CN118473873B - A low-complexity method for estimating packing rate of super-Nyquist systems - Google Patents
A low-complexity method for estimating packing rate of super-Nyquist systems Download PDFInfo
- Publication number
- CN118473873B CN118473873B CN202410393818.8A CN202410393818A CN118473873B CN 118473873 B CN118473873 B CN 118473873B CN 202410393818 A CN202410393818 A CN 202410393818A CN 118473873 B CN118473873 B CN 118473873B
- Authority
- CN
- China
- Prior art keywords
- transmission
- symbol
- transmission frame
- downsampling
- assumed
- 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.)
- Active
Links
- 238000012856 packing Methods 0.000 title claims abstract description 62
- 238000000034 method Methods 0.000 title claims abstract description 44
- 230000005540 biological transmission Effects 0.000 claims abstract description 140
- 230000008569 process Effects 0.000 claims abstract description 24
- 238000001914 filtration Methods 0.000 claims abstract description 12
- 238000005070 sampling Methods 0.000 claims description 16
- 230000001427 coherent effect Effects 0.000 claims description 10
- 230000004044 response Effects 0.000 claims description 8
- 238000013507 mapping Methods 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 5
- 238000010276 construction Methods 0.000 claims description 3
- 238000004088 simulation Methods 0.000 description 11
- 238000007493 shaping process Methods 0.000 description 10
- 238000004891 communication Methods 0.000 description 8
- 238000001514 detection method Methods 0.000 description 7
- 238000004422 calculation algorithm Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 238000012546 transfer Methods 0.000 description 6
- 238000009432 framing Methods 0.000 description 5
- 239000000654 additive Substances 0.000 description 3
- 230000000996 additive effect Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000005562 fading Methods 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 230000011664 signaling Effects 0.000 description 3
- 241000583281 Sugiura Species 0.000 description 2
- 125000004122 cyclic group Chemical group 0.000 description 2
- 238000000354 decomposition reaction Methods 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
- 238000012804 iterative process Methods 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000036962 time dependent Effects 0.000 description 1
Classifications
-
- 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
-
- 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
- H04L25/03178—Arrangements involving sequence estimation techniques
-
- 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
- H04L25/03343—Arrangements at the transmitter end
-
- 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
- H04L25/03828—Arrangements for spectral shaping; Arrangements for providing signals with specified spectral properties
- H04L25/03834—Arrangements for spectral shaping; Arrangements for providing signals with specified spectral properties using pulse shaping
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Detection And Prevention Of Errors In Transmission (AREA)
Abstract
本发明公开了一种低复杂度超奈奎斯特系统打包率估计方法，包括：基于传输导频块及映射后的符号构造传输帧；基于传输帧生成发射信号；对发射信号进行加噪及滤波，生成接收信号；获取初始的假定下采样因子，对初始的假定下采样因子进行迭代更新，基于迭代更新过程中的每个假定下采样因子，分别对接收信号进行下采样，得到下采样后的导频块，并对下采样后的导频块及传输导频块进行相干相关处理，得到每个假定下采样因子对应的判决值；提取最大的判决值对应的假定下采样因子，根据提取的假定下采样因子，生成超奈奎斯特系统的打包率。通过上述技术方案，本发明可以估计随机的超奈奎斯特系统打包率，并且实现复杂度低。
The present invention discloses a low-complexity super-Nyquist system packing rate estimation method, including: constructing a transmission frame based on a transmission pilot block and a mapped symbol; generating a transmission signal based on the transmission frame; adding noise and filtering the transmission signal to generate a received signal; obtaining an initial assumed downsampling factor, iteratively updating the initial assumed downsampling factor, downsampling the received signal based on each assumed downsampling factor in the iterative update process, obtaining a downsampled pilot block, and coherently correlating the downsampled pilot block and the transmission pilot block to obtain a decision value corresponding to each assumed downsampling factor; extracting the assumed downsampling factor corresponding to the maximum decision value, and generating the packing rate of the super-Nyquist system according to the extracted assumed downsampling factor. Through the above technical solution, the present invention can estimate the packing rate of a random super-Nyquist system, and achieve low complexity.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a low-complexity super Nyquist system packing rate estimation method.
