CN112702288B - Underwater sound OFDM communication system channel estimation method with low pilot frequency overhead - Google Patents
Underwater sound OFDM communication system channel estimation method with low pilot frequency overhead Download PDFInfo
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Abstract
The invention discloses a channel estimation method of an underwater sound OFDM communication system with low pilot frequency overhead, which comprises the following steps: s1, calculating channel state information at the preset pilot frequency position at the current moment; s2, pre-estimating a channel state matrix according to the obtained channel state information at the pilot frequency position to obtain a pre-estimated channel state matrix; s3, inputting the pre-estimated channel state matrix into the pre-trained channel estimation model to obtain the channel state matrix at the current moment; wherein the channel estimation model comprises a super-resolution model. The problem that the channel state information of part of preset pilot frequency positions estimates the channel state of unknown data positions is equivalent to a matrix completion problem, a super-resolution model is constructed and trained to serve as a channel estimation model to further accurately estimate a pre-estimated channel state matrix, the matrix of the channel state can be accurately estimated without increasing the number of pilot frequencies, and accurate channel estimation can be achieved with less pilot frequency overhead.
Description
Technical Field
The invention belongs to the technical field of underwater sound wireless communication, and particularly relates to a channel estimation method of an underwater sound OFDM communication system with low pilot frequency overhead.
Background
The ocean contains abundant mineral and biological resources, and is an important strategic space for the sustainable development of human society. With the exponential growth of underwater nodes to be communicated, higher requirements are put forward on the reliability and effectiveness of underwater communication. The underwater sound is the only reliable medium-long distance underwater communication technology by observing the current mainstream underwater communication transmission media such as electromagnetic waves, sound waves, light waves and the like. However, the underwater acoustic channel is harsh and complex, and the underwater acoustic communication faces severe challenges such as severe multipath effect and narrow usable bandwidth, and the development of high-speed underwater acoustic communication is urgently needed.
Orthogonal Frequency Division Multiplexing (OFDM) technology provides a very potential idea for high-speed underwater acoustic communication due to its advantages of strong anti-multipath effect and high spectrum utilization rate. The OFDM passes the single-path high-speed serial data to be the multi-path low-speed parallel data, and can effectively resist the multi-path interference on the premise of not influencing the transmission rate; in addition, the OFDM allows the frequency spectrums to be overlapped by ensuring the orthogonality among the subcarriers, so that the frequency spectrum efficiency of the underwater acoustic channel is effectively improved.
The channel estimation is an indispensable important module in the underwater acoustic OFDM system, and plays a vital role in adaptive modulation and coding of a transmitting end and signal detection and recovery of a receiving end. The traditional channel estimation method mainly comprises three types, namely non-blind estimation, semi-blind estimation and blind estimation, wherein the non-blind estimation refers to an estimation method by means of pilot frequency (reference signal), the blind estimation refers to an estimation method without the pilot frequency through the inherent characteristics of signals, and the semi-blind estimation refers to a method combining the non-blind estimation and the blind estimation. Generally, blind estimation and semi-blind estimation require no or less reference signals, can effectively reduce estimation overhead, and have high data transmission rate, but have high computational complexity and very limited estimation accuracy. Thus, at present, the wireless communication mainly adopts a pilot-based non-blind channel estimation method. However, the underwater acoustic channel is bad and complex, the multipath effect and the doppler effect are severe, and the coherence bandwidth and the coherence time are extremely short (at least one pilot symbol needs to be inserted within one coherence time and one coherence bandwidth to ensure the estimation accuracy). The traditional non-blind channel estimation method improves the estimation accuracy by increasing the number of pilot frequencies, brings serious pilot frequency overhead in an underwater acoustic channel, and greatly reduces the effective transmission rate of data. Therefore, how to achieve accurate channel estimation with less pilot overhead is crucial to the underwater OFDM system.
Disclosure of Invention
In view of the above defects or improvement requirements of the prior art, the present invention provides a channel estimation method for an underwater acoustic OFDM communication system with low pilot frequency overhead, and aims to solve the technical problem that the prior art cannot realize accurate channel estimation with less pilot frequency overhead.
