A blind RS detection method based on the similarity of neighboring subcarriers

Abstract

This invention relates to the field of multi-carrier communication systems and proposes a blind RS detection method based on the similarity of adjacent subcarriers. It aims to solve the problem of high network signaling overhead caused by high-frequency RS signal transmission in dense, large-scale constellation scenarios, eliminating the need to rely on higher-layer signaling and dynamic control signaling to indicate the RS signal pattern. The method first obtains the estimated frequency response sequence of the subcarrier channel corresponding to the RS symbol. Then, through N parallel processing units, it performs differential, modulus-square, and accumulation operations on the N RS patterns supported by the system to obtain the frequency response differential power sum of each pattern. Finally, it retrieves the branch corresponding to the minimum value, and the associated RS pattern is the detection result. This invention designs two implementation schemes: parallel accumulation and sequential accumulation. The former improves detection efficiency, while the latter has low logic resource consumption and is easy to implement in hardware. It is applicable to various multi-carrier systems such as cellular mobile communication, satellite mobile communication, and non-terrestrial network communication.

Description

Technical Field

[0001] This invention relates to the field of multi-carrier communication system applications, and proposes a blind RS detection method based on the similarity of adjacent subcarriers, which is suitable for cellular mobile communication systems, broadband wireless access systems, digital broadcasting systems, and especially suitable for non-terrestrial network satellite mobile communication systems. Background Technology

[0002] Taking the convergence of satellite and terrestrial technologies as an opportunity, 3GPP has incorporated satellite components into cellular mobile communication systems to provide global mobile communication services. Its NTN technical specifications have gained widespread recognition in the satellite industry, making multi-carrier communication technologies, represented by Orthogonal Frequency Division Multiplexing (OFDM), one of the mainstream technologies for satellite internet. In multi-carrier communication systems, channel measurements of communication links are mainly based on reference signals (RS). For example, the signal-to-interference-plus-noise ratio (SINR) of the link is measured based on the demodulation reference signal (DM-RS) in the synchronization signal block (SSB), and the channel transmission characteristics (CQI / RI / PMI) of the link are measured based on the channel state information reference signal (CSI-RS).

[0003] With the rapid and large-scale deployment of satellite internet, the number of satellites visible simultaneously to ground terminals will surge to hundreds. Due to the high-speed movement of satellite nodes, the link quality and connection relationship between ground terminals and satellite nodes dynamically change. Therefore, technologies such as link adaptation and mobility management based on measurement feedback mechanisms are needed to ensure the establishment and maintenance of optimal connection relationships between ground terminals and satellite nodes. However, this will expose the satellite network to severe signaling storm problems. Analyzing only from the perspective of measurement feedback mechanisms, the RS pattern contains signaling fields such as time-domain location, frequency-domain density, symbol length, and number of additional pilots. These need to be jointly indicated by higher-layer signaling (such as RRC configuration) and dynamic control signaling (such as DCI in PDCCH). The terminal must first decode the above signaling to determine the time-frequency resource location of the RS, and then extract the RS for link channel quality measurement.

[0004] As mentioned earlier, the dynamic nature of the link quality and connection relationship between ground terminals and satellite nodes will force RS signals to be transmitted at high frequencies, resulting in a surge in network overhead and forcing satellite networks to face serious signaling storm problems.

[0005] To address the aforementioned issues, the industry has proposed a blind RS pattern detection scheme, whereby the terminal infers the RS time-frequency pattern directly from the characteristics of the received signal without relying on DCI or higher-layer signaling indications. However, existing blind detection technologies generally suffer from high complexity and slow detection speed. Especially in NTN scenarios, terminals (such as satellite terminals and UAV-borne terminals) are limited by size, power consumption, and computing power, making it difficult to practically deploy highly complex blind detection schemes, which severely restricts the widespread application of blind detection technology in non-terrestrial networks. Therefore, developing a low-complexity, high-speed RS pattern blind detection method and device that can quickly and accurately identify RS time-frequency resource configurations without relying on signaling indications, and adapting to diverse application scenarios in both terrestrial and non-terrestrial networks, has become an urgent technical problem to be solved in this field. Summary of the Invention

[0006] Based on the above background, this invention proposes a blind RS detection method based on the phase characteristics of adjacent subcarriers. Although this method has a certain signal-to-noise ratio cost compared with RS sequence detection methods based on SNR estimation and extremum search, it has a much lower cost and complexity than traditional algorithms, making it more suitable for the deployment and promotion of low-cost, dense, and large-scale constellations.

