Transform domain and serial interference cancellation combined scattering waveform transmission method

Abstract

The invention discloses a scattering waveform transmission method combining a transform domain and serial interference cancellation, and relates to the field of wireless communication. According to the method, a DCGWFRFT waveform design technology and a V-BLAST signal detection technology are combined, a novel waveform transmission mode is designed, two time domain components of a sending symbol sequence are subjected to weighted combination, sending symbols in different space time are combined, and finally, the signal detection performance is improved through serial interference cancellation. The bit error rate of the system is greatly reduced. Compared with an existing single-carrier waveform, a transform domain waveform and a V-BLAST-based single-carrier waveform, the waveform design method provided by the invention has better diversity performance under the condition that the data rate is not changed.

Description

Technical Field

[0001] The invention relates to the field of wireless communications, and in particular to a scattering waveform transmission method combining joint transform domain and serial interference cancellation. Background Art

[0002] Tropospheric scatter communication technology is a wireless communication technology that uses the scattering effect of radio waves on the inhomogeneity of the tropospheric medium. Its technical basis is the tropospheric scatter propagation theory. The tropospheric scatter transmission system designed using the tropospheric scatter propagation theory can achieve over-the-horizon transmission, and at the same time has moderate transmission capacity, transmission performance and reliability, as well as strong resistance to nuclear explosions and ionospheric disturbances. Due to its unique transmission characteristics, tropospheric scatter communication technology plays an irreplaceable role in a variety of different communication transmission technologies.

[0003] Scattering communication has a history of more than 60 years since its birth. At present, the capacity problem of scattering communication has become the focus of attention of countries around the world. For example, the American comtech company has achieved a communication rate of 210Mbps, while the rate of scattering communication technology in my country is 50Mbps. With the gradual application of the fifth-generation mobile communication technology, high-throughput satellite technology, and millimeter-wave large-capacity microwave communication technology in communication, the transmission rate of the next-generation communication system will be improved overall. Scattering communication also needs to further improve the transmission rate so as not to become a bottleneck for the communication transmission of the entire network.

[0004] Massive MIMO technology is one of the important technologies for improving system capacity in current mobile communications. Compared with traditional single antennas, massive MIMO communication systems can improve communication capacity and bit error rate performance without the need for additional transmission power or frequency band. Therefore, massive MIMO technology can be introduced into scattering communication, which can also provide scattering communication systems with considerable communication rate and communication quality.

[0005] Massive MIMO technology provides diversity gain through multi-antenna spatial diversity technology, but there is a trade-off between diversity gain and multiplexing gain when the number of antennas is limited. In order to reduce the system bit error rate without losing communication capacity, it is necessary to consider providing additional diversity capabilities through waveform design. Summary of the invention

[0006] In view of this, the present invention proposes a scattering waveform transmission method of joint transform domain and serial interference cancellation. The method combines the waveform design technology of double-component combined generalized weighted fractional Fourier transform (Double-component combined generalized weighted fractional Fourier transform, DCGFRFT) and the signal detection technology of Vertical Bell Labs Layered Space-Time (Vertical Bell Labs Layered Space-Time, V-BLAST), and designs a new waveform transmission mode, which combines the two components of the time domain of the transmitted symbol sequence by weighted combination, merges the transmitted symbols of different space-time, and finally improves the signal detection performance through serial interference cancellation, so as to achieve a significant reduction in the system bit error rate.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0008] A joint transform domain and serial interference cancellation method for scattering waveform transmission,

[0009] The sender performs the following steps:

[0010] Step a1: The transmitter modulates the bit stream sent in M ​​time slots into a symbol sequence x, x∈C MK ; Wherein, C represents a complex number, and the number of antennas at the transmitting end and the receiving end is K;

[0011] Step a2, performing a two-component combined generalized weighted fractional Fourier transform on the symbol sequence x to obtain a transformed transmitted symbol sequence z. The transformation formula is:

[0012] z=F + x;

[0013] Among them, the transformation matrix F + Defined as:

[0014]

[0015] I represents the identity matrix with MK rows and MK columns, and Γ represents the permutation matrix with MK rows and MK columns, which is defined as:

[0016]

[0017] The transformation coefficients are:

[0018]