Background
With the urgent need for high-rate, high-quality communication services, communication systems with higher spectral efficiency and large capacity are becoming urgent. Therefore, the super nyquist system, as a physical layer technology, can improve capacity and spectrum efficiency without requiring additional bandwidth and antennas, thereby gaining attention in the field of communication. However, the nyquist criterion is violated, so that the super-nyquist system introduces intersymbol interference. This naturally led to a study of both aspects of the super nyquist system.
On the one hand, the signal detection algorithm is a necessary means for ensuring the reliability of the super Nyquist system. The signal detection algorithm in the super Nyquist system mainly comprises Bahl-Cocke-Jerinek-Raviv (BCJR), iterative interference cancellation, equalization and precoding. By inserting a cyclic suffix into each transmitted symbol block, shinya Sugiura converts an intersymbol interference matrix caused by the super nyquist system into a cyclic matrix, and a frequency domain equalization algorithm is proposed. The pre-coding algorithm pre-processes the mapped symbols by using intersymbol interference matrix decomposition, and performs corresponding decoding at the receiving end to recover the transmitted symbols. All signal detection algorithms for the super nyquist system, except the time domain equalization algorithm, assume that the packing rate is precisely known at the receiver and transmitter by a control frame or preset method.
On the other hand, intersymbol interference caused by the super nyquist is regarded as artificial noise, and physical layer security is realized by using the super nyquist system. The university of adult electronics Wang Jianquan in its published paper "Filter Hopping Based Faster-Than-Nyquist Signaling for Physical Layer Security"(IEEE Wireless Communications Letters,2018,894-897) considers the time-dependent change of the pulse shaping filter in the transmitter in the super nyquist system. The filter hopping pattern is pre-shared between the transmitter and the legitimate receiver. On this basis, the university of adult electronics Yuan Li proposes a variable packing rate based super nyquist system scheme for physical layer security in its published paper "AVariable Symbol Duration Based FTN Signaling Scheme for PLS"(International Conferenceon Wireless Communications and Signal Processing,2019,1-5), in which the information rates of the cooperative and non-cooperative links are derived. Furthermore, shinya Sugiura in its published paper "Secrecy performance of eigendecomposition-based super nyquist signaling and NOFDM in Quasi-static fading channels"(IEEE Transactions on Wireless Communications,2021,5872-5882) proposes to extend the privacy rate and privacy break probability of a fading eavesdropping channel to a feature decomposition-based super nyquist of a quasi-static frequency flat rayleigh fading channel. These studies are based on the assumption that the packing-rate pattern between the receiver and the transmitter has been determined or synchronized when the super nyquist system is established.
As described above, it can be concluded that for most studies of the nyquist, an accurate packing rate is necessary, otherwise it is difficult to achieve signal detection and physical layer security. Based on deep learning, the university of western electronics Song Peiyang presents a blind packing rate estimation for the super nyquist system in its published paper "For security and higher spectrum efficiency:A variable packing ratio transmission system based on Faster-Than-Nyquist and deep learning"(IEEE Transactions on Wireless Communications,2023,5898-5913). However, its high complexity makes it unsuitable for the super nyquist system. Therefore, there is a need for a low complexity packing rate estimation method for the super nyquist system.
Disclosure of Invention
In order to solve the above-mentioned problems of the prior art, an object of the present invention is to provide a low-complexity method for estimating the packing rate of a super nyquist system, so as to estimate the packing rate of a random super nyquist system and reduce the implementation complexity.
In order to achieve the above object, the present invention provides a low complexity super nyquist system packing rate estimation method, including:
The method comprises the steps of obtaining a transmission pilot frequency block and mapped symbols in a super Nyquist system, constructing a transmission frame based on the transmission pilot frequency block and mapped symbols, up-sampling the transmission frame and forming a baseband to generate a transmission signal, and carrying out noise adding and filtering on the transmission signal to generate a receiving signal;
Acquiring an initial assumed downsampling factor, carrying out iterative updating on the initial assumed downsampling factor, respectively carrying out downsampling on a received signal based on each assumed downsampling factor in the iterative updating process to obtain a downsampled pilot block, and carrying out coherent correlation processing on the downsampled pilot block and a transmission pilot block until the assumed downsampling factor updated last time is larger than an upsampling parameter in the upsampling process to obtain a judgment value corresponding to each assumed downsampling factor;
and extracting an assumed downsampling factor corresponding to the maximum decision value, and generating the packing rate of the super Nyquist system according to the extracted assumed downsampling factor.