[0007] The technical solution adopted in this invention is as follows:

[0008] A blind RS detection method based on the similarity of neighboring subcarriers, the method comprising:

[0009] S1. After the receiver completes the frame, half-frame, time slot and symbol synchronization operations, it performs a fast Fourier transform on the received OFDM symbol sequence with time slot as the granularity to obtain the estimated value sequence of subcarrier channel frequency response corresponding to the RS symbol to be detected in the time-frequency resource grid corresponding to the time slot.

[0010] S2, for the N RS patterns supported by the system, the N parallel processing units are respectively directed to the blind detection operation. Each parallel processing unit corresponds to one RS pattern. The frequency response estimation sequence of the subcarrier channel of the corresponding branch is sequentially subjected to differential calculation, modulus square calculation and accumulation operation between adjacent subcarriers to obtain the frequency response differential power of the corresponding RS pattern.

[0011] S3 performs a minimum value search on the frequency response differential power output of the N parallel processing units. The RS pattern associated with the branch corresponding to the minimum value is the blind detection result.

[0012] In S2, the frequency response estimation sequence of the corresponding branch subcarrier channel is sequentially subjected to differential calculation, modulus square calculation, and accumulation operation between adjacent subcarriers to obtain the frequency response differential power sum of the corresponding RS pattern. The implementation scheme of parallel accumulation and summation of the modulus values ​​of the frequency response difference between adjacent subcarriers is adopted. The specific steps are as follows:

[0013] S2.11, the first The sequence of subcarrier channel frequency response estimates corresponding to the parallel processing units is as follows Calculate the difference between adjacent terms in turn. Obtain the channel frequency response difference sequence Where n is the total number of RS symbols to be detected. , where i represents the branch changes of the parallel processing unit;

[0014] S2.12, for each term in the channel frequency response differential sequence Calculate the square of the modulus separately, and obtain ;

[0015] S2.13, the N parallel processing units synchronously start the accumulation operation, each summing all the modulus square results of its corresponding branch to obtain the frequency response differential power and the sum of the N RS patterns. This enables fully parallel blind detection of N types of RS patterns.

[0016] In S2, the frequency response estimation sequence of the corresponding branch subcarrier channel is sequentially subjected to differential calculation, modulus square calculation, and accumulation operation between adjacent subcarriers to obtain the frequency response differential power sum of the corresponding RS pattern. The implementation scheme adopts the sequential accumulation and summation of modulus values ​​of frequency response differences between adjacent subcarriers. The specific steps are as follows:

[0017] S2.21, will the first Each estimate in the subcarrier channel frequency response estimate sequence corresponding to the parallel processing unit is separated into its real and imaginary parts. The real part is... The imaginary part is , serving as the index of the frequency response estimate in the subcarrier channel frequency response estimate sequence; where i represents the branch change of the parallel processing unit;

[0018] S2.22, by performing a one-cycle delay on the real and imaginary parts using a register, the real part is obtained as follows: The imaginary part is The difference between the delayed real part and the original real part, and the difference between the delayed imaginary part and the original imaginary part, are calculated to obtain the real part difference of the frequency response difference between adjacent subcarriers. Difference between imaginary and real parts ;

[0019] S2.23, squaring the real and imaginary differences respectively, yields the power of the real difference. power difference between the imaginary part and the power ;

[0020] S2.24, sum the real part difference power and the imaginary part difference power to obtain the frequency response difference power of a single group of adjacent subcarriers. ;

[0021] S2.25, the frequency response difference power of all single-group adjacent subcarriers is sequentially accumulated by the accumulator until the power summation of all adjacent subcarrier pairs is completed, and the frequency response difference power sum of the corresponding RS pattern is obtained.