[0019] Where j represents an imaginary unit, the parameter θ0 is randomly generated in the interval [0,2π], and θ1 = θ0 + π / 2;

[0020] Step a3, divide the transformed transmission symbol sequence z into M segments in order, denoted as And in the i-th time slot, the i-th transmission symbol sequence z is sent through K transmitting antennas i , i=1,2,3,……,M;

[0021] The receiving end performs the following steps:

[0022] Step b1: The receiving end receives the i-th segment of the received symbol sequence y through K receiving end antennas in the i-th time slot i :

[0023] y i =H i z i +w i ;

[0024] Among them, H i represents the channel matrix corresponding to the i-th segment received symbol sequence, H i ∈C K×K , w i represents the additive white Gaussian noise corresponding to the i-th segment received symbol sequence, CN() represents complex Gaussian white noise, is the noise power;

[0025] Step b2: The receiving end collects all received symbol sequences and channel matrices, and forms a synthetic signal vector y and a synthetic channel matrix H respectively:

[0026]

[0027]

[0028] Step b3: combine the synthesized channel matrix with the transformation matrix F + Multiply them together to get the equivalent channel matrix G:

[0029] G=HF + ;

[0030] Step b4, calculate the initial equivalent channel equalization matrix:

[0031]

[0032] Step b5, calculate the norm of each column in the equivalent channel matrix G:

[0033] r=[r(1), r(2),..., r(MK)]=[||G[:,1]||2,||G[:,2]||2,...,||G[:,MK]||2];

[0034] Step b6, sorting the elements of the vector r in descending order, and constructing a vector n according to the index values ​​of the sorted elements in the vector r;

[0035] Step b7, initialize m=1, v1=y, length MK make

[0036] Step b8, performing channel equalization on the current n(m)th data stream:

[0037] x temp =W[n(m),:]v m ;

[0038] Step b9, for x temp Demodulate and then re-modulate the demodulated result to obtain the estimated symbol And order

[0039] Step b10, deleting the interference in the synthesized signal vector:

[0040]

[0041] Step b11, set m=m+1;

[0042] Step b12, repeating steps b8 to b11 until m=MK+1;

[0043] Step b13, Demodulate and output the signal detection result.

[0044] Due to the adoption of the above technical solution, the beneficial effects of the present invention compared with the prior art are:

[0045] 1. The present invention improves the diversity performance of the system without using additional communication resources, but at the cost of a certain computational complexity. In addition, compared with the existing precoding algorithms, the algorithm proposed by the present invention does not require the transmitter to know the channel state information.

[0046] 2. The present invention integrates the inverse transformation step of the DCGWFRFT technology with the signal detection step, solving the problem of decreased bit error rate when the transform domain waveform is combined with the V-BLAST technology due to the constellation fission phenomenon and the reduction of the constellation point spacing of the new waveform. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a block diagram of a MIMO scattering communication system in an embodiment of the present invention.

[0048] Figure 2It is a flowchart of waveform transmission and detection of joint transform domain and serial interference cancellation in an embodiment of the present invention.

[0049] Figure 3 It is a flowchart of the V-BLAST signal detection technology in an embodiment of the present invention.

[0050] Figure 4 This is a performance comparison diagram of different waveform design methods under the BPSK modulation mode when the number of transmitting and receiving dual-end antennas is 16 in an embodiment of the present invention.

[0051] Figure 5 This is a performance comparison diagram of different waveform design methods under the QPSK modulation mode when the number of transmitting and receiving dual-end antennas is 16 in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0053] A joint transform domain and serial interference cancellation method for scattering waveform transmission, such as Figure 2 As shown,

[0054] The sender performs the following steps:

[0055] Step a1: The transmitter modulates the bit stream sent in M ​​time slots into a symbol sequence x, x∈C MK ; Wherein, C represents a complex number, and the number of antennas at the transmitting end and the receiving end is K;

[0056] Step a2, performing a two-component combined generalized weighted fractional Fourier transform on the symbol sequence x to obtain a transformed transmitted symbol sequence z. The transformation formula is:

[0057] z=F + x;

[0058] Among them, the transformation matrix F + Defined as:

[0059]

[0060] I represents the identity matrix with MK rows and MK columns, and Γ represents the permutation matrix with MK rows and MK columns, which is defined as:

[0061]

[0062] The transformation coefficients are:

[0063]

[0064] Where j represents an imaginary unit, the parameter θ0 is randomly generated in the interval [0,2π], and θ1 = θ0 + π / 2;

[0065] Step a3, divide the transformed transmission symbol sequence z into M segments in order, denoted as And in the i-th time slot, the i-th transmission symbol sequence z is sent through K transmitting antennas i , i=1,2,3,……,M;

[0066] Specifically, the i-th segment sends a symbol sequence z i The symbol length is K, so it can be sent through K transmitting antennas;

[0067] The receiving end performs the following steps:

[0068] Step b1: The receiving end receives the i-th segment of the received symbol sequence y through K receiving end antennas in the i-th time slot i :

[0069] y i =H i z i +w i ;

[0070] Among them, H i represents the channel matrix corresponding to the i-th segment received symbol sequence, H i ∈C K×K , w i represents the additive white Gaussian noise corresponding to the i-th segment received symbol sequence, CN() represents complex Gaussian white noise, is the noise power; in this embodiment, it is assumed that the receiving end can estimate the real channel;

[0071] Step b2: The receiving end collects all received symbol sequences and channel matrices, and forms a synthetic signal vector y and a synthetic channel matrix H respectively:

[0072]

[0073] Step b3: combine the synthesized channel matrix with the transformation matrix F + Multiply them together to get the equivalent channel matrix G:

[0074] G=HF + ;

[0075] Step b4, calculate the initial equivalent channel equalization matrix:

[0076]

[0077] Step b5, calculate the norm of each column in the equivalent channel matrix G:

[0078] r=[r(1), r(2),..., r(MK)]=[||G[:,1]||2,||G[:,2]||2,...,||G[:,MK]||2];

[0079] Specifically, ||·||2 represents the calculation norm, and G[:,1] represents the first column of the equivalent channel matrix G;

[0080] Step b6, sorting the elements of the vector r in descending order, and constructing a vector n according to the index values ​​of the sorted elements in the vector r;

[0081] Step b7, such as Figure 3 As shown, initialize m = 1, v1 = y, and the length is MK make

[0082] Step b8, performing channel equalization on the current n(m)th data stream:

[0083] x temp =W[n(m),:]v m ;

[0084] Specifically, W[n(m),:] represents the n(m)th row of the initial equivalent channel equalization matrix W; n(m) represents the mth value in the vector n: the elements of the vector r are sorted from large to small, and the number of columns of the equivalent channel matrix G corresponding to the maximum value element after sorting is recorded as n(1), the number of columns of the equivalent channel matrix G corresponding to the second largest element after sorting is recorded as n(2), ..., the number of columns of the equivalent channel matrix G corresponding to the minimum value element after sorting is recorded as n(MK);

[0085] Step b9, for x temp Demodulate and then re-modulate the demodulated result to obtain the estimated symbol And order

[0086] Step b10, deleting the interference in the synthesized signal vector:

[0087]

[0088] Step b11, set m=m+1;

[0089] Step b12, repeating steps b8 to b11 until m=MK+1;

[0090] Step b13, Demodulate and output the signal detection result.

[0091] Specifically, the MIMO scattering communication system structure considered in this embodiment is as follows: Figure 1 As shown;

[0092] Principle description:

[0093] Step b2: After all received signals and estimated channels are synthesized, the synthesized received signal is obtained as

[0094]

[0095] Set z = F + Substituting x into the equation, we get

[0096] y=HF + x+w=Gx+w;

[0097] G is regarded as an equivalent channel matrix, and then the serial interference cancellation based on column norm sorting is used to obtain the V-BLAST signal detection result under the transform domain waveform. Since the equivalent channel matrix G integrates the waveform transformation process of the transform domain waveform, the traditional waveform inverse transformation step is integrated with the signal detection step, which avoids the problem of bit error rate reduction when the transform domain waveform is combined with the V-BLAST technology due to the constellation fission phenomenon and the reduction of the constellation point spacing of the new waveform.

[0098] In summary, the present invention combines the anti-fading waveform based on the transform domain with the classic V-BLAST signal detection technology, and innovatively designs a new signal processing flow of combined inverse transform and signal detection at the receiving end, solving the problem of too small spacing between transform domain waveform constellation points in the traditional step-by-step signal processing flow. The simulation results are shown in Figure 2. Figure 4 and Figure 5 As shown, the horizontal axis represents the signal-to-noise ratio (expressed in dB), and the vertical axis represents the bit error rate, where Figure 4 The modulation method is BPSK, and Figure 5 The modulation mode is QPSK. The scattering channel is randomly generated according to the massive MIMO Rayleigh channel model, where the number of antennas at both ends is set to 16, the number of transmission time slots is M = 8, and each time slot channel is independently randomly generated. The parameters of the waveform transformation are set to θ0 = 0, θ1 = π / 2. The simulation results show that when the bit error rate is 10 -3 When the modulation mode is BPSK, the signal-to-noise ratio performance of the scattering waveform of the joint transform domain and serial interference cancellation proposed in the present invention is improved by about 4.4dB compared with the single-carrier waveform, the signal-to-noise ratio performance is improved by about 2.7dB compared with the transform domain waveform, and the signal-to-noise ratio performance is improved by about 0.8dB compared with the single-carrier waveform based on V-BLAST; when the bit error rate is 10 -3When the modulation mode is QPSK, the signal-to-noise ratio performance of the scattered waveform of the joint transform domain and serial interference cancellation proposed in the present invention is improved by about 6.1dB compared with the single-carrier waveform, the signal-to-noise ratio performance is improved by about 3.2dB compared with the transform domain waveform, and the signal-to-noise ratio performance is improved by about 1.8dB compared with the single-carrier waveform based on V-BLAST.

[0099] Those skilled in the art will appreciate that the embodiments described are intended to help readers understand the principles of the present invention, and should be understood that the scope of protection of the present invention is not limited to the embodiments described. For those skilled in the art, the present invention may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A method for transmitting scattered waveforms by joint transform domain and serial interference cancellation, characterized in that: The sender performs the following steps: Step a1: The transmitter modulates the bit stream sent in M ​​time slots into a symbol sequence x, x∈C MK ; Wherein, C represents a complex number, and the number of antennas at the transmitting end and the receiving end is K; Step a2, performing a two-component combined generalized weighted fractional Fourier transform on the symbol sequence x to obtain a transformed transmitted symbol sequence z. The transformation formula is: z=F + x; Among them, the transformation matrix F + Defined as: I represents the identity matrix with MK rows and MK columns, and Γ represents the permutation matrix with MK rows and MK columns, which is defined as: The transformation coefficients are: Where j represents an imaginary unit, the parameter θ0 is randomly generated in the interval [0,2π], and θ1 = θ0 + π / 2; Step a3, divide the transformed transmission symbol sequence z into M segments in order, denoted as And in the i-th time slot, the i-th transmission symbol sequence z is sent through K transmitting antennas i , i=1,2,3,……,M; The receiving end performs the following steps: Step b1: The receiving end receives the i-th segment of the received symbol sequence y through K receiving end antennas in the i-th time slot i : y i =H i z i +w i ; Among them, H i represents the channel matrix corresponding to the i-th segment received symbol sequence, H i ∈C K×K , w i represents the additive white Gaussian noise corresponding to the i-th segment received symbol sequence, CN() represents complex Gaussian white noise, is the noise power; Step b2: The receiving end collects all received symbol sequences and channel matrices, and forms a synthetic signal vector y and a synthetic channel matrix H respectively: Step b3: combine the synthesized channel matrix with the transformation matrix F + Multiply them together to get the equivalent channel matrix G: G=HF + ; Step b4, calculate the initial equivalent channel equalization matrix: Step b5, calculate the norm of each column in the equivalent channel matrix G: r=[r(1), r(2),..., r(MK)]=[||G[:,1]||2,||G[:,2]||2,...,||G[:,MK]||2]; Step b6, sorting the elements of the vector r in descending order, and constructing a vector n according to the index values ​​of the sorted elements in the vector r; Step b7, initialize m=1, v1=y, length MK make Step b8, performing channel equalization on the current n(m)th data stream: x temp =W[n(m),:]v m ; Step b9, for x temp Demodulate and then re-modulate the demodulated result to obtain the estimated symbol And order Step b10, deleting the interference in the synthesized signal vector: Step b11, set m=m+1; Step b12, repeating steps b8 to b11 until m=MK+1; Step b13, Demodulate and output the signal detection result.

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