Optionally, the construction process of the transmission frame includes:
wherein b k denotes the kth transmission frame, b n denotes the nth symbol in the corresponding transmission frame, p is the transmission pilot block, p= [ p 0,p1,p2,…,pL-1 ], L denotes the length of the transmission pilot block, Representing the length of the mapped symbol, a n is the mapped nth symbol.
Optionally, the generating process of the transmission signal includes:
Where s (T) represents a transmission signal, E s is an average power of a signal in a transmission frame, N is a symbol length in the transmission frame, b n represents an nth symbol in a corresponding transmission frame, N is a reference number of the transmission frame, c (T) is a root-raised cosine shaped pulse of unit energy corresponding to time T, and T is a symbol period of the root-raised cosine shaped pulse.
Optionally, the generating process of the received signal includes:
Where r k represents the kth received symbol in the received signal, g (T) represents the impulse response of the nyquist system transfer function corresponding to time T, E s is the average power of the signal in the transmission frame, N is the symbol length in the transmission frame, b n represents the nth symbol in the corresponding transmission frame, N is the label of the transmission frame, M represents the up-sampling multiple of the nyquist system, T is the symbol period of the root-raised cosine shaped pulse, Q is the up-sampling parameter of the root-raised cosine shaped pulse, and η k is the colored noise.
Optionally, the process of downsampling the received signal includes:
Where y k represents the kth downsampled symbol, g (T) represents the impulse response of the nyquist system transfer function corresponding to time T, E s is the average power of the signal in the transmission frame, N is the symbol length in the transmission frame, b n represents the nth symbol in the corresponding transmission frame, N is the label of the transmission frame, M represents the upsampling multiple of the nyquist system, T is the symbol period of the root-raised cosine shaped pulse, Q is the upsampling parameter of the root-raised cosine shaped pulse, The representation assumes that the downsampling factor is, Is the colored noise after downsampling.
Optionally, the process of performing coherent correlation processing on the pilot block after downsampling and the transmission pilot block includes:
Wherein, The i symbol of the kth pilot block after downsampling is represented, p i is the i symbol of the transmission pilot block, L represents the length of the transmission pilot block, and i represents the symbol index in the transmission pilot block.
Optionally, the generating process of the packing rate of the super nyquist system includes:
where τ is the packing fraction, Q is the upsampling parameter of the root-raised cosine shaped pulse, Is the hypothesized downsampling factor corresponding to the maximum decision value.
Compared with the prior art, the invention has the following advantages and technical effects:
The invention provides a low-complexity super Nyquist system packing rate estimation method by using a pilot frequency-based super Nyquist transmission model, which can convert the packing rate estimation problem into a downsampling factor estimation problem. And the method comprises the steps of carrying out downsampling on the signals after matched filtering by using different assumed downsampling factors, so as to obtain a downsampled pilot block corresponding to each assumed downsampling factor, carrying out coherent correlation operation on the transmission pilot block and the downsampled pilot block, obtaining a judgment value corresponding to the assumed downsampling factors, finding out the assumed downsampling factor corresponding to the maximum judgment value, calculating the packing rate of the corresponding super Nyquist system, and adopting the corresponding packing rate to design a transmission scheme of the corresponding random super Nyquist system, thereby ensuring safe and reliable implementation of signal detection and physical layer and low implementation complexity.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:
Fig. 1 is a diagram of a pilot-based super nyquist transmission system of the present invention;
FIG. 2 is a framing process of the super Nyquist system;
FIG. 3 is a flow chart of an implementation of the low complexity super Nyquist system packing rate estimation method of the present invention;
FIG. 4 is a diagram of simulation results of the invention for packet rate estimation as the packet rate slowly varies;
Fig. 5 is a diagram of simulation results of the packing rate estimation performed when the packing rate is randomly and uniformly distributed in the present invention.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
In order to solve the above-mentioned problems in the prior art, an object of the present invention is to provide a low-complexity super nyquist system packing rate estimation method, so as to estimate a random super nyquist system packing rate and reduce implementation complexity.
