Common waveform method for base station to communicate and radar detect a drone

Abstract

The application belongs to the technical field of MIMO communication and sensing integration, and particularly relates to a common waveform method for base station to carry out communication and radar detection on a UAV. Based on OFDM, in combination with DFT spread spectrum, index modulation and interleaving technology, the application invents a new DFT-S-OFDM-ISIM waveform under a simultaneous system. In terms of communication bit error rate performance, the waveform performance is much better than that of a waveform without DFT spread spectrum, and has a 1dB gain relative to a waveform without time domain interleaving near 30dB signal-to-noise ratio. In terms of PAPR performance index, the waveform is obviously better than other traditional waveforms based on OFDM. On the other hand, for radar performance, the waveform of the application is better than an ordinary waveform with DFT spread spectrum in terms of UAV target hit rate.

Description

Technical Field

[0001] This invention belongs to the field of Massive Multiple Input Multiple Output (MIMO) Integrated Sensing and Communications (ISAC) technology, specifically relating to a shared waveform method for base stations to communicate with and detect unmanned aerial vehicles (UAVs). Background Technology

[0002] Integrated communication and radar technology is a hot topic in sixth-generation mobile communication. Employing a simultaneous system, using the same waveform for communication data transmission and radar target detection not only improves spectrum and hardware efficiency and saves resources, but also enhances information processing efficiency. Orthogonal frequency division multiplexing (OFDM) has been widely used since LTE (Long Term Evolution) and is one of the three key technologies of LTE. It remains a primary modulation method and is therefore often considered as the communication waveform for simultaneous systems. However, due to the limited dynamic range of power amplifiers, the peak-to-average power ratio (PAPR) of OFDM signals introduces nonlinear distortion into the power amplifier, resulting in significant signal distortion. Combining with index modulation (IM), OFDM-IM technology, while sacrificing some bit error rate (BER) performance, achieves subcarrier symbol sparsity, reducing the system's PAPR. Furthermore, frequency domain interleaving of OFDM-IM signals, using OFDM-ISIM, further improves system performance.

[0003] In LTE uplink waveforms, DFT-S-OFDM is a preferred option. Using DFT spread spectrum technology, this waveform not only further reduces PAPR but also has the advantage of easy integration with MIMO technology. Since DFT and IDFT can cancel each other out computationally, DFT-S-OFDM is also known as "single-carrier OFDM." DFT spread spectrum is equivalent to precoding the modulated signal, thereby obtaining diversity gain. Recently, some researchers have considered combining it with OFDM-IM technology for application in the ISAC field, enabling simultaneous optimization of communication and radar system performance. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of traditional waveforms based on OFDM technology by proposing a novel improved waveform that combines interleaving, DFT spread spectrum, and index modulation techniques to achieve multiple gains on both the communication and sensing sides.

[0005] The technical solution of this invention is: a shared waveform method for base station communication and radar detection of unmanned aerial vehicles (UAVs). This waveform is shared by both MIMO communication and MIMO radar systems, enabling simultaneous data communication between the base station and the UAV, as well as base station tracking of the UAV. The system includes one base station (BS) and one UAV, both equipped with uniform linear arrays. The BS has N... t Root dual-function transmit antenna and Q r The UAV has N receiving antennas. r The root receiving antenna. The communication channel between the BS and UAV is a block fading Rayleigh channel, and the radar channel is considered a Gaussian channel. All noise is additive white Gaussian noise. The dual-function waveform of this invention is based on OFDM principles, combined with DFT spread spectrum and time-domain interleaving techniques. In the MIMO model, it is used for communication between the BS and UAV, and for estimating the distance, velocity, and angle of the UAV. It can also be used in multi-UAV application scenarios. This invention includes the following steps:

[0006] Communication side:

[0007] S1. Divide the M transmission time slots into G sub-time slots of length L = M / G. The transmission symbol for each sub-time slot is represented as: x g =[x g,0 ,x g,1 ,...,x g,L-1 ] T If g = 0, 1, ..., G-1, then the time-domain transmission signal is:

[0008] x0 = [x0 T ,x1 T ,...,x G-1 T ] T =[x 0,0 ,x 0,1 ,...,x 0,L-1 ,...,x G-1,0 ,x G-1,1 ,...,x G-1,L-1 ](Formula 1)

[0009] For DFT-S-OFDM-IM, taking the sub-slot as the basic unit of modulation, it can be denoted as:

[0010] x g =[S g,0 ,0,...,0,S g,1 ,0,...,0,Sg,J-1 ,0,...,0] (Formula 2)

[0011] Among them, S g,j Let y represent a j-th order QAM modulated signal, j = 0, 1, ..., J-1, and y g ∈ξ, where ξ is the codebook of all possible vectors. During the modulation phase, The selected bits activate K out of L sub-slots, and p2 = Klog2J bits are used for modulation. Therefore, for each sub-slot, the number of modulation bits is p = p1 + p2, and the total number of bits for the entire DFT-S-OFDM-IM symbol is Gp.

[0012] S2. Based on Formula 1, perform time-domain interleaving of length M on the time-domain transmitted signal to obtain the transmitted signal x(m), m = 0, 1, ..., M-1. Perform an M-point DFT transform on x(m) to obtain the frequency-domain signal X(k):

[0013]

[0014] In a MIMO system, considering multiple antennas for transmission, the nth antenna... t The frequency domain signal of the transmitting antenna is:

[0015]

[0016] S3. Centralized subcarrier allocation is adopted, and X n(t) (k) is allocated to N = MA subcarriers. The positive integer A is called the spreading factor, which is usually taken as 2. The resulting spread spectrum signal is:

[0017]

[0018] S4. Then perform an N-point IFFT operation on Equation 5 to transform it to the time domain for transmission, obtaining the time-domain signal x. n(t) (n):

[0019]

[0020] S5, regarding x n(t) (n) Perform parallel-to-serial conversion, add a cyclic prefix, and then transmit via the RF chain. The receiver signal processing is the reverse process of the transmitter.

[0021] Let the nth t The frequency domain signal of the root receiving antenna is Y nr =[Y nr (0),Y nr (1),...,Y nr (M-2),Y nr [M-1], the channel matrix is Indicates the number of multipath paths in Gaussian white noise. Below, there is

[0022] Y nr =H nr×nt X n(t) +W nr ,n r =0,1,...,N r -1 (Formula 7)

[0023] The transmitted signal of each sub-block is reconstructed using the ML detection algorithm, and the transmitted signal is estimated as follows:

[0024]

[0025] Among them, X n(t),g Y nr,g H g These are the frequency domain transmitted signal, received signal, and channel matrix corresponding to the g-th sub-block, respectively.

[0026] Radar side:

[0027] S6. For multi-carrier signals, different subcarriers are processed separately. The nth subcarrier within the u-th pulse... t The m-th subcarrier signal of the root transmitting antenna is represented as x. u,nt (m,t), then the qth r The signal corresponding to the root receiving antenna is:

[0028]

[0029] Where, α l Let l be the reflectance factor of the l-th target. This represents additive white Gaussian noise. Let x be the round-trip time for detecting the l-th UAV. To separate the received waveform, the signal from Equation 9 is compared with the transmitted waveform x. u,nt (m,t) are synchronously mixed, then low-pass filtered, retaining only one data sampling point for each pulse, to obtain the q-th pulse. r Separated signals on the root receiving antenna:

[0030]

[0031] S7, set Rearrange Formula 10 into vector form y (r) Corresponding vector elements The construction dimension is N t Q r The observation matrix A of UM×UMQ:

[0032]

[0033] In the formula, The relative factor of carrier frequency. Construct a sparse vector b with sparsity L, and obtain y. (r) The relationship with observation matrix A is as follows:

[0034] y (r) =Ab+w (r) (Formula 12)

[0035] By determining the values ​​of the non-zero elements in b, the three-dimensional parameters of the UAV, such as distance, speed, and angle, can be obtained.