[0022] The beneficial effects of this invention are as follows:

[0023] This invention discloses a blind RS detection method based on the similarity of adjacent subcarriers, which solves the problem of high network signaling overhead caused by high frequency transmission of RS signals in dense large-scale constellation scenarios, and eliminates the need to rely on higher-layer signaling and dynamic control signaling to indicate the pattern of RS signals. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating the implementation scheme of the present invention, which uses the modulus of the frequency response difference of adjacent subcarriers to calculate and sum the values ​​in parallel.

[0025] Figure 2 The flowchart of the implementation scheme of this invention is based on the sequential accumulation and summation of the modulus values ​​of the frequency response differences of adjacent subcarriers. Detailed Implementation

[0026] To more clearly illustrate the present invention, the following description, in conjunction with embodiments and accompanying drawings, further clarifies the invention. Those skilled in the art should understand that the specific descriptions below are illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0027] This invention discloses a blind RS detection method based on the similarity of neighboring subcarriers, the method comprising:

[0028] S1. After the receiver completes the frame, half-frame, time slot and symbol synchronization operations, it performs a fast Fourier transform on the received OFDM symbol sequence with time slot as the granularity to obtain the estimated value sequence of subcarrier channel frequency response corresponding to the RS symbol to be detected in the time-frequency resource grid corresponding to the time slot.

[0029] S2, for the N RS patterns supported by the system, the N parallel processing units are respectively directed to the blind detection operation. Each parallel processing unit corresponds to one RS pattern. The frequency response estimation sequence of the subcarrier channel of the corresponding branch is sequentially subjected to differential calculation, modulus square calculation and accumulation operation between adjacent subcarriers to obtain the frequency response differential power of the corresponding RS pattern.

[0030] S3 performs a minimum value search on the frequency response differential power output of the N parallel processing units. The RS pattern associated with the branch corresponding to the minimum value is the blind detection result.

[0031] S2 can be implemented by parallel accumulation and summation of the modulus values ​​of the frequency response difference between adjacent subcarriers, such as... Figure 1 As shown, the specific steps are as follows:

[0032] S2.11: The differential calculation between adjacent subcarriers is specifically as follows: The sequence of subcarrier channel frequency response estimates corresponding to the parallel processing units is as follows (where n is the total number of RS symbols to be processed), calculate the difference between adjacent terms in turn. ( ), to obtain the channel frequency response difference sequence ;

[0033] S2.12: Modulus Square Calculation: For each term in the channel frequency response difference sequence ( ) Calculate the square of the modulus respectively, and obtain ;

[0034] S2.13: The N parallel processing units synchronously start the accumulation operation, each summing all the modulus square results of its corresponding branch to obtain the frequency response differential power and the sum of the N RS patterns. This enables fully parallel blind detection of N types of RS patterns.

[0035] S2 can also be implemented by sequentially accumulating and summing the modulus values ​​of the frequency response differences of adjacent subcarriers, such as... Figure 2 As shown, the specific steps are as follows:

[0036] S2.21: The first Each estimate in the subcarrier channel frequency response estimate sequence corresponding to the parallel processing unit is separated into its real and imaginary parts. The real part is... The imaginary part is , serving as the index of the frequency response estimate in the subcarrier channel frequency response estimate sequence;

[0037] S2.22: By performing a one-cycle delay on the real and imaginary parts using registers, the real part is obtained as follows: The imaginary part is The difference between the delayed real part and the original real part, and the difference between the delayed imaginary part and the original imaginary part, are calculated to obtain the real part difference of the frequency response difference between adjacent subcarriers. Difference between imaginary and real parts ;

[0038] S2.23: Squaring the real and imaginary differences respectively, we obtain the power of the real difference. power difference between the imaginary part and the power ;

[0039] S2.24: Summing the real and imaginary difference power yields the frequency response difference power of a single set of adjacent subcarriers. ;

[0040] S2.25: The frequency response difference power of all single-group adjacent subcarriers is sequentially accumulated using an accumulator until the power of all adjacent subcarrier pairs is summed, thus obtaining the frequency response differential power of the corresponding RS pattern. This solution consumes low logic resources and is easy to implement in FPGA or ASIC chip hardware.

[0041] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A blind RS detection method based on the similarity of neighboring subcarriers, characterized in that, The method includes: S1. After the receiver completes the frame, half-frame, time slot and symbol synchronization operations, it performs a fast Fourier transform on the received OFDM symbol sequence with time slot as the granularity to obtain the estimated value sequence of subcarrier channel frequency response corresponding to the RS symbol to be detected in the time-frequency resource grid corresponding to the time slot. S2, for the N RS patterns supported by the system, the N parallel processing units are respectively directed to the blind detection operation. Each parallel processing unit corresponds to one RS pattern. The frequency response estimation sequence of the subcarrier channel of the corresponding branch is sequentially subjected to differential calculation, modulus square calculation and accumulation operation between adjacent subcarriers to obtain the frequency response differential power of the corresponding RS pattern. S3 performs a minimum value search on the frequency response differential power sum output by the N parallel processing units. The RS pattern associated with the branch corresponding to the minimum value is the blind detection result.

2. The RS blind detection method based on the similarity of adjacent subcarriers according to claim 1, characterized in that, In S2, the frequency response estimation sequence of the corresponding branch subcarrier channel is sequentially subjected to differential calculation, modulus square calculation, and accumulation operation between adjacent subcarriers to obtain the frequency response differential power sum of the corresponding RS pattern. The implementation scheme of parallel accumulation and summation of the modulus values ​​of the frequency response difference between adjacent subcarriers is adopted. The specific steps are as follows: S2.11, the first The sequence of subcarrier channel frequency response estimates corresponding to the parallel processing units is as follows Calculate the difference between adjacent terms in sequence. Obtain the channel frequency response difference sequence Where n is the total number of RS symbols to be detected. , where i represents the branch changes of the parallel processing unit; S2.12, for each term in the channel frequency response differential sequence Calculate the square of the modulus separately, and obtain ; S2.13, the N parallel processing units synchronously start the accumulation operation, each summing all the modulus square results of its corresponding branch to obtain the frequency response differential power and the sum of the N RS patterns. This enables fully parallel blind detection of N types of RS patterns.

3. The RS blind detection method based on the similarity of adjacent subcarriers according to claim 1, characterized in that, In S2, the frequency response estimation sequence of the corresponding branch subcarrier channel is sequentially subjected to differential calculation, modulus square calculation, and accumulation operation between adjacent subcarriers to obtain the frequency response differential power sum of the corresponding RS pattern. The implementation scheme adopts the sequential accumulation and summation of modulus values ​​of frequency response differences between adjacent subcarriers. The specific steps are as follows: S2.21, will the first Each estimate in the subcarrier channel frequency response estimate sequence corresponding to the parallel processing unit is separated into its real and imaginary parts. The real part is... The imaginary part is , serving as the index of the frequency response estimate in the subcarrier channel frequency response estimate sequence; where i represents the branch change of the parallel processing unit; S2.22, by performing a one-cycle delay on the real and imaginary parts using a register, the real part is obtained as follows: The imaginary part is The difference between the delayed real part and the original real part, and the difference between the delayed imaginary part and the original imaginary part, are calculated to obtain the real part difference of the frequency response difference between adjacent subcarriers. Difference between imaginary and real parts ; S2.23, squaring the real and imaginary differences respectively, yields the power of the real difference. power difference between the imaginary part and the power ; S2.24, sum the real part difference power and the imaginary part difference power to obtain the frequency response difference power of a single group of adjacent subcarriers. ; S2.25, the frequency response difference power of all single-group adjacent subcarriers is sequentially accumulated by the accumulator until the power summation of all adjacent subcarrier pairs is completed, and the frequency response difference power sum of the corresponding RS pattern is obtained.

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