CN113206693A - Multi-antenna single carrier frequency domain equalization simplification device and algorithm - Google Patents

Multi-antenna single carrier frequency domain equalization simplification device and algorithm Download PDF

Info

Publication number
CN113206693A
CN113206693A CN202110398980.5A CN202110398980A CN113206693A CN 113206693 A CN113206693 A CN 113206693A CN 202110398980 A CN202110398980 A CN 202110398980A CN 113206693 A CN113206693 A CN 113206693A
Authority
CN
China
Prior art keywords
antenna
frequency domain
signal
array
domain equalization
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202110398980.5A
Other languages
Chinese (zh)
Inventor
熊军
孙博韬
马杰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Rinfon Technology Co ltd
Original Assignee
Beijing Rinfon Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Rinfon Technology Co ltd filed Critical Beijing Rinfon Technology Co ltd
Priority to CN202110398980.5A priority Critical patent/CN113206693A/en
Publication of CN113206693A publication Critical patent/CN113206693A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0224—Channel estimation using sounding signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03159—Arrangements for removing intersymbol interference operating in the frequency domain

Abstract

The invention relates to the technical field of communication, in particular to a multi-antenna single carrier frequency domain equalization simplifying device and an algorithm, which comprise a multi-antenna beam forming processing module, wherein the multi-antenna beam forming processing module comprises an antenna array receiver module, an analog-to-digital converter, a digital beam forming device and a beam controller; the multi-antenna beam forming processing module carries out channel estimation according to a predicted reference signal and a received reference signal, and finally a beam forming algorithm forms a weight of network beam forming; the invention uses the weighting factor of the beam forming to complete the weighting combination of the received signals, and the signals after the weighting combination are uniformly synchronized, thereby simplifying the complexity of the parallel synchronization of the multiple antennas, better resisting the influence of noise on the synchronization after the weighting combination, ensuring the synchronization to be more accurate and having strong creativity.

Description

Multi-antenna single carrier frequency domain equalization simplification device and algorithm
Technical Field
The invention relates to the technical field of communication, in particular to a multi-antenna single carrier frequency domain equalization simplifying device and algorithm.
Background
The intelligent antenna array is composed of a plurality of antenna units, each antenna is connected with a complex weighting device, and finally the complex weighting devices are combined and output through an adder. The intelligent antenna with the structure can only complete spatial processing. Meanwhile, the intelligent antenna with space domain and time domain processing capacity is relatively complex in structure, and a delay tap weighting network is connected behind each antenna. The main meaning of adaptive or intelligent means that these weighting coefficients can be updated and adjusted adaptively according to a certain adaptive algorithm.
The basic problems to be solved by the intelligent antenna array are interference resistance and channel gain of a desired signal is improved. Interference rejection refers to improving the reception quality of a desired signal in the context of an interfering signal, that is, increasing the processing gain of the desired signal and suppressing interference. Smart antennas do this without relying solely on modulation techniques, sources, channel coding techniques, and other inherent conventional techniques. The intelligent antenna studies how to adaptively and independently adjust the excitation coefficients of each antenna unit of the antenna array, and intelligently change the beam shape to obtain spatial processing gain so as to improve the final reception.
The goal of beamforming is to form the best combination or allocation of baseband (intermediate frequency) signals based on system performance metrics. Specifically, the main task is to compensate signal fading and distortion caused by spatial loss, multipath effect and other factors in the wireless propagation process, and simultaneously reduce interference among co-channel users. Therefore, it is necessary to first build a system model to describe the signals at various places in the system, and then it is possible to express the combination or distribution of signals as a mathematical problem to find the optimal solution according to the system performance requirements. The goal of intelligent antenna beamforming is to form the best processing of the baseband signal according to the system performance index. Specifically, the main task of beamforming is to compensate for signal fading caused by spatial loss, multipath effect, etc. during wireless propagation, and simultaneously reduce co-channel interference between users. The intelligent antenna adopts a digital method to realize beam forming, so that the software design can complete the updating of the self-adaptive algorithm, and the flexibility of the system is improved on the premise of not changing the hardware configuration of the system. The beam forming algorithm carries out weighting summation processing on the array element receiving signals to form antenna beams, a beam main lobe is aligned to the direction of a desired user, and a beam side lobe or null is aligned to the interference direction. According to different processes of beam forming, the modes for realizing the intelligent antenna are divided into two modes, namely an array element space processing mode and a beam space processing mode.
1) The array element space processing mode is that after the weighted summation processing is directly carried out on each array element according to received signal sampling, array output is formed, and the main lobe of an array directional diagram is aligned with the arrival direction of a user signal. Since each array element participates in the adaptive weighting adjustment, the method belongs to the fully adaptive array processing.
2) The beam space processing mode is the development direction of the current adaptive array processing technology. The second stage performs adaptive weighting adjustment on the beam output of the first stage and then synthesizes to obtain array output. The structure has the characteristics of small calculated amount, quick convergence and good beam forming performance.
Disclosure of Invention
Aiming at the defects of the prior art, the invention discloses a multi-antenna single carrier frequency domain equalization simplification device and algorithm, which solve the problem that FPGA (field programmable gate array) resources are excessively consumed by multi-antenna single carrier frequency domain equalization of a receiver, simplify processing and realize the problem of using beam forming of large-scale MIMO (multiple input multiple output) on the single carrier frequency domain equalization.
The invention is realized by the following technical scheme:
a multi-antenna single carrier frequency domain equalization simplifying device comprises an intelligent antenna, wherein the intelligent antenna is composed of an array element, a weighting circuit and a receiving circuit; the multi-antenna beam forming processing module comprises an antenna array receiver module, an analog-to-digital converter, a digital beam former and a beam controller;
and the multi-antenna beam forming processing module carries out channel estimation according to the predicted reference signal and the received reference signal, and finally forms a network beam forming weight by a beam forming algorithm.
Furthermore, the antenna array receiver module completes frequency conversion, filtering and amplification of signals, so that the signals meet the requirements of ADC conversion;
the analog-to-digital converter realizes analog-to-digital conversion;
the digital beam former performs mathematical operation to generate beams;
the beam controller controls the beams generated by the digital beamformer.
Furthermore, after the user transmission signal is attenuated and delayed by the multipath channel, the smart antenna reaches each array element of the antenna array by the combination and superposition of all the transmission signals and their respective delayed copies, which is set as x (t), defines a weight wk for each array element, and performs array signal processing calculation, so that the beam forming output of the array weighted combination vector is:
y(t)＝ωH(t)*x(t) (1)
formula (1) is a basic model of a smart antenna forming beam signal;
where the weights wk match the slow fading of the channel.
Furthermore, in the multi-antenna beam forming processing module, an array composed of N array elements is arranged in the space and is arranged in a field composed of M far-field point sources, and the frequency of a signal source is f0The array elements are numbered from 1 to N, any one array element is selected as a reference point, and the position vectors relative to the reference point are ri(i＝1,...N；r＝0)；
Then, after the plane wave sent by the point source i reaches the array element, due to the addition of noise, the signal actually received by the array element is:
Figure BDA0003019578770000031
wherein n isi(t) is a mean of 0 and a variance of
Figure BDA0003019578770000032
White noise of (2);
assuming that the radio wave S (t) is incident from the front direction at an angle theta, and the first antenna unit is used as a reference, when no observation noise exists, the signal X received by the mth antenna unitm(t) is expressed as:
Figure BDA0003019578770000033
wherein
Figure BDA0003019578770000034
In order to be the center frequency of the signal,
Figure BDA0003019578770000035
this formula corresponds to a linear alignment, and the antenna array received signal vector is complex weighted and is expressed as:
Figure BDA0003019578770000041
the utility model provides a smart antenna algorithm of balanced simplification of many antennas single carrier frequency domain, the balanced simplification device of many antennas single carrier frequency domain uses the algorithm, the weight of each antenna array element is obtained to the algorithm self-adaptation, includes the following step:
t1 firstly obtains the estimation channel of each antenna element by reference signal;
t2 determining array element weight by using estimation channel according to criterion;
t3 finally weights the signals of each channel with a shaped vector, and transmits signals with directivity in waveform from each antenna element, thereby achieving the effect of spatial filtering.
Furthermore, a channel cyclic delay estimation algorithm is adopted for channel estimation, the matched filter is obtained through continuous sliding of the local pilot signal to obtain signal vector distribution on different time delay positions, multipath positions with larger energy are identified, and the vector distribution of the multipath positions is recorded.
Furthermore, the effect of the channel on a data block is regarded as a cyclic convolution of the entire data block, modifying the multipath channel model into one
y＝HCx+ω
And after the channel estimation signal h of each antenna is obtained, carrying out single carrier frequency domain equalization processing on each antenna.
Furthermore, in the transmission process of the channel, the equivalent channel after beam forming is obtained through the measurement of the special pilot frequency, and coherent frequency domain equalization detection is carried out;
and (3) equalizing the frequency domain receiving vector after the FFT and the CP deletion by adopting a forward linear equalizer, wherein the frequency domain receiving vector is represented by the following formula:
Figure BDA0003019578770000042
where W ═ W (0), W (1), W (N-1)]TIs the equalizer coefficient vector;
a zero-forcing equalizer:
Figure BDA0003019578770000043
MMSE equalizer:
let the variance of the noise be E (v)n 2)＝σ2Let us order
Figure BDA0003019578770000044
Is provided with
Figure BDA0003019578770000051
Wherein
Figure BDA0003019578770000052
Order to
Figure BDA0003019578770000053
Obtaining an MMSE equalizer:
Figure BDA0003019578770000054
Figure BDA0003019578770000055
thus, single carrier frequency domain equalization of each antenna is completed;
Figure BDA0003019578770000056
combining the signals after frequency domain equalization
Figure BDA0003019578770000057
Converting the result after frequency domain equalization combination into time domain to obtain
Figure BDA0003019578770000058
Namely, it is
Figure BDA0003019578770000059
Furthermore, the algorithm directly utilizes the inverse matrix of the autocorrelation matrix of the signal statistical properties according to the formula of the optimal wiener solution
Figure BDA00030195787700000510
And the cross-correlation vector gammaxyAnd obtaining the optimal weight coefficient.
The invention has the beneficial effects that:
the invention uses the weighting factor of the beam forming to complete the weighting combination of the received signals, and the signals after the weighting combination are uniformly synchronized, thereby simplifying the complexity of the parallel synchronization of the multiple antennas, better resisting the influence of noise on the synchronization after the weighting combination and ensuring more accurate synchronization. According to the unified synchronous position, each antenna takes out the pilot signal according to the position to carry out independent channel estimation, then respective frequency domain equalization is carried out, maximum ratio MRC combination is carried out after the frequency domain equalization, IFFT output time domain signals are carried out after combination instead of combination after IFFT output, therefore, IFFT processing is saved, and processing complexity is further simplified.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a received signal according to an embodiment of the present invention;
FIG. 2 is a schematic block diagram of a simplified apparatus for multi-antenna single carrier frequency domain equalization;
fig. 3 is a schematic diagram of channel estimation by sliding filtering according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment aims at the problems that the existing multi-antenna beam forming technology and multi-antenna equalization technology occupy more resources and have higher cost. How to save resources consumed by single-carrier multi-antenna beam forming without performance degradation becomes a key point of present research.
First, a signal model for array antenna signal processing is considered, and then the principle and the system structure of the adaptive antenna can be further understood.
N array elements are arranged in space to form an array, the array elements are arranged in a field formed by M far-field point sources, the frequency of a signal source is f0 and is not related to each other, the array elements are numbered from 1 to N, and any one array element is selected as a reference point (reference point). Here we do not choose array element 1 as a reference point.
Fig. 1 shows a schematic diagram of the array receiving signals. The position vectors are r with respect to the reference pointi(i-1.. N; r-0). After the plane wave emitted by the point source i reaches the array element, due to the addition of noise, the signal actually received by the array element is;
Figure BDA0003019578770000071
wherein n isi(t) is a mean of 0 and a variance of
Figure BDA0003019578770000072
White noise of (2).
Assuming that the radio wave S (t) is incident from the front direction at an angle theta, and the first antenna unit is used as a reference, when no observation noise exists, the signal X received by the mth antenna unitm(t) can be expressed as:
Figure BDA0003019578770000073
wherein
Figure BDA0003019578770000074
In order to be the center frequency of the signal,
Figure BDA0003019578770000075
the formula corresponds to a linear array, if the circular array formula is changed once. The received signal vector of the antenna array is complex weighted and can be expressed as:
Figure BDA0003019578770000076
signals received by each antenna unit of the self-adaptive antenna are subjected to complex addition of weights, the amplitude and the phase of a test signal are changed, and finally summation output is carried out. Since the received signal is a wave, the amplitude and phase of the adjustment signal are selected to synthesize the wave. And because the digital wave forming is simpler and more convenient in realization, a digital wave beam forming system can be adopted. The embodiment adopts the beam weighting forming process in advance to simplify the synchronization process as follows:
this embodiment presents a simplified multi-antenna receiving architecture as shown in fig. 2: a multi-antenna beam forming processing module: the digital beam forming device mainly comprises an antenna array receiver module, an analog-to-digital converter (ADC), a digital beam former and a beam controller.
The receiving module completes frequency conversion, filtering and amplification of the signal, so that the signal meets the requirement of ADC conversion. The ADC performs analog-to-digital conversion. The digital beamformer can perform fast mathematical operations to generate beams.
In this embodiment, as shown in the figure, a system structure based on beamforming of reference signals is firstly performed channel estimation according to a predicted reference signal and a received reference signal, and then a beamforming algorithm forms a weight of network beamforming.
The calculation efficiency of the beam forming algorithm based on the reference signal is obviously improved, but the spectrum efficiency is reduced; the algorithm does not need to know any relevant information such as the same incoming wave direction.
The intelligent antenna is a bidirectional antenna installed on an unmanned aerial vehicle, and the principle of the intelligent antenna is that a main beam of the antenna is aligned with the arrival direction of a user signal, and a side lobe or a null is aligned with the arrival direction of an interference signal, so that a directional beam is generated, and the purposes of effectively moving the user signal and deleting or inhibiting the interference moving signal are achieved.
The intelligent antenna is composed of an array element, a weighting part and a combining part to form a receiving circuit. After the user transmission signal is attenuated and delayed by multipath channel, the combined superposition of all transmission signals and their respective delayed copies is reached to each array element of the antenna array, and it is defined as x (t). If a weight wk is defined for each array element, and array signal processing calculation is performed according to signal detection requirements and a certain criterion, the beam forming output of the array weighting merging vector is as follows:
y(t)＝ωH(t)*x(t) (1)
equation (1) is a basic model for smart antenna forming beam signals. The weights wk are matched with the slow fading of the channel, such as the direction of the incoming wave DOA and the average path loss. In the TDD system, due to the reciprocity characteristic of the channel, when performing beamforming, the weight parameter can be accurately estimated according to the DOA and the path loss information of the uplink of the base station without using the CSI information fed back by the terminal. The basic principle of the intelligent antenna algorithm is that after DOA estimation is obtained from an uplink signal of an antenna array, a weight is generated for an antenna weight controller, and then the weight is fed back to the antenna array, and a shaped beam is formed by the antenna array.
The core of the intelligent antenna system is to select an efficient intelligent algorithm and obtain the weight of each antenna array element in a self-adaptive manner through the algorithm. The method comprises the steps of firstly obtaining an estimated channel of each antenna array element by means of a reference signal, then determining the weight of the array element by using the estimated channel according to some criteria, finally weighting the signal of each channel by using a forming vector, and sending the signal from each antenna array element, wherein the waveform of the sent signal has certain directivity, thereby achieving the purposes of fully utilizing an effective signal and inhibiting an interference signal and achieving the effect of spatial domain filtering.
The specific implementation flow is as follows, after each receiving antenna receives its own signal, it first carries on pre-weighting process, namely receiving shaping process, after weighting and merging the multi-channel data flow, it forms a data flow, and the signal after weighting and merging carries on synchronous process, thus it simplifies the complexity of the multi-antenna parallel synchronization, and it can better resist the influence of noise on the synchronization after weighting and merging, and makes the synchronization more accurate. After signal synchronization, the pilot signal of each antenna is taken out at the same position to perform channel estimation according to the pilot, and the channel estimation can adopt a channel cyclic delay estimation algorithm: in real time, the signal vector distribution at different time delay positions is obtained by the matched filter through continuous sliding of the local pilot signal, the multipath positions with larger energy are identified, and the vector distribution of the multipath positions is recorded.
The sliding filtering is used for channel estimation as shown in fig. 3, the measurement accuracy of the matched filter can reach 1/4-1/2 chips, and the interval of different receiving paths of the smart antenna receiver is one chip. Due to the existence of the cyclic prefix, the influence of the channel on one data block can be regarded as cyclic convolution of the whole data block, and a multipath channel model can be rewritten into
y＝HCx+ω
And after the channel estimation signal h of each antenna is obtained, single carrier frequency domain equalization processing of each antenna is started. The TRB algorithm based on training sequence matched filtering has good robustness, and is particularly suitable for the mobile communication environment with extremely unstable channel characteristics. Such algorithms can improve the signal-to-noise ratio and mitigate the effects of fading by optimal synthesis of multipath signals. In practical application, accurate synchronization is required; the best performance can be achieved with low delay spread.
The weighting factors w of the multiple antennas can be calculated according to the received channel h information. The calculation of the weighting factors is not important in this embodiment, and therefore, it is not described in detail.
In the transmission process, the unmanned aerial vehicle obtains the equivalent channel after beam forming through the measurement of the special pilot frequency, and performs coherent frequency domain equalization detection.
The frequency domain received vector after FFT and CP removal can be equalized by a simple forward linear equalizer, which can be represented by the following formula:
Figure BDA0003019578770000091
where W ═ W (0), W (1), W (N-1)]TIs the equalizer coefficient vector.
A zero-forcing equalizer:
Figure BDA0003019578770000092
MMSE equalizer:
let the variance of the noise be E (v)n 2)＝σ2Let us order
Figure BDA0003019578770000101
Is provided with
Figure BDA0003019578770000102
Wherein
Figure BDA0003019578770000103
Order to
Figure BDA0003019578770000104
Obtaining an MMSE equalizer:
Figure BDA0003019578770000105
Figure BDA0003019578770000106
thus, single carrier frequency domain equalization of each antenna is completed.
Figure BDA0003019578770000107
Combining the signals after frequency domain equalization
Figure BDA0003019578770000108
Converting the result after frequency domain equalization combination into time domain to obtain
Figure BDA0003019578770000109
Namely, it is
Figure BDA00030195787700001010
Only one IFFT process is needed at this time, saving the work of IFFT processing.
The shaping processing of the single carrier unmanned aerial vehicle is completed, and the basic principle is described as follows again: assume that there are nt transmit antennas at the transmit end. The beamforming process is as follows: at a transmitting end, one path of data flow is copied into nt paths of sub-flows in an equal power mode, and each path of sub-flow is weighted by the beam forming weight and then transmitted from the corresponding transmitting antenna. The waveform of the transmitted signal has a specific directivity, thereby achieving the effect of spatial filtering.
The DMI algorithm directly utilizes the inverse matrix of the autocorrelation matrix of the signal statistical properties according to the formula of the optimal wiener solution
Figure BDA0003019578770000111
And the cross-correlation vector gammaxyAnd obtaining the optimal weight coefficient. But due to the time-varying nature of the mobile channel
Figure BDA0003019578770000112
And gammaxyFor time-variant, constant observation and updating are required.
In the embodiment, the weighting factors of the beam forming are utilized to complete the weighting combination of the received signals, and the signals after the weighting combination are uniformly synchronized, so that the complexity of the parallel synchronization of multiple antennas is simplified, and the influence of noise on the synchronization can be better resisted after the weighting combination, so that the synchronization is more accurate. According to the unified synchronous position, each antenna takes out the pilot signal according to the position to carry out independent channel estimation, then respective frequency domain equalization is carried out, maximum ratio MRC combination is carried out after the frequency domain equalization, IFFT output time domain signals are carried out after combination instead of combination after IFFT output, therefore, IFFT processing is saved, and processing complexity is further simplified.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (9)

1. A multi-antenna single carrier frequency domain equalization simplifying device comprises an intelligent antenna, wherein the intelligent antenna is composed of an array element, a weighting circuit and a receiving circuit; the multi-antenna beam forming processing module comprises an antenna array receiver module, an analog-to-digital converter, a digital beam forming device and a beam controller;
and the multi-antenna beam forming processing module carries out channel estimation according to the predicted reference signal and the received reference signal, and finally forms a network beam forming weight by a beam forming algorithm.
2. The multi-antenna single-carrier frequency domain equalization simplification apparatus of claim 1, wherein the antenna array receiver module performs frequency conversion, filtering and amplification of signals to make the signals meet ADC conversion requirements;
the analog-to-digital converter realizes analog-to-digital conversion;
the digital beam former performs mathematical operation to generate beams;
the beam controller controls the beams generated by the digital beamformer.
3. The multi-antenna single-carrier frequency domain equalization simplification apparatus of claim 1, characterized in that, after a user transmission signal is attenuated and delayed by a multipath channel, the smart antenna reaches each array element of an antenna array by the combination superposition of all transmission signals and their respective delayed copies, which is set as x (t), a weight wk is defined for each array element, and after the array signal processing calculation, the beamforming output of the array weighted combining vector is:
y(t)＝ωH(t)*x(t) (1)
formula (1) is a basic model of a smart antenna forming beam signal;
where the weights wk match the slow fading of the channel.
4. The multi-antenna single-carrier frequency domain equalization simplification apparatus of claim 1, characterized in that in the multi-antenna beamforming processing module, there are N array elements arranged in space to form an array, and the array is placed in a field formed by M far-field point sources, and the signal source frequency is f0The array elements are numbered from 1 to N, any one array element is selected as a reference point, and the position vectors relative to the reference point are ri(i＝1,...N；r＝0)；
Then, after the plane wave sent by the point source i reaches the array element, due to the addition of noise, the signal actually received by the array element is:
Figure FDA0003019578760000021
wherein n isi(t) is a mean of 0 and a variance of
Figure FDA0003019578760000022
White noise of (2);
assuming that the radio wave S (t) is incident from the front direction at an angle theta, and the first antenna unit is used as a reference, when no observation noise exists, the signal X received by the mth antenna unitm(t) is expressed as:
Figure FDA0003019578760000023
wherein
Figure FDA0003019578760000024
In order to be the center frequency of the signal,
Figure FDA0003019578760000025
the formula corresponds to a linear array, and the antenna array receives a signal vectorComplex weighted, represented as:
Figure FDA0003019578760000026
5. an intelligent antenna algorithm for multi-antenna single carrier frequency domain equalization simplification, which is used by the multi-antenna single carrier frequency domain equalization simplification device of any claim 1 to 4, and is characterized in that the algorithm adaptively obtains the weight of each antenna array element, and the method comprises the following steps:
t1 firstly obtains the estimation channel of each antenna element by reference signal;
t2 determining array element weight by using estimation channel according to criterion;
t3 finally weights the signals of each channel with a shaped vector, and transmits signals with directivity in waveform from each antenna element, thereby achieving the effect of spatial filtering.
6. The multi-antenna single-carrier frequency domain equalization simplified smart antenna algorithm as recited in claim 5, wherein a channel cyclic delay estimation algorithm is employed for channel estimation, and through continuous sliding of local pilot signals, the matched filter is obtained to obtain signal vector distributions at different time delay positions, identify multipath positions with greater energy, and record their vector distributions.
7. The multi-antenna single-carrier frequency domain equalization simplified smart antenna algorithm as claimed in claim 5, characterized in that the effect of the channel on one data block is regarded as a cyclic convolution of the whole data block, adapting the multipath channel model to be one that is adapted to the full data block
y＝HCx+ω
And after the channel estimation signal h of each antenna is obtained, carrying out single carrier frequency domain equalization processing on each antenna.
8. The multi-antenna single carrier frequency domain equalization simplified smart antenna algorithm according to claim 5, characterized in that during the transmission of the channel, the equivalent channel after beam forming is obtained by measuring the dedicated pilot frequency, and coherent frequency domain equalization detection is performed;
and (3) equalizing the frequency domain receiving vector after the FFT and the CP deletion by adopting a forward linear equalizer, wherein the frequency domain receiving vector is represented by the following formula:
Figure FDA0003019578760000031
where W ═ W (0), W (1), W (N-1)]TIs the equalizer coefficient vector;
a zero-forcing equalizer:
Figure FDA0003019578760000032
MMSE equalizer:
let the variance of the noise be E (v)n 2)＝σ2Let us order
Figure FDA0003019578760000033
Is provided with
Figure FDA0003019578760000034
Wherein
Figure FDA0003019578760000035
Order to
Figure FDA0003019578760000036
Obtaining an MMSE equalizer:
Figure FDA0003019578760000037
Figure FDA0003019578760000038
thus, single carrier frequency domain equalization of each antenna is completed;
Figure FDA0003019578760000039
combining the signals after frequency domain equalization
Figure FDA00030195787600000310
Converting the result after frequency domain equalization combination into time domain to obtain
Figure FDA0003019578760000041
Namely, it is
Figure FDA0003019578760000042
9. The multi-antenna single-carrier frequency domain equalization simplified smart antenna algorithm as claimed in claim 5, characterized in that the algorithm directly utilizes the inverse of the autocorrelation matrix of the signal statistical properties according to the formula of the optimal wiener solution
Figure FDA0003019578760000043
And the cross-correlation vector gammaxyAnd obtaining the optimal weight coefficient.
CN202110398980.5A 2021-04-14 2021-04-14 Multi-antenna single carrier frequency domain equalization simplification device and algorithm Pending CN113206693A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110398980.5A CN113206693A (en) 2021-04-14 2021-04-14 Multi-antenna single carrier frequency domain equalization simplification device and algorithm

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110398980.5A CN113206693A (en) 2021-04-14 2021-04-14 Multi-antenna single carrier frequency domain equalization simplification device and algorithm

Publications (1)

Publication Number Publication Date
CN113206693A true CN113206693A (en) 2021-08-03

Family

ID=77026794

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110398980.5A Pending CN113206693A (en) 2021-04-14 2021-04-14 Multi-antenna single carrier frequency domain equalization simplification device and algorithm

Country Status (1)

Country Link
CN (1) CN113206693A (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110890912A (en) * 2019-06-04 2020-03-17 熊军 Beam forming method with decision feedback frequency domain equalization under multiple antennas
CN111082843A (en) * 2019-09-18 2020-04-28 熊军 Method for realizing single carrier equalization aiming at intelligent multi-antenna beam forming

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110890912A (en) * 2019-06-04 2020-03-17 熊军 Beam forming method with decision feedback frequency domain equalization under multiple antennas
CN111082843A (en) * 2019-09-18 2020-04-28 熊军 Method for realizing single carrier equalization aiming at intelligent multi-antenna beam forming

Similar Documents

Publication Publication Date Title
US7605755B2 (en) Antenna array including virtual antenna elements
JP3849881B2 (en) Antenna array transceiver algorithm
Castanheira et al. Hybrid beamforming designs for massive MIMO millimeter-wave heterogeneous systems
Cupo et al. A four-element adaptive antenna array for IS-136 PCS base stations
EP3639389B1 (en) Methods and devices for processing uplink signals
EP1276251A1 (en) Method for calculating a weighting vector for an antenna array
CN111512571B (en) Method and apparatus for signal detection in a MIMO communication system
JP2009153139A (en) Pre-coding processing method and apparatus for mimo downlink, and base station
WO2013056393A1 (en) Radio receiver for polarized antenna system
US8724754B2 (en) Noise power thresholding and balancing for long term evolution (LTE) symbol detection
CN107733487B (en) Signal detection method and device for large-scale multi-input multi-output system
Bento et al. Frequency-domain detection without matrix inversions for mmWave communications with correlated massive MIMO channels
CN105375967A (en) Enhanced maximal ratio combining (MRC) detection method and receiver based on statistical method
CN113206693A (en) Multi-antenna single carrier frequency domain equalization simplification device and algorithm
CN104539401A (en) Self-adaption precoding method, base station and system
CN113395098B (en) Method and device for multi-antenna signal combination and transmitting signal shaping
Anughna et al. Performance Analysis on various Diversity Schemes with Channel Equalization and Estimation Techniques in MIMO OFDM system
Reddy et al. A Comprehensive Survey on mm Wave Systems with Beamforming Effects in Antenna for 5G Applications
Mumtaz et al. Adaptive beamforming for OFDMA using positioning information
CN102201890B (en) Data transmitting method and device
Rao et al. Channel Estimation for mmWave MIMO using Deep Residual Learning
Bhavana et al. Efficient Beamforming Techniques in MU-MIMO
Likhitkar et al. Beam-forming for MIMO-OFDM Wireless Systems
Ogawa et al. Basestation adaptive antennas for a high-speed FDD/TDMA system
Paulin et al. Linear precoder optimization of spectral efficiency of time division duplex hyper MIMO system with pilot contamination

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination