A Scattering Waveform Transmission Method Based on Joint Transform Domain and Serial Interference Cancellation

Abstract

The present invention discloses a scattering waveform transmission method for joint transform domain and serial interference cancellation, relating to the field of wireless communications. The present invention combines DCGWFRFT waveform design technology with V-BLAST signal detection technology to design a new waveform transmission method. By weightedly combining the two time-domain components of the transmitted symbol sequence, the transmitted symbols at different space-times are merged. Finally, serial interference cancellation is used to improve signal detection performance, thereby significantly reducing the system bit error rate. Compared with existing single-carrier waveforms, transform domain waveforms, and V-BLAST-based single-carrier waveforms, the waveform design method of the present invention has better diversity performance while maintaining a constant data rate.

Description

Technical Field

[0001] The present 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] Troposcatter communication technology is a wireless communication technique that exploits the scattering of radio waves by the inhomogeneous nature of the tropospheric medium. Its foundation is the theory of tropospheric scatter propagation. Troposcatter transmission systems designed using this theory can achieve beyond-line-of-sight transmission while offering moderate transmission capacity, performance, and reliability, as well as strong resistance to nuclear explosions and ionospheric disturbances. Due to its unique transmission characteristics, troposcatter communication technology plays an irreplaceable role among various communication transmission technologies.

[0003] Scatter communication has a history of over 60 years. Its capacity has become a major concern worldwide. For example, US-based Comtech has achieved a 210 Mbps communication speed, while my country's current scatter communication technology only reaches 50 Mbps. With the gradual application of fifth-generation mobile communications, high-throughput satellite technology, and millimeter-wave, high-capacity microwave communications, the transmission speed of next-generation communication systems will increase overall. Scatter communication also needs to further improve its transmission speed to avoid becoming a bottleneck for network-wide communications.

[0004] Massive MIMO technology is one of the key technologies currently used to increase system capacity in mobile communications. Compared to traditional single-antenna systems, Massive MIMO systems can achieve improvements in communication capacity and bit error rate performance without requiring additional transmit power or bandwidth. Therefore, Massive MIMO technology can be incorporated into scattering communications, similarly providing impressive communication rates and quality.

[0005] Massive MIMO technology provides diversity gain through spatial diversity using multiple antennas. However, with a limited number of antennas, there is a trade-off between diversity gain and multiplexing gain. To reduce the system's bit error rate without sacrificing communication capacity, waveform design is necessary to provide additional diversity capabilities. Summary of the Invention

[0006] In view of this, the present invention proposes a scattering waveform transmission method with joint transform domain and serial interference cancellation. This method combines the waveform design technology of the double-component combined generalized weighted fractional Fourier transform (DCGWFRFT) with the signal detection technology of the Vertical Bell Labs Layered Space-Time (V-BLAST). A new waveform transmission mode is designed. By weightedly combining the two time domain components of the transmitted symbol sequence, the transmitted symbols of different space-times are merged. Finally, serial interference cancellation is used to improve the signal detection performance, thereby significantly reducing 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 sending end 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 ; Where C represents a complex number, and the number of antennas at both the transmitting and receiving ends is K;

[0011] Step a2: Perform 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 the imaginary unit, the parameter θ0 is randomly generated in the interval [0,2π], θ1 = θ0 + π / 2;

[0020] Step a3: divide the transformed transmission symbol sequence z into M segments in order, recorded 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] In step b2, the receiving end collects all received symbol sequences and channel matrices, and composes a composite signal vector y and a composite 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: sort the elements of vector r in descending order, and construct vector n based on the index value of each sorted element in vector r;

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

[0036] Step b8: Perform 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 remodulate the demodulated result to obtain the estimated symbol And order

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

[0040]

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

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

[0043] Step b13, Perform demodulation and output signal detection results.

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

[0045] 1. The present invention improves system diversity performance without using additional communication resources, but at the expense of a certain degree of computational complexity. In addition, compared to existing precoding algorithms, the algorithm proposed in 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 bit error rate degradation 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 2This is a flowchart of waveform transmission and detection for 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 with reference to 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 sending end 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 ; Where C represents a complex number, and the number of antennas at both the transmitting and receiving ends is K;

[0056] Step a2: Perform 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 the imaginary unit, the parameter θ0 is randomly generated in the interval [0,2π], θ1 = θ0 + π / 2;

[0065] Step a3: divide the transformed transmission symbol sequence z into M segments in order, recorded 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 the 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] In step b2, the receiving end collects all received symbol sequences and channel matrices, and composes a composite signal vector y and a composite 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: sort the elements of vector r in descending order, and construct vector n based on the index value of each sorted element in 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: Perform 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 remodulate the demodulated result to obtain the estimated symbol And order

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

[0087]

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

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

[0090] Step b13, Perform demodulation and output signal detection results.

[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 combines all received signals and estimated channels to obtain a composite received signal:

[0094]

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

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

[0097] Treating G as an equivalent channel matrix and applying serial interference cancellation based on column norm sorting yields V-BLAST signal detection results for transform-domain waveforms. Because the equivalent channel matrix G incorporates the waveform transformation process of the transform-domain waveform, it merges the traditional inverse waveform transformation step with the signal detection step. This avoids the bit error rate degradation that occurs when transform-domain waveforms are combined with V-BLAST technology due to constellation fission and the reduced spacing between constellation points.

[0098] In summary, this invention combines the transform-domain anti-fading waveform 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. 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 scheme 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 and θ1 = π / 2. The simulation results show that when the bit error rate is 10 -3 When the modulation mode is BPSK, the scattering waveform of the joint transform domain and serial interference cancellation proposed in the present invention improves the signal-to-noise ratio performance by about 4.4dB compared with the single-carrier waveform, the signal-to-noise ratio performance by about 2.7dB compared with the transform domain waveform, and the signal-to-noise ratio performance 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. It will be apparent to those skilled in the art that various modifications and variations are possible in the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A method for transmitting scattered waveforms using a joint transform domain and serial interference cancellation method, characterized in that: The sending end 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 ; Where C represents a complex number, and the number of antennas at both the transmitting and receiving ends is K; Step a2: Perform a two-component combined generalized weighted fractional Fourier transform on the symbol sequence x to obtain the 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 the imaginary unit, the parameter θ0 is randomly generated in the interval [0,2π], θ1 = θ0 + π / 2; Step a3: divide the transformed transmission symbol sequence z into M segments in order, recorded 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; In step b2, the receiving end collects all received symbol sequences and channel matrices, and composes a composite signal vector y and a composite 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: sort the elements of vector r in descending order, and construct vector n based on the index value of each sorted element in vector r; Step b7, initialize m=1, v1=y, length MK make Step b8: Perform 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 remodulate the demodulated result to obtain the estimated symbol And order Step b10: Delete the interference in the synthesized signal vector: Step b11, set m=m+1; Step b12: Repeat steps b8 to b11 until m=MK+1; Step b13, Perform demodulation and output signal detection results.

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