In order to achieve the above object, in a first aspect, the present invention provides a channel estimation method for an underwater acoustic OFDM communication system with low pilot overhead, including the following steps:
s1, calculating channel state information at the preset pilot frequency position at the current moment;
s2, pre-estimating a channel state matrix according to the obtained channel state information at the pilot frequency position to obtain a pre-estimated channel state matrix;
s3, inputting the pre-estimated channel state matrix into the pre-trained channel estimation model to obtain the channel state matrix at the current moment;
wherein the channel estimation model comprises a super-resolution model.
Further preferably, the method for training the channel estimation model includes:
acquiring a sending signal X of a sending end and a receiving signal Y of a receiving end in an underwater sound OFDM communication system at different moments, and calculating to obtain channel state matrixes at different moments in a real underwater sound environment according to the sending signal X and the receiving signal Y of the receiving end, wherein the sending signal X is known at the sending end and the receiving end;
respectively calculating channel state information at preset pilot frequency positions in the transmission signals X for the acquired transmission signals X at different moments, and pre-estimating a channel state matrix according to the obtained channel state information at the pilot frequency positions to obtain pre-estimated channel state matrices at different moments;
and taking the channel state matrixes pre-estimated at different moments as input, taking the corresponding channel state matrix in the real underwater acoustic environment as output, and training the channel estimation model to obtain the pre-trained channel estimation model.
Further preferably, the channel estimation model further includes a multiplication module and a division module; the multiplication module, the super-resolution model and the division module are sequentially connected in series;
the multiplication module is used for multiplying the data input into the channel estimation model by the scaling factor and outputting the data into the super-resolution model;
the division module is used for correspondingly dividing the output data of the super-resolution model by the scaling factor.
Further preferably, the size of the pre-estimated channel state matrix is recorded as R × C, and the real part and the imaginary part of each element in the pre-estimated channel state matrix are divided to obtain a real part matrix and an imaginary part matrix of which the sizes are R × C; and recombining the real part matrix and the imaginary part matrix to obtain a matrix with the size of R multiplied by C multiplied by 2, and using the matrix as the input of the channel estimation model.
Further preferably, the super-resolution model is a VDSR model.
Further preferably, the excitation function of the VDSR model is an LReLu function.
Further preferably, the LS algorithm is used to calculate the channel state information at the preset pilot positions.
Further preferably, the channel state matrix is pre-estimated by using an interpolation algorithm according to the channel state information at the obtained pilot frequency position.
Further preferably, the interpolation algorithm is a cubic spline interpolation algorithm.
In a second aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, implements the method for channel estimation in an underwater acoustic OFDM communication system with low pilot overhead as described above.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
1. the invention provides a channel estimation method of an underwater acoustic OFDM communication system with low pilot frequency overhead, which is characterized in that the problem that the channel state information of part of preset pilot frequency positions estimates the channel state of an unknown data position is equivalent to a matrix completion problem, a super-resolution model is constructed and trained to be used as a channel estimation model to further accurately estimate a pre-estimated channel state matrix, the matrix of the channel state can be accurately estimated without increasing the number of pilot frequencies, and accurate channel estimation can be realized with less pilot frequency overhead.
2. The channel estimation method of the underwater sound OFDM communication system with low pilot frequency overhead provided by the invention considers that the channel state matrixes of the underwater sound are all minimum numbers, and the input is multiplied by the scaling factor before the super-resolution model is input, so that the problem that the gradient disappears in the training process of the channel estimation model is avoided.
3. Since in the hydroacoustic channel, the elements in the channel state matrix are complex and the real and imaginary parts in each element are closely related, they together determine the amplitude attenuation and phase rotation of the channel. In order to save the inherent intraconnection between the real part and the imaginary part of the elements of the channel state matrix, the channel estimation method of the underwater sound OFDM communication system with low pilot frequency overhead provided by the invention divides the real part and the imaginary part of each element in the pre-estimated channel state matrix, further recombines the divided two matrixes with equal size, and recombines the matrixes into a two-channel real number matrix along a third coordinate, so as to ensure that the three-dimensional convolution in the training process of a channel estimation model can simultaneously take account of the information of the real part and the imaginary part.
4. The channel estimation method of the underwater acoustic OFDM communication system with low pilot frequency overhead, provided by the invention, has the advantages that the excitation function of the channel estimation model is preferably the LReLu function, so that the gradient can be effectively calculated by both positive numbers and negative numbers, and the overfitting of a network caused by introducing excessive parameters is avoided.
Drawings
Fig. 1 is a flowchart of a channel estimation method of an underwater acoustic OFDM communication system with low pilot overhead according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a process for recombining a pre-estimated channel state matrix into a three-dimensional matrix according to embodiment 1 of the present invention;
fig. 3 is a schematic diagram of a channel estimation process of an underwater acoustic OFDM communication system with low pilot overhead according to embodiment 1 of the present invention;
fig. 4 is an MSE performance diagram of channel estimation of the underwater acoustic OFDM communication system according to embodiment 1 of the present invention;
fig. 5 is a BER performance diagram of channel estimation of the underwater acoustic OFDM communication system provided in embodiment 1 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Examples 1,
A method for estimating a channel of an underwater acoustic OFDM communication system with low pilot overhead, as shown in fig. 1, includes the following steps:
s1, calculating channel state information at the preset pilot frequency position at the current moment;
specifically, in the present embodiment, the LS algorithm with low complexity is used to calculate the channel state information at the preset pilot position at the current time. The channel transmission matrix may be represented as:
Y＝HX+N
wherein H, X, N and Y are the channel transmission matrix, the transmission data matrix, the channel additive noise and the reception data matrix, respectively. The LS algorithm represents the channel estimation problem as minimizing the true received data Y and the estimated received data
Mean square error between, expressed as:
wherein the content of the first and second substances,
is an estimate of the channel transmission matrix.
To solve the minimization problem, the LS algorithm attempts to find
Satisfy the point where the gradient is 0, i.e.
Finally, the result of the rough estimation of the position state of the pilot frequency position channel is obtained as
S2, pre-estimating a channel state matrix according to the obtained channel state information at the pilot frequency position to obtain a pre-estimated channel state matrix;
the present embodiment pre-estimates the channel state matrix using an interpolation algorithm. Preferably, the cubic spline interpolation algorithm of the present embodiment pre-estimates the channel state matrix.
S3, inputting the pre-estimated channel state matrix into the pre-trained channel estimation model to obtain the channel state matrix at the current moment; the channel estimation model mainly comprises a super-resolution model;
specifically, the training method of the channel estimation model includes:
acquiring a sending signal X of a sending end and a receiving signal Y of a receiving end in an underwater sound OFDM communication system at different moments, and calculating to obtain channel state matrixes at different moments in a real underwater sound environment according to the sending signal X and the receiving signal Y of the receiving end, wherein the sending signal X is known at the sending end and the receiving end;
respectively calculating channel state information at preset pilot frequency positions in the transmission signals X for the acquired transmission signals X at different moments, and pre-estimating a channel state matrix according to the obtained channel state information at the pilot frequency positions to obtain pre-estimated channel state matrices at different moments;
and taking the channel state matrixes pre-estimated at different moments as input, taking the corresponding channel state matrix in the real underwater acoustic environment as output, and training the channel estimation model to obtain the pre-trained channel estimation model.
In this embodiment, the parameters of the underwater acoustic OFDM communication system are set to have a carrier frequency of 16kHz, a bandwidth of 4kHz, a number of subcarriers of 512, each frame including 16 symbols (corresponding to a size of a channel matrix of 512 × 16), and a modulation scheme of QPSK. The invention generates 10000 channel matrixes, wherein 8000 are used as training sets, 1000 are used as verification sets, and the rest 1000 are used as test sets.
Preferably, the channel estimation model further includes a multiplication module and a division module; the multiplication module, the super-resolution model and the division module are sequentially connected in series; the multiplication module is used for multiplying the data input into the channel estimation model by the scaling factor and outputting the data into the super-resolution model; the division module is used for corresponding the output data of the super-resolution modelDivided by a scaling factor to compensate for this effect. As the underwater acoustic channel state matrixes are all small numbers and are all 10-3～10-6In the training process of the channel estimation model, the problem of gradient disappearance is easily caused. Therefore, the data input into the channel estimation model is multiplied by a scaling factor alpha before training, and the gradient calculation of the model in the training process can be ensured to be normally carried out.
Further, in the underwater acoustic channel, the elements in the channel state matrix are complex numbers, and the real part and the imaginary part in each element are closely related, so that amplitude attenuation and phase rotation of the channel are jointly determined, and in order to save the inherent interconnection between the real part and the imaginary part of the elements of the channel state matrix, as shown in fig. 2, the real part and the imaginary part of each element in the pre-estimated channel state matrix are segmented, two equally-large matrices after segmentation are further recombined, and are recombined into a two-channel real number matrix along a third coordinate, so that the three-dimensional convolution in the training process of the channel estimation model can simultaneously take account of the real part information and the imaginary part information. Specifically, the size of a pre-estimated channel state matrix is recorded as R × C, and a real part matrix and an imaginary part matrix with the sizes of R × C are obtained after real parts and imaginary parts of elements in the pre-estimated channel state matrix are segmented; and recombining the real part matrix and the imaginary part matrix to obtain a matrix with the size of R multiplied by C multiplied by 2, and using the matrix as the input of the channel estimation model.
Further, the channel estimation model in this embodiment is preferably a deep residual convolutional neural network, i.e., a VDSR model, which has good performance, low complexity and is very representative. In addition, in the underwater acoustic channel, the elements in the channel state matrix are positive or negative, and the classical ReLu activation function is constant 0 in the negative half axis, which will prevent the gradient propagation of negative numbers in the training process. In order to ensure the nonlinearity of the activation function, and at the same time, not introduce too many parameters to cause network overfitting, the present embodiment preferably selects the excitation function of the VDSR model as an lreul function, which is expressed as:
wherein, aiIs an adjustable gradient value with the value between 0 and 1,typically set to 0.2.
Specifically, as shown in fig. 3, the neural network in the VDSR model is composed of 20 convolution layers and 19 LReLu activation functions, the sizes of convolution kernels of the first 19 layers are all 3 × 3, and the number of convolution kernels is 64. The last convolution layer is used as an output layer, the number of convolution kernels is 2 (corresponding to a two-channel real number matrix), and an activation function is not needed. The loss function in the invention is set as the mean square error between the estimated channel matrix and the real channel matrix:
wherein h isiThe elements in the channel state matrix under the real underwater acoustic environment;
m is the number of elements in the pre-estimated channel state matrix.
In the training process, the scaling factor α of the present embodiment is set to 10, and the initial learning rate is set to 0.001. To speed up the convergence of the initial channel estimation model while avoiding late missing of the optimal solution, the learning rate will be attenuated by a factor of 0.1 after each 40 iterations. The iteration termination condition is 100 iterations, but if no drop in the loss function occurs in 5 consecutive iterations, the iteration will terminate early to avoid network overfitting.
In order to further illustrate the effect of the channel estimation method for the underwater acoustic OFDM communication system with low pilot frequency overhead provided by the present invention, the LS algorithm, the DNN algorithm, and the channel estimation method (denoted as CSRNet) provided by the present invention are respectively adopted to perform channel estimation respectively under the condition that the preset number of pilot frequencies is 2symbols (denoted as 2symbols) and 4symbols (denoted as 4symbols), and respectively calculate the mean square error MSE between the estimated channel matrix and the real channel matrix, and recover the BER when transmitting data by using the estimated channel matrix (for the underwater acoustic OFDM system, recovering the transmitted data is an important purpose of channel estimation), thereby obtaining the MSE performance diagram of the channel estimation of the underwater acoustic OFDM communication system shown in fig. 4 and the BER performance diagram of the channel estimation of the underwater acoustic OFDM communication system shown in fig. 5. As can be seen from fig. 4, compared with the DNN algorithm (the performance of the DNN algorithm is already very close to the MMSE algorithm as the performance upper limit), the method proposed by the present invention can always achieve a lower mean square error (mean square error) up to 67.64% (when SNR is 0 dB) under the same number of pilots. Compared with the widely used LS algorithm, when the pilot frequency overhead is reduced by 50%, the method provided by the invention can still obtain lower error performance, which means that the invention realizes higher estimation precision with lower pilot frequency overhead. As can be seen from fig. 5, compared with the DNN algorithm, the method of the present invention always achieves a lower error rate when recovering the transmitted data. It is more important to note that the method of the present invention using 2symbols as pilot can achieve lower BER than the LS algorithm using 4symbols as pilot, up to 44.74%. That is, the present invention enables more accurate signal detection with lower pilot overhead.
Examples 2,
A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a low pilot overhead underwater OFDM communication system channel estimation method as described in an embodiment.
The related technical scheme is the same as embodiment 1, and is not described herein.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A channel estimation method of an underwater sound OFDM communication system with low pilot frequency overhead is characterized by comprising the following steps:
s1, calculating channel state information at the preset pilot frequency position at the current moment;
s2, pre-estimating a channel state matrix according to the channel state information at the pilot frequency position to obtain a pre-estimated channel state matrix;
s3, inputting the pre-estimated channel state matrix into a pre-trained channel estimation model to obtain a channel state matrix at the current moment; the pre-estimated channel state matrix is R multiplied by C in size, and real parts and imaginary parts of all elements in the pre-estimated channel state matrix are divided to obtain real part matrixes and imaginary part matrixes of R multiplied by C in size; recombining the real part matrix and the imaginary part matrix to obtain a matrix with the size of R multiplied by C multiplied by 2, and using the matrix as the input of the channel estimation model;
the channel estimation model comprises a multiplication module, a super-resolution model and a division module which are sequentially connected in series;
the multiplication module is used for multiplying the data input into the channel estimation model by a scaling factor and outputting the data to the super-resolution model;
the division module is used for correspondingly dividing the output data of the super-resolution model by the scaling factor.
2. The method for channel estimation in an underwater acoustic OFDM communication system with low pilot overhead as claimed in claim 1, wherein said training method for channel estimation model comprises:
acquiring a sending signal X of a sending end and a receiving signal Y of a receiving end in an underwater sound OFDM communication system at different moments, and calculating to obtain channel state matrixes at different moments in a real underwater sound environment according to the sending signal X and the receiving signal Y of the receiving end, wherein the sending signal X is known at the sending end and the receiving end;
respectively calculating channel state information at preset pilot frequency positions in the transmission signals X for the acquired transmission signals X at different moments, and pre-estimating a channel state matrix according to the obtained channel state information at the pilot frequency positions to obtain pre-estimated channel state matrices at different moments;
and training the channel estimation model by taking the channel state matrixes pre-estimated at different moments as input and taking the corresponding channel state matrix under the real underwater acoustic environment as output to obtain the pre-trained channel estimation model.
3. The channel estimation method according to claim 1 or 2, wherein the super-resolution model is a VDSR model.
4. The channel estimation method according to claim 3, wherein the excitation function of the VDSR model is LReLu function.
5. The channel estimation method according to claim 1 or 2, characterized in that the channel state information at the preset pilot positions is calculated using an LS algorithm.
6. The channel estimation method according to claim 1 or 2, characterized in that the channel state matrix is pre-estimated using an interpolation algorithm based on the channel state information at the pilot positions.
7. The channel estimation method of claim 6, wherein the interpolation algorithm is a cubic spline interpolation algorithm.
8. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the channel estimation method according to any one of claims 1 to 7.
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