The invention provides a method for estimating the packing rate of a low-complexity super Nyquist system, which comprises the steps of framing mapped symbols, constructing a transmission frame of the super Nyquist based on pilot frequency, using the super Nyquist transmission model to convert the packing rate estimation problem into a downsampling factor estimation problem, carrying out upsampling and baseband forming on the transmission frame to obtain a transmission signal, carrying out additive Gaussian white noise channel and matched filtering on the transmission signal to describe the transmission process of the transmission signal to obtain a receiving signal, carrying out downsampling on the matched and filtered receiving signal by using different postulated downsampling factors to generate downsampled symbols, extracting the acquired pilot frequency blocks from the downsampled symbols, carrying out coherent correlation operation on the transmission pilot frequency blocks and the downsampled pilot frequency blocks to obtain judgment values corresponding to different postulated downsampling factors, finding the postulated downsampling factors corresponding to the maximum judgment values, and calculating the packing rate of the super Nyquist system according to the found postulated downsampling factors to obtain the estimated packing rate.
As some embodiments, the constructing of the k-th transmission frame based on the pilot frequency comprises constructing the transmission frame based on the transmission pilot frequency block and the mapped symbol:
wherein b k denotes the kth transmission frame, k is the corresponding reference number of the transmission frame, b n denotes the nth symbol in the corresponding transmission frame, p= [ p 0,p1,p2,…,pL-1 ] is the transmission pilot block, L denotes the length of the transmission pilot block, Representing the mapped symbol block length, a n is the mapped nth symbol.
As some embodiments, up-sampling and baseband shaping are performed on the transmission frame and transmitting, and a transmission signal is obtained:
Where s (T) represents a transmission signal, E s is an average power of a transmission frame signal, N is a symbol corresponding to a symbol in the transmission frame, N is a length of the symbol in the transmission frame, c (T) is a root-raised cosine shaped pulse of unit energy corresponding to time T, and T is a symbol period of the root-raised cosine shaped pulse.
As some embodiments, the transmitted signal is subjected to an additive white gaussian noise channel and matched filtering to obtain a received signal:
Where r k represents the kth received symbol in the received signal, g (T) represents the impulse response of the nyquist system transfer function corresponding to time T, E s is the average power of the signal in the transmission frame, N is the symbol length in the transmission frame, b n represents the nth symbol in the corresponding transmission frame, N is the label of the transmission frame, M represents the up-sampling multiple of the nyquist system, T is the symbol period of the root-raised cosine shaped pulse, Q is the up-sampling parameter of the root-raised cosine shaped pulse, and η k is the colored noise.
The specific acquisition process of the received signal is as follows:
wherein r (t) represents the received signal, Representing a linear convolution of the data,Representing the impulse response of the super Nyquist system transfer function corresponding to time t, n (t) representing white noiseRepresenting the matched filtered colored noise.
When the assumed downsampling factor is not greater than Q, i.eDownsampling the received signal using a hypothetical downsampling factor to obtain downsampled symbols:
Where y k represents the kth downsampled symbol, M represents the upsampling multiple of the Nyquist system, Q is the upsampling parameter of the root-raised cosine shaped pulse, Representing an assumed downsampling factor, which takes a value not greater than the upsampling parameter Q of the root-raised cosine shaped pulse,Is the colored noise after downsampling.
Extracting pilot blocks from the corresponding positions in the downsampled symbols to obtain downsampled pilot blocks
Performing coherent correlation operation on the transmission pilot block and the pilot block after downsampling to obtain a decision value corresponding to the assumed downsampling factor:
where Λ represents the decision value corresponding to the hypothesized downsampling factor, Representing the ith symbol of the kth pilot block after downsampling, p i is the ith symbol of the transmission pilot block.
And in a certain range, the numerical value of the hypothesized downsampling factor is continuously adjusted through iterative updating, the operations of downsampling the matched and filtered received signal, acquiring a downsampled pilot block and related operations are sequentially iterated based on each hypothesized downsampling factor adjusted in the iterative updating process, and the generated judgment value in the iterative process is stored until the hypothesized downsampling factor is larger than the upsampling parameter of the root raised cosine shaping pulse, and the iteration is stopped.
As some embodiments, among the stored decision values corresponding to different assumed downsampling factors, finding the assumed downsampling factor corresponding to the maximum decision value, and calculating the packing rate τ of the ultranyquist system:
Wherein, Is the hypothesized downsampling factor corresponding to the maximum decision value.
The invention discloses the technical effects that a pilot frequency-based super Nyquist transmission model is used, and the invention provides a low-complexity super Nyquist system packing rate estimation method which can convert the packing rate estimation problem into a downsampling factor estimation problem. And carrying out downsampling on the signals after matching and filtering by using different assumed downsampling factors, so as to obtain a downsampled pilot block corresponding to each assumed downsampling factor, then carrying out coherent correlation operation on the transmission pilot block and the downsampled pilot block, obtaining a judgment value corresponding to the assumed downsampling factor, finding out the assumed downsampling factor corresponding to the maximum judgment value, thus calculating the packing rate of the super Nyquist system, ensuring safe and reliable implementation of signal detection and physical layer, and having low implementation complexity.
The foregoing is described in detail with reference to the accompanying drawings:
the invention aims to overcome the defects of the prior art, and provides a low-complexity method for estimating the packing rate of a super Nyquist system, so as to obtain the packing rate of the super Nyquist and reduce the implementation complexity.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
The pilot-based super nyquist transmission system adopted by the invention with reference to fig. 1-2 mainly comprises a data source module, a constellation mapping module, a framing module, an up-sampling module, a baseband shaping module, a channel module, a matched filtering module and a packing rate estimation module, wherein:
The data source module is used for generating bit data required to be transmitted by the super Nyquist system and transmitting the bit data to the constellation mapping module;
The constellation mapping module maps the bit data into symbols according to constellation mapping rules and transmits the mapped symbols to the framing module;
The framing module is used for inserting a known transmission pilot frequency block into each mapped symbol block, forming a transmission frame so as to construct the transmission frame based on the transmission pilot frequency block and the mapped symbols, and transmitting the transmission frame to the up-sampling module;
the up-sampling module performs zero value interpolation on the transmission frame to perform up-sampling on the transmission frame and transmits the transmission frame subjected to zero value interpolation to the baseband shaping module;
The baseband forming module is used for performing super Nyquist forming on the up-sampled transmission frame to perform baseband forming on the transmission frame, transmitting the transmission frame after the baseband forming, namely a transmission signal, and transmitting the transmission frame to the channel module;
The channel module is used for adding Gaussian white noise to the transmission frame after the baseband shaping and transmitting the transmission frame after the Gaussian white noise addition to the matched filtering module;
The matched filtering module carries out matched filtering on a received signal which is a transmission frame added with Gaussian white noise, and transmits the filtered received signal to the packing rate estimation module;
And the packing rate estimation module is used for downsampling the filtered received signals by using different assumed downsampling factors to obtain a downsampled pilot block, performing coherent correlation operation on the transmission pilot block and the downsampled pilot block to obtain a judgment value corresponding to the assumed downsampling factors, sequentially iterating the downsampling operation and the correlation operation, finding the assumed downsampling factor corresponding to the maximum judgment value, and calculating the packing rate of the super Nyquist system.
Referring to fig. 3, the steps of the present invention for packet rate estimation using the above-mentioned nyquist system are as follows:
step 1, the construction of the k transmission frame of the super nyquist based on the pilot frequency comprises the steps of transmitting a pilot frequency block and mapped symbols:
wherein b k denotes the kth transmission frame, k is the corresponding reference number of the transmission frame, b n denotes the nth symbol in the corresponding transmission frame, p= [ p 0,p1,p2,…,pL-1 ] is the transmission pilot block, L denotes the length of the transmission pilot block, Representing the mapped symbol block length, a n is the mapped nth symbol.
Step 2, up-sampling and baseband shaping are carried out on the transmission frame, and transmitting signals are obtained:
Where s (T) represents a transmission signal, E s is an average power of a transmission frame signal, N is a symbol corresponding to a symbol in the transmission frame, N is a length of the symbol in the transmission frame, c (T) is a root-raised cosine shaped pulse of unit energy corresponding to time T, and T is a symbol period of the root-raised cosine shaped pulse.
Step 3, the transmitting signal is subjected to an additive Gaussian white noise channel and matched filtering to obtain a receiving signal:
Where r k represents the kth received symbol in the received signal, g (T) represents the impulse response of the nyquist system transfer function corresponding to time T, E s is the average power of the signal in the transmission frame, N is the symbol length in the transmission frame, b n represents the nth symbol in the corresponding transmission frame, N is the label of the transmission frame, M represents the up-sampling multiple of the nyquist system, T is the symbol period of the root-raised cosine shaped pulse, Q is the up-sampling parameter of the root-raised cosine shaped pulse, and η k is the colored noise.
The specific acquisition process of the received signal is as follows:
wherein r (t) represents the received signal, Representing a linear convolution of the data,Representing the impulse response of the super nyquist system transfer function corresponding to time t, n (t) represents white noise,Representing the matched filtered colored noise. When the assumed downsampling factor is not greater than Q, downsampling the matched filtered received signal using the assumed downsampling factor to obtain downsampled symbols:
Where y k represents the kth downsampled symbol, M represents the upsampling multiple of the Nyquist system, Q is the upsampling parameter of the root-raised cosine shaped pulse, Representing an assumed downsampling factor, which takes a value not greater than the upsampling parameter Q of the root-raised cosine shaped pulse,Is the colored noise after downsampling.
Extracting pilot blocks from the corresponding positions in the downsampled symbols to obtain downsampled pilot blocks
Performing coherent correlation operation on the transmission pilot block and the pilot block after downsampling to obtain a decision value corresponding to the assumed downsampling factor:
where Λ represents the decision value corresponding to the hypothesized downsampling factor, Representing the ith symbol of the kth pilot block after downsampling, p i is the ith symbol of the transmission pilot block.
And in a certain range, the numerical value of the hypothesized downsampling factor is continuously adjusted through iterative updating, the operations of downsampling the matched and filtered received signal, acquiring the downsampled pilot block and related operations are sequentially iterated based on each adjusted hypothesized downsampling factor in the iterative updating process, and the generated judgment value in the iterative process is stored until the hypothesized downsampling factor is larger than the upsampling parameter of the root raised cosine shaping pulse, and the iteration is stopped.
It should be noted that, the above-mentioned transmission signal, the received signal and the symbol after downsampling are all simulation signal models for signal transmission, where the simulation signal model corresponding to the symbol after downsampling only includes "assumed downsampling factor" as a variable, under the condition of parameter determination of the nyquist system and transmission frame determination, different assumed downsampling factors can generate the symbol after downsampling correspondingly, where the value of the assumed downsampling factor obtained by each iteration is substituted into the calculation formula of the symbol after downsampling, so as to extract the pilot block after downsampling, further calculate the decision value through correlation operation, obtain several groups of different downsampling factors through several groups of iterations, further obtain several groups of different decision values, select the maximum decision value from them, and finally calculate the packing rate by using the downsampling factor corresponding to the maximum decision value.
In the iterative updating process of the assumed downsampling factor, the numerical value of the assumed downsampling factor of the previous iteration is increased by a fixed step length to perform iterative updating, wherein the initial value and the fixed step length of the initial assumed downsampling factor are set according to the upsampling parameters of the root raised cosine shaping pulse, the initial value of the downsampling factor is smaller than the upsampling parameters of the root raised cosine shaping pulse, and the fixed step length is 1.
Step 4, finding an assumed downsampling factor corresponding to the maximum decision value, and calculating the packing rate tau of the super Nyquist system:
Wherein, Is the hypothesized downsampling factor corresponding to the maximum decision value.
In this embodiment, the effect of this embodiment is further described in connection with a simulation experiment;
1. simulation conditions
The simulation experiments of this example were performed under MATLAB2022B software. In the simulation experiment of this embodiment, BPSK is used as the modulation scheme of the pilot block, and the length of a single pilot block is 32.
The roll-off factor of the root-raised cosine shaped pulse and the matched filter is set to 0.3.
2. Simulation content and result analysis
Simulation 1, under the above conditions, when the slow change of the packing rate is considered, the packing rate is estimated by the present invention, and the result is shown in fig. 4.
Simulation 2, under the above conditions, when the packing rate is considered to be randomly and uniformly distributed in [0.6,0.7,0.8,0.9,1], the packing rate is estimated by using the method, and the result is shown in fig. 5.
The horizontal axis in fig. 4 and 5 represents the bit signal-to-noise ratio of the nyquist system in dB (decibel) and the vertical axis represents the false alarm probability PFA (ProbabilityofFalseAlarm).
As can be seen from fig. 4, when the slow change of the packing rate is considered, the invention has the highest estimation accuracy for the packing rate of 1 at a low bit signal-to-noise ratio, and has the highest estimation accuracy for the packing rate of 0.8 as the bit signal-to-noise ratio increases, and has the lowest estimation accuracy for the packing rate of 0.6 regardless of the bit signal-to-noise ratio. As can be seen from fig. 5, under the same bit signal-to-noise ratio, the false alarm probability when the packing rate is randomly and uniformly distributed is higher than the false alarm probability when the packing rate is slowly changed, and the estimation accuracy is reduced compared with the case when the packing rate is slowly changed. The method can estimate the packing rate of the random super Nyquist system, and ensure the safe and reliable implementation of signal detection and physical layer.
The present application is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present application are intended to be included in the scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.
Claims (1)
1. A method for low complexity super nyquist system packing rate estimation, comprising:
the method comprises the steps of obtaining a transmission pilot frequency and a mapped symbol in a super Nyquist system, constructing a transmission frame based on the transmission pilot frequency and the mapped symbol, up-sampling the transmission frame and forming a baseband to generate a transmission signal, and carrying out noise adding and filtering on the transmission signal to generate a receiving signal;
Acquiring an initial assumed downsampling factor, carrying out iterative updating on the initial assumed downsampling factor, respectively carrying out downsampling on a received signal based on each assumed downsampling factor in the iterative updating process to obtain a downsampled pilot frequency, and carrying out coherent correlation processing on the downsampled pilot frequency and a transmission pilot frequency until the assumed downsampling factor updated last time is larger than an upsampling parameter in the upsampling process to obtain a judgment value corresponding to each assumed downsampling factor;
Extracting an assumed downsampling factor corresponding to the maximum judgment value, and generating the packing rate of the super Nyquist system according to the extracted assumed downsampling factor;
The construction process of the transmission frame comprises the following steps:
Wherein b k denotes the kth transmission frame, b n denotes the nth symbol in the corresponding transmission frame, p is the transmission pilot, p= [ p 0,p1,p2,…,pL-1 ], L denotes the length of the transmission pilot, A n represents the length of the mapped symbol, and a is the n-th symbol after mapping;
the generation process of the transmission signal comprises the following steps:
Where s (T) represents a transmission signal, τ is a packing rate, E s is an average power of a signal in a transmission frame, N is a symbol length in the transmission frame, b n represents an nth symbol in a corresponding transmission frame, N is a reference number of the transmission frame, c (T) is a root raised cosine shaped pulse of unit energy corresponding to time T, and T is a symbol period of the root raised cosine shaped pulse;
The generation process of the received signal comprises the following steps:
wherein r k represents a kth received symbol, g (T) represents an impulse response of a transmission function of the ultranyquist system corresponding to time T, τ is a packing rate, E s is an average power of a signal in a transmission frame, N is a symbol length in the transmission frame, b n represents an nth symbol in the corresponding transmission frame, N is a reference number of the transmission frame, M represents an up-sampling multiple of the ultranyquist system, T is a symbol period of a root-raised cosine shaped pulse, Q is an up-sampling parameter of the root-raised cosine shaped pulse, and η k is colored noise;
The process of downsampling the received signal includes:
Wherein y k represents a kth downsampled symbol, g (T) represents an impulse response of a transmission function of the ultranyquist system corresponding to time T, τ is a packing rate, E s is an average power of a signal in a transmission frame, N is a symbol length in the transmission frame, b n represents an nth symbol in the corresponding transmission frame, N is a reference number of the transmission frame, M represents an upsampling multiple of the ultranyquist system, T is a symbol period of the root-raised cosine shaped pulse, Q is an upsampling parameter of the root-raised cosine shaped pulse, The representation assumes that the downsampling factor is,For colored noise after the downsampling,
The process of carrying out coherent correlation processing on the pilot frequency after downsampling and the transmission pilot frequency comprises the following steps:
Wherein, The ith symbol of the kth pilot frequency after downsampling is represented, p i is the ith symbol of the transmission pilot frequency, L represents the length of the transmission pilot frequency, and i represents the symbol mark in the transmission pilot frequency;
The generation process of the packing rate of the super Nyquist system comprises the following steps:
where τ is the packing fraction, Q is the upsampling parameter of the root-raised cosine shaped pulse, Is the hypothesized downsampling factor corresponding to the maximum decision value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410393818.8A CN118473873B (en) | 2024-04-02 | 2024-04-02 | A low-complexity method for estimating packing rate of super-Nyquist systems |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410393818.8A CN118473873B (en) | 2024-04-02 | 2024-04-02 | A low-complexity method for estimating packing rate of super-Nyquist systems |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118473873A CN118473873A (en) | 2024-08-09 |
| CN118473873B true CN118473873B (en) | 2024-12-27 |
Family
ID=92170018
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410393818.8A Active CN118473873B (en) | 2024-04-02 | 2024-04-02 | A low-complexity method for estimating packing rate of super-Nyquist systems |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118473873B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105933255A (en) * | 2016-04-01 | 2016-09-07 | 中国人民解放军理工大学 | Low-complexity super-Nyquist transmission method |
| KR101759021B1 (en) * | 2016-02-29 | 2017-07-17 | 연세대학교 산학협력단 | Device and Method for Eliminating Interference in FTN Communication System |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014091271A1 (en) * | 2012-12-10 | 2014-06-19 | Agence Spatiale Europeenne | Data detection method and data detector for signals transmitted over a communication channel with inter-symbol interference |
| US9838230B2 (en) * | 2013-12-09 | 2017-12-05 | Telefonaktiebolaget Lm Ericsson (Publ) | Pre-coding in a faster-than-Nyquist transmission system |
-
2024
- 2024-04-02 CN CN202410393818.8A patent/CN118473873B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101759021B1 (en) * | 2016-02-29 | 2017-07-17 | 연세대학교 산학협력단 | Device and Method for Eliminating Interference in FTN Communication System |
| CN105933255A (en) * | 2016-04-01 | 2016-09-07 | 中国人民解放军理工大学 | Low-complexity super-Nyquist transmission method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118473873A (en) | 2024-08-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109617847B (en) | OFDM receiving method without cyclic prefix based on model-driven deep learning | |
| CN110149287B (en) | A Super-Nyquist System Based on Linear Precoding and Its Symbol Estimation Method | |
| CN113381951B (en) | MFTN Joint Channel Estimation and Equalization Method in Time-variable Frequency Selective Fading Channel | |
| CN105814855A (en) | Pre-coding in a faster-than-Nyquist transmission system | |
| CN111431832B (en) | Signal modulation method and system based on multi-dimensional OFDM and MIMO communication system | |
| CN101242388A (en) | Channel Estimation Method for High Speed Single Carrier Frequency Domain Equalized UWB System | |
| CN106899376B (en) | Non-coherent detection method for physical layer network coding continuous phase modulation signal | |
| CN110311876A (en) | Implementation method of underwater acoustic orthogonal frequency division multiplexing receiver based on deep neural network | |
| CN116633734B (en) | SVD precoding method of super Nyquist system suitable for high-order modulation | |
| Shen et al. | Chip rate and pseudo‐noise sequence estimation for direct sequence spread spectrum signals | |
| CN108123724B (en) | Communication system based on short wave narrow-band waveform | |
| US10237096B2 (en) | Processing of a faster-than-Nyquist signaling reception signal | |
| CN118473873B (en) | A low-complexity method for estimating packing rate of super-Nyquist systems | |
| CN114124168A (en) | A MIMO-NOMA system signal detection method and system based on deep learning | |
| CN118300936B (en) | Robust and high-precision packing rate estimation method for super Nyquist system | |
| CN118300937B (en) | Method for estimating packing rate of super Nyquist system capable of resisting frequency offset and phase noise | |
| CN116668246B (en) | A frequency domain equalization method for super-Nyquist systems without cyclic prefix | |
| CN117040982B (en) | A method for generating signals and directly estimating signal bit error rate based on shaping filter | |
| CN116708096B (en) | GTMH precoding method for super-Nyquist system without prefix and suffix | |
| CN116633733B (en) | GMD precoding method of super Nyquist system based on cyclic convolution | |
| CN109639301B (en) | A FTN Equalization Method Based on Confidence Estimation | |
| Yang et al. | Joint multiple turbo equalization for harsh time-varying underwater acoustic channels | |
| Xia et al. | Deep Learning Based Signal Detection for Hybrid Modulated Faster-than-Nyquist Optical Wireless Communications | |
| CN109743271B (en) | Symbol estimation method of super-Nyquist system based on iterative interference cancellation | |
| Li et al. | Robust Semi-Blind Packing Ratio Estimation for Faster-Than-Nyquist Signaling |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |