate">\; \&infin;</span>}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j\&tau;\&omega;</span>}}\mathrm{<span\; class="notranslate">\; d\&tau;</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

where y(t) is the sampled signal, which is band-limited and contains the mode signature of the signal (Bluetooth, Zigbee or IEEE 802.11b).

Through the Wigner transform, the time-frequency analysis of the signal in the time domain window T can obtain three characteristic quantities of the signal: the standard deviation of the instantaneous frequency, the characteristic quantity of the phase composition within the duration of the signal, and the standard deviation of the instantaneous bandwidth.

In order to obtain the first feature quantity from the given time-frequency distribution, first calculate the instantaneous frequency of the signal, as shown in expression (2).

${<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; \&omega;</span>}<span\; class="notranslate">\; ></span>}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; \&Integral;</span>\mathrm{<span\; class="notranslate">\; \&omega;W</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; \&omega;</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; d\&omega;</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Among them, y(t) is the time-domain distribution of the received signal, and W(t, ω) is the Wigner time-frequency distribution of the received signal. <ω> _t is the average frequency within a specific time period [t, t+Δt]. When Δt→0, <ω> _t can be considered as the instantaneous frequency at time t. Assuming that the signal is a general band-pass signal, it can be represented by (3) formula.

s(t)=A(t)e ^j(t) (3)

where A(t) is the amplitude of the signal and (t) is the phase of the signal. Instantaneous frequency ω _i such as (4) expression.

ω _i =<ω> _t (4)

Then the first feature quantity - the standard deviation of the instantaneous frequency can be obtained from the expression (5).

$\mathrm{<span\; class="notranslate">\; std</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; T</span>}}\underset{\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; T</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}^{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}}$ $<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

in, is the frequency average value in the time domain window T, which can be expressed by expression (6).

${\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; T</span>}}\underset{\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; T</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

Experiments have proved that the values of instantaneous frequency std(ω _i ) of IEEE 802.11b network and Zigbee network using DSSS spread spectrum method are relatively flat, but their respective std(ω _i ) values are different. Generally speaking, IEEE 802.11 The value of std(ω _i ) of b is larger, and the value of std(ω _i ) of Zigbee is smaller. But the bluetooth network that adopts FHSS mode, its instantaneous frequency std(ω _i ) fluctuates greatly.

The second feature quantity—the phase composition feature quantity within the signal duration is obtained based on the following considerations. In the time domain observation window T, the phase composition of the direct sequence spread spectrum method is continuous in the duration, but the phase composition of the frequency hopping spread spectrum method is discontinuous, because the frequency hopping method uses different Hopping frequency. Thus, different signals can be distinguished empirically over the duration of the signal.

The third characteristic quantity - the standard deviation of the instantaneous bandwidth of the signal can be obtained from the Wigner transformation. The mean square value of the signal bandwidth can be obtained from expression (7).

${\mathrm{<span\; class="notranslate">\; B</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}{<span\; class="notranslate">\; \&Integral;</span>}_{<span\; class="notranslate">\; -</span><span\; class="notranslate">\; \&infin;</span>}^{<span\; class="notranslate">\; +</span><span\; class="notranslate">\; \&infin;</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&omega;</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; \&omega;</span>}<span\; class="notranslate">\; ></span>}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; \&omega;</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; d\&omega;</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

It can be obtained from the above formula that the instantaneous bandwidth of the signal can be obtained by taking the square root of ^B2 , and the standard deviation of the instantaneous bandwidth can be obtained further. For Bluetooth networks, Zigbee networks and IEEE 802.11b networks, the standard deviations of their respective signal instantaneous bandwidths are different.

The time-frequency characteristic quantities of the pseudo-random sequence codes used in the three networks of Bluetooth, Zigbee and IEEE 802.11b are different, and the above three characteristic quantities extracted from various sequence signals are also different, so they can be distinguished according to this characteristic Signals of these three networks. The characteristic quantities of pseudo-random sequence samples used by these three networks are known, and these sample characteristic quantities are used to train the fuzzy controller network. When the network uses these samples to achieve the goal, the network can be used to judge the signal. The characteristic quantities of the received signal are extracted by Wigner time-frequency analysis method, and they are input into the fuzzy neural network controller, each of which corresponds to a different output range. In the present invention, what fuzzy controller adopts is fuzzy self-adaptive echo theory (Fuzzy ART) neural network algorithm, has characteristics such as quick judgment ability, stronger network robustness and higher accuracy, and its structure is as follows Shown in accompanying drawing 4. The bluetooth network adopts the FH-CDMA spread spectrum method. If the feature quantity of its standard pseudo-random sequence code is input into the fuzzy controller, the range of the corresponding output value is [0, 0.3]. The Zigbee network adopts the DS-CDMA spread spectrum method, and the characteristic quantity of its standard pseudo-random sequence sample is input into the fuzzy controller, and the corresponding output value ranges from (0.3, 0.6). The IEEE 802.11b network adopts the DS-CDMA spread spectrum method. Similarly, if the characteristic quantity of its standard pseudo-random sequence sample is input into the fuzzy controller, the corresponding output range is [0.6, 1.0]. As shown in Figure 3, the three fuzzy output range values and controller precision can be adjusted by adjusting the threshold parameter ρ of the fuzzy neural network controller. Firstly, 100 known pseudo-random sequence features and their corresponding output values are obtained from three different networks as samples to train the neural network, and the weights of the network are continuously changed through fuzzy control rules until the controller enters When it reaches a steady state and the network error reaches the specified value, stop training the network, and retain the parameters (including weights and thresholds) of each neuron in the controller at this time, which completes the training process (or learning process) of the network controller. . Using the trained network, the input signal sequence can be discriminated and output. For example, if the feature quantity of the input signal sequence is [0.11, 0.23, 0.98, 0.55, 0.67, 1, ..., 1.0], after the fuzzy controller, if the output value is 0.2, according to the above fuzzy discrimination rules, it can It is judged that the serial signal is sent by the Bluetooth device.

After the above steps, the identification process of the communication mode is completed. At the same time, the fuzzy controller sends a control signal to the reconfigurable terminal, and calls the corresponding communication module to realize the functions of despreading, demodulating and running the underlying protocol of the signal, thus obtaining the information data and completing the receiving process. The software structure of the reconfigurable terminal is shown in Figure 4, and the hardware is jointly completed by DSP+FPGA, in which DSP mainly completes the control function, and FPGA mainly completes functions such as signal processing and underlying protocols.

The process of transmitting signals is shown in Figure 2. First, the user selects the network to be communicated, and then sends a control signal to the reconfigurable terminal through the communication mode selector circuit to call the corresponding software module to realize the spread spectrum and modulation of information data. And functions such as the underlying protocol, and then become an analog signal through D/A conversion. Then it becomes a high-frequency signal through an up-conversion circuit, and then becomes an easy-to-transmit high-frequency signal through a broadband amplifier, and finally transmits it through a smart antenna to complete the signal transmission process.

Claims (3)

1. A multi-mode mobile communication terminal is characterized in that the terminal is composed of a transmitter and a receiver, and the transmitter is composed of a reconfigurable terminal (1), a communication module (2), a D/A converter (3) , a communication mode selector (4), an upconverter (5), a broadband amplifier (6), and a smart antenna (15), the output terminal of the communication mode selector (4) is connected to the input of the reconfigurable terminal (1) terminal, the output terminal of the reconfigurable terminal (1) is connected to the input terminal of the D/A converter (3), the output terminal of the D/A converter (3) is connected to the input terminal of the up-converter (5), and the up-converter The output end of (5) connects the input end of broadband amplifier (6), and the output end of broadband amplifier (6) connects the input end of smart antenna (15); Receiver consists of smart antenna (15), radio frequency filter and amplifier (8 ), a down converter (9), an A/D converter (10), a communication mode pattern recognition and a pattern converter (14), a reconfigurable terminal (1), and the output terminal of the smart antenna (15) is connected to a radio frequency The input terminal of the filter and the amplifier (8), the output terminal of the radio frequency filter and the amplifier (8) are connected to the input terminal of the down-converter (9), and the output terminal of the down-converter (9) is connected to the A/D converter (10 ), the output of the A/D converter (10) is connected to the input of the communication mode pattern recognition and mode converter (14) and the reconfigurable terminal (1), and the communication mode pattern recognition and mode converter (14 ) is connected to the input end of the reconfigurable terminal (1); wherein, the reconfigurable terminal (1) and the smart antenna (15) are shared by the transmitter and the receiver. 2. multi-mode mobile communication terminal according to right 1, it is characterized in that communication mode pattern recognition and pattern converter (14) are made up of Wigner time-frequency analysis module (11), fuzzy neural network controller (12) and pattern The conversion modules (13) are sequentially connected in series, and the reconfigurable terminal (1) is composed of a group of communication modules (2). 3. A signal processing method for the multi-mode mobile communication terminal as claimed in claim 1, characterized in that the method for signal processing is after the signal received by the smart antenna (15) is amplified through the radio frequency filter and the amplifier (8) , and then sent to the downconverter (9) for frequency conversion, and then sent to the A/D converter (10) for processing, to obtain the intermediate frequency digital signal and send it to the communication mode pattern recognition and mode converter (14). When the intermediate frequency signal is first input to Wigner The frequency analysis module (11) extracts three characteristic quantities that mark different network signals: the standard deviation of the instantaneous frequency, the phase composition characteristic quantity in the signal duration, and the standard deviation of the instantaneous bandwidth, and then these three characteristic quantities are sent into the fuzzy neural network After the controller (12), a fuzzy value is output. According to the fuzzy discrimination criterion, the size of the fuzzy value reflects which network the received signal comes from, so the mode conversion module (13) sends a control signal and sends it to the reconfigurable terminal (1) The corresponding communication module is called, and after that, the received data signal passes through the reconfigurable terminal (1) to realize functions such as despreading and demodulation, and restore information data.

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