[0036] The beneficial effects of this invention are as follows: Based on OFDM, and combining DFT spread spectrum, indexed modulation, and interleaving techniques, this invention presents a novel DFT-S-OFDM-ISIM waveform under simultaneous modulation and oscillation. In terms of communication bit error rate performance, this waveform significantly outperforms waveforms without DFT spread spectrum, and exhibits a 1dB gain relative to waveforms without time-domain interleaving near a 30dB signal-to-noise ratio. Under PAPR performance metrics, this waveform is significantly superior to other traditional OFDM-based waveforms. Furthermore, regarding radar performance, the waveform of this invention achieves a higher hit rate against UAV targets than ordinary waveforms using DFT spread spectrum. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the communication system model of the present invention;

[0038] Figure 2 This is a schematic diagram of the radar system model of the present invention;

[0039] Figure 3 This is a schematic diagram comparing the bit error rate and communication performance of the waveform of this invention with that of a traditional waveform;

[0040] Figure 4 This is a schematic diagram comparing the peak-to-average power ratio (PAPR) communication performance of the waveform of this invention with that of a traditional waveform;

[0041] Figure 5 This is a schematic diagram comparing the radar performance of the ambiguity function of the waveform of this invention with that of a traditional waveform;

[0042] Figure 6 This is a schematic diagram comparing the radar performance of UAV target hit rate with the waveform of this invention and the traditional waveform. Detailed Implementation

[0043] The effectiveness and practicality of this invention are demonstrated below with reference to the accompanying drawings and simulation examples:

[0044] exist Figure 1In the background communication model, a 4×4 MIMO system is considered. In the Ruili channel, the number of subcarriers is set to 128, the total number of time slots is M=128, the number of sub-time slots G=32 groups with a time slot length of L=4, and K=3 sub-time slots are activated in each group. Figure 3 As shown, the DFT-S-OFDM-ISIM waveform proposed in this invention significantly outperforms traditional DFT-S-OFDM and ordinary OFDM waveforms without time-domain interleaving in terms of bit error rate performance, exhibiting a 1dB advantage near a 30dB signal-to-noise ratio. Furthermore, the traditional OFDM-based waveform shows a substantial improvement in bit error rate performance after DFT spreading. Finally, compared to the DFT-S-OFDM-ISIM waveform activated by a single time slot at K=1, the DFT-S-OFDM-ISIM waveform of this invention achieves a significant performance advantage due to the doubling of spectral transmission efficiency and the adoption of low-order symbol modulation. Figure 4 By comparing the peak-to-average power ratio (PAPR) difference between the waveform of this invention and the conventional residual waveform, it is easy to find that the PAPR performance of the DFT-S-OFDM-ISIM waveform is second only to the time-domain non-sparse DFT-S-OFDM waveform and the index modulation waveform without time-domain interleaving, and is far superior to other waveforms, thereby reducing the impact of nonlinear distortion on system performance.

[0045] exist Figure 2 In the background radar model, considering the uniformity and waveform sharing of integrated sensing devices, a 4×4 MIMO system under the AWGN channel is similarly set up, with a total number of time slots M=128 and a total number of subcarriers of 128. Figure 5 The ambiguity performance of the waveform of this invention under compressed sensing algorithm and the waveform without time-domain indexed modulation was compared. It can be seen that the main peak of the waveform of this invention is more obvious and easier to identify, while the side lobes are sparser, demonstrating the advantage of this waveform in radar tracking of UAVs. Furthermore, Figure 6 The radar performance was verified from the perspective of radar hit rate. Simulation results show that the two waveforms without DFT spread spectrum outperform other waveforms in terms of hit rate performance, and have an advantage of about 2dB in the -18dB to -8dB signal-to-noise ratio range. Furthermore, the DFT-S-OFDM-ISIM waveform proposed in this invention outperforms the remaining waveforms in hit rate.

Claims

1. A shared waveform method for base station communication and radar detection of unmanned aerial vehicles (UAVs), defining a system comprising one base station (BS) and one UAV, both equipped with uniform linear arrays, wherein the BS has N... t Root dual-function transmit antenna and Q r The UAV has N receiving antennas. r The root receiving antenna; the communication channel between the BS and UAV is a block fading Rayleigh channel, the radar channel is a Gaussian channel, and the noise is additive white Gaussian noise; its characteristics are... include: Communication side: S1. Divide the M transmission time slots into G sub-time slots of length L = M / G, and represent the transmission symbol of each sub-time slot as x. g =[x g,0 ,x g,1 ,...,x g,L-1 ] T If g = 0, 1, ..., G-1, then the time-domain transmission signal is: x₀ = [x₀ T , x₁ T , ..., x G-1 T T = [x 0,0 , x 0,1 , ..., x 0,L-1 , ..., x G-1,0 , x G-1,1 , ..., x G-1,L-1 (Formula 1)​ For DFT-S-OFDM-IM, the sub-slot is taken as the basic unit of modulation and denoted as: x g =[S g,0 ,0,...,0,S g,1 ,0,...,0,S g,J-1 ,0,...,0](Formula 2) Among them, S g,j Let y represent a j-th order QAM modulated signal, j = 0, 1, ..., J-1, and y g ∈ξ, where ξ is the codebook of all possible vectors; during the modulation phase, The bit selection activates K out of L sub-slots, and p2 = Klog2J bits are used for modulation. Therefore, for each sub-slot, the number of modulation bits is p = p1 + p2, and the number of bits for the entire DFT-S-OFDM-IM symbol is Gp. S2. Based on Formula 1, perform time-domain interleaving of length M on the time-domain transmitted signal to obtain the transmitted signal x(m), m=0,1,...M-1. Perform an M-point DFT transform on x(m) to obtain the frequency-domain signal X(k): nth t The frequency domain signal of the transmitting antenna is: S3. Centralized subcarrier allocation is adopted, and X n(t) (k) is allocated to N = MA subcarriers, where the positive integer A is called the spreading factor, and the resulting spread spectrum signal is: S4. Then perform an N-point IFFT operation on Equation 5 to transform it to the time domain for transmission, obtaining the time-domain signal x. n(t) (n): S5, regarding x n(t) (n) Perform parallel-to-serial conversion, add a cyclic prefix, and then transmit via the RF chain; the receiver signal processing is the reverse process of the transmitter: Let the nth r The frequency domain signal of the root receiving antenna is The channel matrix is Indicates the number of multipath paths in Gaussian white noise. Below, there is The transmitted signal of each sub-block is reconstructed using the ML detection algorithm, and the transmitted signal is estimated as follows: Among them, X n(t),g , H g These are the frequency domain transmitted signal, received signal, and channel matrix corresponding to the g-th sub-block, respectively. Radar side: S6. For multi-carrier signals, different subcarriers are processed separately; the nth subcarrier within the u-th pulse is processed separately. t The m-th subcarrier signal of the root transmitting antenna is represented as Then the qth r The signal corresponding to the root receiving antenna is: Where, α l Let l be the reflectance factor of the l-th target. This represents additive white Gaussian noise. To determine the round-trip time for detecting the l-th UAV; combine the signal from Formula 9 with the transmitted waveform. Synchronous mixing followed by low-pass filtering, retaining only one data sampling point for each pulse, yields the q-th pulse. r Separated signals on the root receiving antenna: S7, set Rearrange Formula 10 into vector form y (r) Corresponding vector elements The construction dimension is N t Q r The observation matrix A of UM×UMQ: In the formula, The carrier frequency relative factor is expressed as Q = Q r N t Construct a sparse vector b with sparsity L to obtain y. (r) The relationship with observation matrix A is as follows: y (r) = Ab + w (r) (Official 12) By determining the values ​​of the non-zero elements in b, the three-dimensional parameters of the UAV, namely distance, speed, and angle, are obtained.

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