CN100442685C - A Device for Ring Array Beam Forming in Vehicle Area Network - Google Patents

Abstract

The device for forming a ring array beam in the vehicle area network is a kind of cyclostationary characteristic of the signal, and applies the blind adaptive beamforming technology of the ring antenna array to the communication of the vehicle area network. The received signal preprocessing module (317) consists of multiple groups and The loop antenna array receiving part (31) has the same number of antennas as processing circuits, and each group of processing circuits consists of a low-noise power amplifier (32), a baseband converter (33), a low-pass filter (34), and an analog/digital converter. (35) are formed in series successively, and synchronizer (36) joins with the analog/digital converter (35) of each group respectively; (38) are formed in series successively, and the effect of digital signal processor (37) is to utilize the cyclostationary characteristic of signal, realizes the digital calculation part of blind self-adaptive beamforming; A part (320), a low-power transmitting module (312), a low-power receiving module (313), a decryptor and a decoder (314), and a receiving terminal (315) are sequentially connected in series.

Description

A Device for Ring Array Beam Forming in Vehicle Area Network

technical field

The present invention utilizes the cyclostationary characteristics of signals to apply the loop antenna array blind self-adaptive beamforming technology to vehicle area network communication, and belongs to the technical field of mobile communication.

Background technique

Cyclostationary signals are a very important class of non-stationary signals, and their second-order statistical properties, that is, the mean value and autocorrelation function of the signal, vary periodically. Because most of the signals used in mobile communication systems have unique cyclostationary characteristics, it can be used to realize blind beamforming.

The signal from the mobile station arrives at the antenna array from a certain direction, which may be called the direction of arrival (DOA). Adaptive antenna is the main type of smart antenna, which can realize omnidirectional tracking and complete the receiving and sending of user signals. The adaptive array antenna system uses digital signal processing technology to identify the arrival direction of user signals, and forms the antenna main beam in this direction. The adaptive array antenna provides different spatial signals according to different spatial propagation directions of user signals, which can effectively overcome the influence of interference on the system.

The antenna receiving system can adopt a certain algorithm to distinguish signals from different directions of arrival mainly in the baseband, thereby reducing interference and enhancing system performance. The performance of the smart antenna system mainly depends on the baseband algorithm and array structure, so it is necessary to design a reasonable smart antenna array structure while exploring the efficient baseband algorithm. The optimization of the array structure is also a key issue in the field of smart antennas. The ring array has good omnidirectional scanning characteristics, which can create conditions for the rapid shaping of smart antennas.

Beamforming is a method that can effectively reduce co-channel interference and is widely used in radar, personal communication systems, etc. Traditional beamforming methods require prior knowledge of signal direction of arrival, steering vector, training sequence, etc. Two methods based on user transmission training sequence and signal direction of arrival have been proposed, as shown in Figure 1. However, the former needs to synchronize the training sequence and occupy more channels, while the latter needs to verify the data stream arriving at the array, which requires a large amount of calculation and is relatively complicated to implement, so it is still difficult to apply.

The blind adaptive beamforming algorithm proposed through in-depth study of signal characteristics can overcome the above shortcomings to a large extent. Since the vast majority of signals in mobile communications are cyclostationary, and it is relatively easy to obtain different cyclic frequencies, a variety of methods for blind adaptive beamforming using cyclostationary properties have been proposed, such as Spectrum Self-Coherent Restoration (SCORE) algorithm and Cyclic Adaptive Beamforming (CAB) algorithm, etc.

Vehicle area network applications must solve the problem of effective and reliable communication during high-speed movement, which requires the applied algorithm to have strong real-time performance, so it is necessary to research and develop a method with better calculation, convergence speed and performance .

In the vehicle area network, various devices in the vehicle form a wireless personal area network. Through the vehicle antenna, they can communicate with the public mobile communication system outside the vehicle, as well as the wide area network, local area network, Internet, etc. for data and voice communication. It is a system with low power inside the car and high power outside the car. However, a single omnidirectional receiving antenna can no longer meet the high-speed transmission requirements for high-quality data, voice and graphics in harsh environments. How to design and install an array composed of multiple antenna elements on a vehicle, and adopt a fast-converging, moderately computationally intensive beamforming method is of great practical significance.

Contents of the invention

Technical problem: The purpose of this invention is to design a device for forming a circular array beam in a vehicle area network, so as to reduce co-channel interference and save channel resources at the same time.

Technical solution: The present invention is an adaptive beamforming method based on signal cyclostationary characteristics, which does not require reference signals, direction of arrival, etc., and the antenna array adopts a circular array. In addition, it applies the designed annular array beamforming method to the vehicle area network, which is loaded on the vehicle.

The present invention not only adopts an effective and novel baseband self-adaptive beam-forming method, that is, an adaptive beam-forming method utilizing the cyclostationary characteristics of signals, but also adopts a ring array structure which is beneficial to receiving signals in all directions.

The present invention is composed of a loop antenna array receiving part, a received signal preprocessing module, a beam forming module, a vehicle area network conversion and a receiving module in series, and the power supply supplies power to the four parts;

Among them, the received signal preprocessing module is composed of multiple groups of processing circuits with the same number of antennas as the receiving part of the loop antenna array, and each group of processing circuits consists of a low-noise power amplifier, a baseband converter, a low-pass filter, and an analog/digital converter. The synchronizer is connected to the analog/digital converter of each group respectively; the beamforming module is composed of a digital signal processor, a despreader and an equalizer in series; the vehicle area network conversion and receiving module is converted by the network Part, low-power transmitting module and low-power receiving module, descrambler and decoder, and receiving terminal are sequentially connected in series. Among them, the inter-network conversion part includes power conversion, protocol conversion, and working power conversion.

The digital signal processor in the beamforming module is composed of a signal space projection converter, a memory, a cross-correlation calculation part, and an adaptive weight calculation part in series; among them, the cross-correlation calculation part consists of a time offset device, a frequency offset device, a synchronization The adaptive weight calculation part is composed of an adaptive maximum correlation operator, a weight adjuster, and a weight generator; the first output terminal of the memory is connected to the input terminal of the time biaser, A time offset device, a frequency offset device, a cross-correlator, an adaptive maximum correlation operator, a weight value adjuster, and a weight value generator are connected in series; the second output terminal of the memory is connected to a synchronizer, and the cross-correlator and the weight value generator are connected in series. connected in series; the third output terminal of the memory is connected to the input terminal of the autocorrelator, and the output terminal of the autocorrelator is connected to the weight generator, and the weight generator outputs weights w ₁ (n), w ₂ (n), ..., w _M (n); the input signal of the digital signal processor is the digital receiving signal (x ₁ (n), x ₂ (n), ..., x _M (n)), beamforming signal (y(n)), synchronous signal (T(n)) and cycle frequency (α), the output signal is the weights w ₁ (n), w ₂ (n), . . . , w _M (n). The vehicle-mounted loop antenna array is mounted on the top of the mobile vehicle.

The receiving part of the loop antenna array is composed of 8 isotropic antenna array elements evenly distributed on a circle with a certain radius, and receives the approximate plane wave signal from the mobile communication network. The function of the received signal preprocessing module is to remove part of the noise and convert the signal into a digital baseband signal, which is prepared for the future beamformer in the design.

The beamforming module is implemented by a digital signal processor, which adjusts the weights of each received signal to the optimal value through a certain algorithm. The input signals of the adaptive beamformer are eight preprocessed baseband digital signals and the cycle frequency of the useful signal, and the output signal is the digital signal multiplied by the optimal weight. The final effect is to align the main lobe of the formed beam with the useful signal, and at the same time try to direct the null of the beam towards the interference signal, so that the output signal reaches the maximum signal-to-noise ratio.

In addition to the digital signal, the input of the digital signal processor also includes the cycle frequency, the synchronization signal and the output signal of the beamformer. It differs from traditional beamformers in that it does not require the input of direction of arrival, steering vector or training sequence, only the additional input of cycle frequency. Since most communication signals have cyclostationary characteristics, that is, their statistics have periodic laws, this periodic law is easier to study than general non-stationary signals, and there are more available statistical laws than stationary signals, therefore, this The adaptive beamforming method can not only reduce the amount of input prior information, but also achieve the effect of fast convergence and moderate calculation amount, which is easy to implement in engineering.

In addition, it is very meaningful to apply this circular array beamforming scheme to the vehicle area network. The ring array can be installed on the top of the vehicle, not only can receive the signal from the base station of the mobile communication network in all directions, but also has the advantages of not being limited by the volume of the antenna of the mobile station and not directly radiating to the human body. The wireless vehicle area network is realized in the car, and the mobile terminal in the car is connected to the converter through the low-power wireless vehicle area network, and then the converter is connected to the mobile communication network through the loop antenna. The circular array can not only receive signals in all directions, but also can be converted into a semi-circular or arc antenna array when power needs to be saved.

Beneficial effects: the method of the present invention utilizes the characteristic that most communication signals are cyclostationary, and establishes a cyclostationary signal model received by a loop antenna array at the receiving end of mobile communication, and then realizes blind adaptive beamforming. It does not require prior knowledge such as array calibration, direction of arrival, training sequence, spatial autocorrelation matrix of interference and noise, and only needs the cyclic frequency of the signal at the transmitting end. Compared with other blind adaptive beamforming methods, it has a faster convergence speed and a moderate amount of computation. At the same time, the annular array has good omnidirectional scanning characteristics, which can create conditions for the rapid shaping of smart antennas.

This method has certain significance in improving communication system capacity and reducing computational complexity, and because it does not require prior information such as direction of arrival and training sequence, it is more practical in specific applications. It is applied in the vehicle area network and can support high-speed moving vehicles to communicate high-quality, high-speed real-time data, images and various multimedia messages. In addition, applying the ring array to the top of the vehicle does not affect the practical function and aesthetics of the vehicle, and has the advantages of not being limited by the volume of the mobile station antenna and not directly generating radiation to the human body, so it is a feasible solution.

The specific method and device for realizing the ring array beamforming in the vehicle area network of this design are shown in Fig. 3 and Fig. 4 . The advantage is that the digital signal processor in the beamforming module in the block diagram has no reference signal or direction-of-arrival input, which reduces co-channel interference and saves channel resources.

The vehicle-mounted receiving antenna array is implemented by a ring array composed of 8 antenna elements. The advantages are: it has good comprehensive scanning characteristics and can receive signals in all directions; it can also be converted into a semicircle or arc array when power needs to be saved; the ring antenna array Installed on the top of the vehicle, it is practical and does not affect the appearance.

Description of drawings

FIG. 1 is a schematic diagram of adaptive beamforming based on direction of arrival (DOA). Among them, Fig. 1a is a schematic diagram of basic adaptive beamforming; Fig. 1b is a block diagram of the adaptive beamforming algorithm part in Fig. 1a.

Figure 2 is a schematic diagram of a loop antenna array, which consists of 8 antenna elements.

FIG. 3 is a block diagram of the overall system implementation of the present invention, that is, a block diagram of a vehicle-mounted annular array beamforming and receiving system. x ₁ (n), x ₂ (n), . . . , x _M (n) represent the digital signals after receiving signal preprocessing, and y(n) represent the output signals processed by the beamforming module.

FIG. 4 is a block diagram of a digital signal processor in the overall implementation block diagram of FIG. 3 of the present invention.

Fig. 5 is a schematic diagram of the application of the present invention in a vehicle area network.

In the above figure, there are: loop antenna array receiving part 31, low noise power amplifier 32, baseband converter 33, low pass filter 34, analog/digital converter 35, synchronizer 36, digital signal processor 37, despreader And equalizer 38, power conversion 39, protocol conversion 310, working power conversion 311, low power transmitting module 312, low power receiving module 313, decryptor and decoder 314, receiving terminal 315, power supply 316, received signal preprocessing module 317 , a beam forming module 318 , a vehicle area network conversion and receiving module 319 , and an inter-network conversion part 320 .

Signal space projection converter 41, memory 42, time offset device 43, frequency offset device 44, synchronizer 45, cross correlator 46, autocorrelator 47, adaptive maximum correlation operator 48, weight value adjuster 49, weight value Generator 410 , cross-correlation calculation part 411 , adaptive weight calculation part 412 . The input signal is the digital receiving signal x ₁ (n), x ₂ (n), ..., x _M (n), the beamforming signal y(n), the synchronization signal T(n) and the cycle frequency α, and the output signal is the weight w ₁ (n), w ₂ (n), . . . , w _M (n).

Detailed ways

Below in conjunction with accompanying drawing, the scheme design of the present invention is described in detail as follows.

1. Module composition

The main implementation block diagram designed by the present invention is shown in FIG. 3 , and the specific adaptive beamforming method is described in FIG. 4 .

Figure 3 depicts the block diagram of the vehicle-mounted circular array beamforming and receiving system. It belongs to the receiving end design of mobile communication, including five parts: loop antenna array receiving part 31 , received signal preprocessing module 317 , beamforming module 318 , vehicle area network conversion and receiving module 319 and power supply 316 .

The leftmost is a circular antenna array composed of 8 antenna elements. The radius of this ring is R, and the 8 antenna elements are evenly distributed on the circle. The continuous signals received by each antenna element are respectively u ₁ (t), u ₂ (t), ..., u _M (t), they respectively pass through the low noise power amplifier to amplify the useful signal power, and then pass through the baseband converter Converts a continuous signal from frequency band to baseband. After the baseband signals received by the eight antennas are obtained, the interference signals outside the frequency band are filtered out through the low-pass filter respectively. Subsequently, each analog signal that has passed the low-pass filter is passed through an analog/digital converter, that is, the analog signal is converted into a digital signal after being sampled, quantized, and synchronized. The reason for this design is that the subsequent beamforming module can be calculated by digital signal processing, the speed will be faster, and the implementation is relatively simple. After the above steps, the 8 signals are converted into x ₁ (n), x ₂ (n), ..., x _M (n) digital signals, which are also the input signals of the beamforming module.

The beamforming module is connected after the A/D converter, its input signal is x ₁ (n), x ₂ (n), ..., x _M (n), and its output signal is y(n). Among them, after the input signals x ₁ (n), x ₂ (n), ..., x _M (n) are multiplied by their respective weights w ₁ (n), w ₂ (n), ..., w _M (n) to obtain the desired output signal y(n). The main part of the beamforming module is a digital signal processor, its input has x ₁ (n), x ₂ (n), ..., x _M (n), y(n) and synchronization signal T(n), the output are the weights w ₁ (n), w ₂ (n), . . . , w _M (n).

The specific adaptive beamforming manner has been specifically described in FIG. 4 . The main idea is that this adaptive beamforming module does not require the direction of arrival, training sequence and matrix verification, but only needs the cyclic frequency of the useful signal at the transmitting end to use the corresponding adaptive algorithm, and the adaptive beamforming after digital signal processing After calculation, the optimal weight value is obtained. After the optimal weight is multiplied by the input signal, the signal after removing interference and noise is obtained. Among them, it is very important to model the communication signal as a cyclostationary signal. The statistical characteristics of the cyclostationary signal are periodic, and the blind adaptive algorithm adopted in the present invention utilizes the periodic second-order statistical characteristics, and the blind adaptive beamforming can be realized by using a small amount of calculation, and then the output signal Perform despreading and equalization.

Finally, the beamformed output signal y(n) passes through the inter-network conversion part, including: converting high-power communication signals into low-power ones, converting mobile communication standards into wireless personal area network standards (including Transmission rate conversion), convert the working power. After the converted communication signal passes through the low-power transmitting module, the low-power receiving module and the deciphering and decoding module, the receiving terminal receives the signal.

The power supply supplies power to the other four module sections.

2. Description of the core part

The core parts in the implementation block diagram of the present invention are the loop antenna array receiving part 31, the digital signal processor 37 and the vehicle area network conversion and receiving module 319, as shown in the lower right corner of Fig. 2, Fig. 4 and Fig. 3 respectively.

(1) Loop antenna array receiving part

A circular array structure that is beneficial to receiving signals in all directions is adopted in realization. Figure 2 is a schematic diagram of a uniform ring array. Suppose there are M array elements uniformly arranged on a circle with radius R. Compared with the size of the antenna array, the signal source is relatively far away from the antenna array, so it can be considered that the signal arrives in the form of a plane wave, and the energy when it reaches each array element is the same. Due to the difference in the wave path reaching each array element, the phase of the signal on each array element is different. Let the wavelength of the signal be λ, and the direction of arrival angle be θ. The collection of steering vectors in all directions constitutes the array manifold of the antenna array. Different antenna arrays have different array manifolds, and the array manifolds largely determine the performance of smart antenna systems.

For a circular array, the circle O is generally selected as the phase reference point, and the rightmost array element is used as the first array element, and each array element in the clockwise direction is the second array element, the third array element, and so on. For a signal with a direction of arrival angle of θ, the relative phase on the lth array element can be obtained:

φ _l = βRcos(θ+2π(l-1)/m), β=2π/λ, l=1, 2, ..., M

The steering vector of the circular array at the direction of arrival angle θ is obtained as:

$a\left(\mathrm{\θ}\right)=\left[\begin{array}{c}{e}^{j{\mathrm{\φ}}_1}\\ e^{j{\mathrm{\φ}}_2}\\ .\\ .\\ .\\ e^{j{\mathrm{\φ}}_m}\end{array}\right]=\left[\begin{array}{c}{e}^{\mathrm{j\β}R\cos \mathrm{\θ}}\\ e^{\mathrm{j\β}R\cos (\mathrm{\θ}+2\mathrm{\π}/m)}\\ .\\ .\\ .\\ e^{\mathrm{j\β}R\cos (\mathrm{\θ}+2\mathrm{\π}(m-1)/m)}\end{array}\right],$ where M=8

(2) Digital signal processor

a.principle

Beamforming mainly refers to forming a beam lobe for a useful signal in a specific direction, and directing the null of the beam to an interference signal to attenuate co-channel interference in other directions.

The cyclostationary property means that when a signal exhibits cyclostationarity, there is a certain degree of spectral correlation in the frequency domain. When the time delay is constant, the cycle frequency of the signal is related to the baud rate of the signal transmission, while the cycle frequency of the stationary noise signal is zero. The blind beamforming algorithm based on the cyclostationary characteristics of the signal is to use the cyclic frequency of the signal to perform adaptive beamforming under the assumption that the cyclic frequency of the desired signal is different from that of the interference signal and the noise signal is a stationary signal.

Assuming that each array element is ideal and isotropic, the received digital signal x(n) is an M×1-dimensional complex vector. The useful signal and the interference signal are narrowband plane waves, there are K signals, and x(n) can be expressed as a vector: $x\left(\mathrm{no}\right)=\underset{k=1}{\overset{m}{\mathrm{\Σ}}}a\left({\mathrm{\θ}}_k\right){\mathrm{the\; s}}_k\left(\mathrm{no}\right)+i\left(\mathrm{no}\right)+v\left(\mathrm{no}\right).$ Among them, s _k (n) is the useful signal, a(θ _k ) is the steering vector of the kth arriving signal, i(n) is the interference signal, and v(n) is the M-dimensional white noise.

The method of beamforming is to find the weight vector according to a certain criterion, so that the useful output signal is y(n)=w ^H x(n), and the cost function of the algorithm used in this paper is J=<|y(n)-r (n)| ² > _T , where r(n)=c ^H x(n-τ)e ^j2πan , c is any control vector, this cost function can be regarded as the array output y(n) and r(n, The least squares problem of τ) actually takes the maximum correlation between x(n) and its own time-frequency offset. Therefore, as long as the cycle frequency α is known, the cost function can be minimized to achieve the purpose of beamforming to extract useful signals. The optimal weight vector is obtained as: $W_{\mathrm{SC}}=R_{\mathrm{xxx}}^{-1}{R}_{\mathrm{xr}}$

Ideally, it can converge to the beamformer in the sense of maximum output SINR, resulting in an optimal solution. However, it is impossible to achieve ideal conditions in practice, and there are pointing errors and array element disturbances. In summary, the influence from the noise subspace component is relatively large. The method of subspace decomposition can be used to project the signal steering vector to the signal subspace, and the original basic algorithm can be corrected. The new method designed can be applied to practical engineering, and its convergence speed and performance are satisfactory.

b. Realize the module

The implementation of the digital signal processor in the present invention is shown in FIG. 4 . The input signals of the digital signal processor are: digital input signal x ₁ (n), x ₂ (n), ..., x _M (n), output signal y(n) of the beamforming module, synchronization signal T(n) And the cycle frequency α of the communication signal. The synchronization signal is used to synchronize the signals in the digital processing module, and the cycle frequency α can frequency-shift the input signal, and then use the cyclostationary statistical characteristics of the communication signal to effectively adjust the weight.

Comparing Fig. 4 with Fig. 1b, it can be seen that the beamforming implementation adopted by the present invention has no training sequence (or direction of arrival), but only the cyclic frequency of the signal. Because the cycle frequency only occupies a small bandwidth, it can support the requirements of high-speed and high-quality signal transmission of the third generation mobile communication. The output signal of the digital signal processor is the weight coefficient calculated adaptively. Referring to Fig. 3, weight coefficients w ₁ (n), w ₂ (n), ..., w _M (n) and digital input signals x ₁ (n), x ₂ (n), ..., x _M (n) phase After multiplication, the output signal y(n) of the beamformer is obtained.

The digital signal processor module is composed of the following parts: a signal space projection converter 41 , a memory 42 , a cross-correlator 46 , a cross-correlation calculation part 411 , and an adaptive weight calculation part 412 .

As shown in Figure 4, the digital input signals _x1 (n), _x2 (n), ..., _xM (n) are first transformed by signal space projection, and the steering vector is projected to the signal subspace (but no input Steering vector), which can eliminate part of the influence from noise. Then the processed signal is input into the memory to facilitate the calculation of the subsequent cross-correlation matrix and auto-correlation matrix.

The principle of the cross-correlation calculation part is described above, and the implementation method is shown in Figure 4. The input signal in the memory is divided into two paths, one path passes through the time deviation device and the frequency deviation device, and the other path passes through the synchronizer. The two signals are simultaneously input into the cross-correlator to calculate the cross-correlation function. Among them, the frequency offset part needs the cycle frequency α of the input signal.

Then, digital signal processing enters the adaptive weight calculation part. It is divided into three processes: firstly, the current weight coefficient is calculated from the cross-correlation matrix and autocorrelation matrix, and then an adaptive algorithm is used to adaptively select the maximum correlation function and perform correlation calculation. During the adaptive calculation process, the weight adjuster is used to adjust the weight coefficient adaptively at any time until the adaptive convergence reaches the optimal weight value.

The calculation of the entire adaptive beamforming does not require a training sequence (or direction of arrival). This method has great advantages, can effectively save bandwidth and is reasonably feasible in practical applications.

(3) Vehicle area network conversion and receiving module

The design of this part is mainly applied in the vehicle area network. The purpose is to realize high-speed and high-quality signal communication through the vehicle-mounted device. The vehicle can safely and reliably receive the communication signal at the receiving terminal when running at high speed. The specific design is shown in the lower right part of Figure 3.

In the wireless vehicle area network, it includes an inter-network conversion part 320 , a low-power transmitting module 312 , a low-power receiving module 313 , a decryptor and decoder 314 , and a receiving terminal 315 .

The inter-network conversion part includes power conversion (from high power to low power), protocol conversion (from mobile communication standard to IEEE 802.11 corresponding standard) and working power conversion. Protocol conversion includes network conversion such as transmission rate conversion. The low-power transmitting and receiving modules in the wireless vehicle area network ensure that the high-power signals received by the vehicle-mounted antenna in high-speed operation will not affect the human body after processing, and at the same time, high-speed broadband signals can be received normally. Since equalization and despreading have been carried out before, the wireless receiving module here only has decryption and decoding operations. Finally, the digital signal is received by the receiving terminal. This receiving terminal refers to various communication terminals used in the car, such as mobile phones, notebook computers, etc.

3. Implementation device of vehicle area network application

The realization of the beamforming method of the circular array can be applied in the wireless vehicle area network, as shown in FIG. 5 . Outside the vehicle, a loop antenna array is mounted on the roof for convenient omnidirectional reception. In the car, mobile terminals (such as mobile phones) and equipment (notebooks, PDAs, etc.) form the wireless personal area network in the car. The ring smart antenna communicates with the base station of the cellular network and other mobile communication systems for long-distance communication. The mobile terminal in the car can not only communicate with the equipment in the car through the wireless vehicle area network, but also communicate with the external cellular network through interface conversion.

The device for forming the annular array beam in the vehicle area network in the presidential structure is composed of the annular antenna array receiving part 31, the received signal preprocessing module 317, the beam forming module 318, the vehicle area network conversion and receiving module 319, and the power supply 316 is connected in series. These four parts supply power; Wherein, the received signal preprocessing module 317 is made up of multiple groups and the same processing circuit of the number of antennas of the loop antenna array receiving part (31), and each group of processing circuits is composed of a low-noise power amplifier 32, a baseband converter 33, A low-pass filter 34 and an analog/digital converter 35 are connected in series successively, and a synchronizer 36 is respectively connected with the analog/digital converter 35 of each group; the beam forming module 318 is composed of a digital signal processor 37, a despreader and an equalizer The vehicle area network conversion and receiving module 319 is composed of the inter-network conversion part 320, the low-power transmitting module 312 and the low-power receiving module 313, the descrambler and the decoder 314, and the receiving terminal 315. Among them, the network conversion part 320 includes power conversion 39 , protocol conversion 310 , and working power conversion 311 . The digital signal processor 37 in the beamforming module 318 is composed of a signal space projection converter 41, a memory 42, a cross-correlation calculation part 411, and an adaptive weight calculation part 412; Device 43, frequency deviation device 44, synchronizer 45, cross-correlator 46, auto-correlator 47 constitute, adaptive weight calculation part 412 is composed of adaptive maximum correlation operator 48, weight adjuster 49, weight generator 410 Form; the first output terminal of memory 42 connects the input end of time deviation device 43, time deviation device 43, frequency deviation device 44, cross-correlator 46, self-adaptive maximum correlation arithmetic unit 48, weight adjuster 49, weight generation The second output terminal of the memory 42 is connected to the synchronizer 45, and the cross-correlator 46 and the weight generator 410 are connected in series; the third output terminal of the memory 42 is connected to the input end of the autocorrelator 47, and the autocorrelator 47 The output terminal of the weight generator 410 is connected to the weight generator 410, and the weight value w ₁ (n), w ₂ (n), ..., w _M (n) is output by the weight generator 410; the input signal of the digital signal processor 37 is a digital receiving Signal x ₁ (n), x ₂ (n), ..., x _M (n), beamforming signal y(n), synchronization signal T(n) and cycle frequency α, the output signal is weight w ₁ (n) , w ₂ (n), . . . , w _M (n).

Therefore, using a mobile terminal such as a mobile phone in a high-speed moving vehicle can reduce the transmission power and use the wireless vehicle area network. The car has become the terminal of the mobile communication system, which is equivalent to the transfer station of the mobile phone, and it replaces the mobile phone to receive high-power signals. At the same time, the ring array installed on the roof can receive signals in all directions, creating conditions for the rapid shaping of smart antennas.

This design solution can solve the difficulties faced by using smart antennas on mobile phones, and can also reduce the harm of high power to the human body. The advantage of applying the loop antenna array to the roof of the car is that the signal reception effect is good, and the design scheme is not only easy to implement, but also does not affect the shape design of the car. If the vehicle needs to save power consumption, it is very convenient to change the circular array into a semicircular array or an arc array.

Claims (2)

1. A device forming an annular array beam in a vehicle area network, characterized in that the device consists of an annular antenna array receiving part (31), a received signal preprocessing module (317), a beam forming module (318), and a vehicle area network conversion and the receiving module (319) are sequentially connected in series; Wherein, the function of the received signal preprocessing module (317) is to carry out power amplification, filter out interference, analog/digital conversion preprocessing work to the received signal, the output digital signal x ₁ (n), x ₂ (n), ..., x _M (n) is directly calculated and processed by the digital signal processor (37) in the beamforming module (318), and the received signal preprocessing module (317) is processed by a plurality of groups having the same number of antennas as the receiving part of the loop antenna array The circuit is composed of; each group of processing circuits is sequentially connected in series by a low-noise power amplifier (32), a baseband converter (33), a low-pass filter (34), and an analog/digital converter (35); the loop antenna array receiving part ( The continuous signal received by each antenna array element in 31) passes through the low-noise power amplifier (32) respectively to eliminate part of the noise, and the continuous signal is converted from the frequency band to the baseband signal by the baseband converter (33), and passed through the low-pass filter ( 34) filter the interfering signal outside the frequency band, convert the analog signal into a digital signal by the analog/digital converter (35), and the synchronizer (36) in the received signal preprocessing module (317) is respectively connected with the analog/digital signal of each group. The converters (35) are connected and are responsible for the synchronous work of multiple received signal analog/digital conversions. The beamforming module (318) is used to form beam lobes in the direction of useful signals, and direct the nulls of the beams to interference signals. A blind adaptive algorithm based on signal cyclostationarity is used to realize adaptive beamforming. The beamforming module (318) is composed of a digital signal processor (37), a despreader and an equalizer (38) in series. The signal processor (37) is characterized in that direction of arrival, training sequence and matrix check are not required, and only the cycle frequency of the useful signal is needed to adaptively calculate the weight coefficient w ₁ (n) of the beamforming module (318) , w ₂ (n),..., w _M (n); the vehicle area network conversion and receiving module (319) solves the compatibility problem between the vehicle area network and the mobile communication network; the output signal of the beamforming module (318) passes through the vehicle area network The conversion and receiving module (319) obtains the received signal required by the vehicle area network terminal, and the function of the digital signal processor (37) in the beamforming module (318) is to effectively utilize the cyclostationary characteristic of the signal to realize blind adaptive beamforming The digital calculation function formed, the digital signal processor (37) is successively connected in series by the signal space projection converter (41), memory (42), cross-correlation calculation part (411), adaptive weight value calculation part (412), After the input signal x ₁ (n), x ₂ (n), ..., x _M (n) undergoes signal space projection transformation, the steering vector is projected to the signal subspace to eliminate part of the influence from the noise, and then the processed The signal input of the signal is input in the memory, to facilitate the calculation of the cross-correlation matrix and the autocorrelation matrix, the output signal of the memory (42) is divided into three paths, the first path passes through the time deviation device (43), the frequency deviation device (44), the second Two routes pass through the second synchronizer (45), and the signals of the two routes are input into the cross-correlator (46) simultaneously to calculate the cross-correlation matrix; the third output end of the memory (42) is connected to the auto-correlation device (47), for calculating the auto-correlation Matrix; the adaptive weight calculation part (412) in the digital signal processor (37) is made of adaptive maximum correlation operator (48), weight adjuster (49), weight generator (410), and adaptive The weight calculation part (412) is divided into three operation processes: first, according to the cross-correlation matrix and the autocorrelation matrix, the current weight coefficient is calculated by the weight generator (410); then the adaptive maximum correlation operator (48 ) to select the maximum cross-correlation function; finally, utilize the weight adjuster (49) to adaptively adjust the weight coefficient until it converges to the optimal weight; The input signal of digital signal processor (37) is digital reception signal x ₁ (n), x ₂ (n), ..., x _M (n), beamforming signal y (n), synchronous signal T (n), output Signals are weight coefficients w ₁ (n), w ₂ (n), ..., w _M (n), this weight coefficient vector and the input signal vector x ₁ (n) of the beamforming module (318), x ₂ ( n), ..., x _M (n) are multiplied to obtain the beamforming signal y(n). 2. The device for forming a circular array beam in a vehicle area network according to claim 1, wherein the vehicle-mounted circular antenna array is mounted on the top of a moving vehicle.

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