CN118234049A - Random access preamble and preamble detection method for mobile satellite communication network - Google Patents

Abstract

The invention discloses a random access preamble of a mobile satellite communication network and a preamble detection method, which provides an interleaving cascade preamble obtained by interleaving L=2 different basic sequences according to a preset sequence selection pattern in a time domain, wherein the detection method specifically comprises the following steps: s1, sampling the received signal, and compensating the common frequency offset corresponding to the beam center for the sampling sequence. S2, obtaining the estimation of the normalized decimal time offset of the received signalShift the compensated sampling sequence to the leftAnd sampling points. S3, acquiring estimation of normalized integer time offset of the received signal by adopting sequence selection pattern auxiliary cross correlation algorithmS4, estimating according to normalized decimal time offsetAnd normalized integer time offset estimationObtaining an estimate of the overall normalized time offsetCompared with the traditional technology, the application provides better performance than the traditional cascade leading design, can effectively promote the acquisition of accurate time synchronization, obviously improves the estimation performance of integer time offset and effectively reduces the false detection rate.

Description

Random access preamble and preamble detection method for mobile satellite communication network

Technical Field

The invention relates to the technical field of mobile satellite communication, in particular to a random access preamble and a preamble detection method of a mobile satellite communication network.

Background

The aeronautical communication system and mobile satellite network (Mobile Satellite Network, MSN) are the most promising candidates for being highly complementary in terms of coverage to the terrestrial network (TERRESTRIAL NETWORK, TN). Particularly in MSNs, the distance between a User Equipment (UE) and a Base Station (BS) typically deployed on a satellite is much larger than in TN. This results in significant propagation delay.

From the UE's perspective, the total delay is the sum of the common propagation delay and the UE-specific delay of all UEs in the cell. Once the common delay is broadcast on the system information block defined in the third generation partnership project 5G standard, the UE may compensate for it prior to its initial Random Access (RA) procedure. The BS may calculate and cancel a common doppler shift relative to a reference point (e.g., cell center). Thus, during RA in MSNs, only UE-specific doppler shift will affect preamble detection.

The preamble is one of the key design goals in RA activity. With a larger subcarrier spacing (Subcarrier Spacing, SCS), the impact of Frequency Offset (FO) on the correlation peak can be significantly reduced, so that the accuracy of the Time Offset (TO) estimation can be improved, and with a larger number of repetitions, the link budget can be improved and the duration of the preamble can be made longer, thereby extending the range of TO that can be estimated.

There are some concatenated preamble based RA schemes in the prior art, such as a cyclic shift based concatenated preamble (CYCLIC SHIFT Based Cascaded Preamble, CS-CP) and a repetition based concatenated preamble (Repetition Based Cascaded Preamble, R-CP). However, both of the above schemes cannot achieve accurate estimation of ITO at low Signal-to-noise Ratio (SNR).

In view of the above needs and the drawbacks of the prior art, the present application proposes a random access preamble and preamble detection method for a mobile satellite communication network.

Disclosure of Invention

The invention provides a random access preamble and a preamble detection method of a mobile satellite communication network, which are used for obtaining the correlation gain of a sequence selection pattern, providing better performance than the traditional cascade preamble design, effectively promoting the acquisition of accurate time synchronization, remarkably improving the estimation performance of integer time offset and effectively reducing the false detection rate.

The primary purpose of the invention is to solve the technical problems, and the technical scheme of the invention is as follows:

The first aspect of the present invention provides a random access preamble of a mobile satellite communication network, specifically: selecting staggered cascade preambles obtained by staggered arrangement of patterns with L=2 different basic sequences according to a preset sequence in a time domain; wherein the preset sequence selection pattern is a binary synchronous sequence, and the preamble consists of a useful part of a signal and a Cyclic Prefix (CP) with a duration of T _cp.

Further, the useful part of the signal is a useful signal s _u(t)(0≤t＜T_u with a duration of T _u =kt, expressed as:

s_u(t)＝s_k(t-KT),kT≤t＜(k+1)T,k＝0,…,K-1 (1)

wherein s _k (T) (0.ltoreq.t < T) is the kth component signal, Is the duration of the component signal, Δf is the subcarrier spacing; the general expression of orthogonal frequency division multiplexing (Discrete Fourier transform spread Orthogonal Frequency Division Multiplexing,DFTS-OFDM),s_k(t)(k＝0,…,K-1) using discrete fourier transform spreading in an enhanced Physical Random access channel (Physical Random ACCESS CHANNEL, PRACH) is:

Where x _k N (n=0, …, N-1) is the kth time domain discrete component sequence, and the positive integer γ represents the starting position of N enhanced physical random access channel subcarriers in the frequency domain.

According to the technical characteristics, the input of the orthogonal frequency division multiplexing module of the discrete Fourier transform spread at the transmitter end is a preamble sequence formed by K component sequences.

Further, each component sequence is L candidate base sequencesOne, and is determined by the sequence selection pattern (Sequence Selection Pattern, SSP) u [ K ] (k=0, …, K-1) as:

For k ₀∈{0,…,K-1},u[k₀ epsilon {0, …, L-1} is an index of a candidate base sequence.

According to the technical feature described above, this means that the selection of the kth component sequence is influenced by the kth element of the sequence selection pattern.

Further, after adding the cyclic prefix, the transmitted signal is:

Wherein T _d＝T_cp+T_u is the total duration of the transmitted signal, < - > _X represents the modulo X operation, satisfying < X > _X＝＜x+X>_X, and the preamble received by the satellite base station under the line-of-sight channel is:

Where ρ is the average power of the received signal, τ is the time offset, f _d is the Doppler shift, θ is the random phase, w (T) is the additive Gaussian white noise with power spectral density N ₀, and T ₀ and T _rw are the start time and duration of the receive window, respectively.

The second aspect of the present invention provides a preamble detection method, which specifically includes the following steps:

S1, sampling a received signal, and compensating a common frequency offset corresponding to a beam center for a sampling sequence;

s2, obtaining the estimation of the normalized decimal time offset of the received signal Shifting the compensated sample sequence to the left/>Sampling points;

S3, acquiring estimation of normalized integer time offset of the received signal by adopting sequence selection pattern auxiliary cross correlation algorithm

S4, shifting according to normalized decimal timeAnd normalized integer time offset estimation/>Obtaining an estimate of the overall normalized time offset/>

Further, in step S1, during the process of sampling the received signal, the detection window includes N _dw sampling points, and all the sampling points are uniformly distributed to K sub-windows; the receive window starts at T ₀＝T_cp, with a duration of T _rw = (k+1) T, and the received signal y (T) is sampled at t=nt _s+T_cp(n＝0,…,N_rw -1), resulting in:

y_s[n]＝y(nT_s+T_cp),n＝0,…,N_rw-1 (6)

Wherein, For the number of sampling points of the receiving window,/>For the sampling interval, N _s is the fast fourier transform (Fast Fourier Transform, FFT) size, corresponding to the number of sub-window sampling points.

Further, the expression for compensating the common frequency offset corresponding to the beam center for the sampling sequence is:

y_k[n]＝y_c[n+kN_s],n＝0,…,N_s-1 (9)

where y _k [ n ] denotes the portion of the compensated sample sequence that falls within the kth (k=0, …, K-1) sub-window.

Further, the step S3 specifically includes: for the case H _dr where the roots of the two base sequences are different, the individual power delay profile (Power Delay Profile, PDP) is calculated as:

Λ_l,k[n]＝|c_l,k[n]|²,l＝0,1,k＝0,…,K-1,n＝0,…,N_d-1, (10)

Wherein c _l,k[n](n＝0,…,N_d -1) is a cross-correlation function, Is the inverse fast fourier transform size (INVERSE FFT, IFFT) applied to PDP computation,/>Represents a minimum integer not less than x;

Wherein, And/>By respectively at/>And/>The tail is filled with N _d -N zeros, and the local frequency domain sequence/>Is/>N-point discrete Fourier transform (Discrete Fourier Transform, DFT),/>By extracting from Y _k[m](m＝0,…,N_s -1) the N symbols starting from index gamma, Y _k [ m ] is the N _s -point fast Fourier transform of Y _k [ N ]; the total power delay profile is generated by:

Wherein, Is the first cumulative power delay spectrum, H _sr,/>, for the case where the roots of the two base sequences are identicalIs/>Is calculated/>, using the first ₀ (l ₀ =0 or 1) cumulative single power delay profileThe method comprises the following steps:

wherein R (·) represents a numerical rounding operator; obtaining The index of the maximum value of (c) is:

σ ²＝N₀ B is the noise power, where b=n _s Δf is the system bandwidth if The preamble exists where λ is a predefined threshold that depends on the target false alarm rate, and the normalized fractional time offset is estimated as:

and moving the compensated sample sequence back The sampling points compensate for their fractional time offsets.

Further, the step S3 specifically includes: calculating K shifted subsequencesTime-domain cross-correlation of each of the L candidate base sequences as shown in the following equation:

wherein the local time domain sequence (N=0, …, N _s -1) is/>N _s point inverse fast Fourier transform,/>By respectively at/>Is obtained by filling y-1 and N _s -N-y +1 zeros at the beginning and end of (c).

Further, the robustness of the detection is maximized using a sequence selection pattern as shown in the following equation:

Wherein, U [ K ] = - (-1) ^u[k] (k=0, …, K-1) is an effective sequence selection pattern generated by converting {0,1} to { ±1}, v >Representing the detected sequence selection pattern; since the a priori parameter T _cp should be chosen to satisfy τ < T _cp, there is ε _i≤K_cp -1, thereby setting the length of ψi in equation (19) to K _cp; estimating a normalized integer time offset by searching for a maximum value of ψ [ i ]:

The estimation of the overall normalized time offset in step S4 is shown.

Compared with the prior art, the technical scheme of the invention has the beneficial effects that:

The invention provides a random access preamble and a preamble detection method of a mobile satellite communication network, the preamble based on a sequence selection pattern can provide better performance than the traditional cascade preamble design, and the sequence selection pattern of the staggered cascade preamble scheme is composed of binary synchronous sequences, so that the acquisition of accurate time synchronization is promoted; the auxiliary cross-correlation algorithm based on the sequence selection pattern can remarkably improve the estimation performance of the integer time offset and effectively reduce the false detection rate.

Drawings

Fig. 1 is a schematic diagram of a random access preamble of a mobile satellite communication network according to the present invention.

Fig. 2 is a schematic diagram of a detection window of a received signal according to an embodiment of the present invention.

Fig. 3 is a flowchart of a preamble detection method according to the present invention.

FIG. 4 is a graph showing MDR/RASR performance of I-CPs of different m-SSPs in one embodiment of the present invention.

Fig. 5 shows MDR/RASR performance for different study protocols in one example.

FIG. 6 is a schematic diagram of an experimental system in an embodiment of the invention.

Detailed Description

So that the manner in which the above recited objects, features and advantages of the present invention can be understood in detail, a more particular description of the invention, briefly summarized below, may be had by reference to the appended drawings. It should be noted that, without conflict, the embodiments of the present invention and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.

Before describing the specific technical scheme, the abbreviations of proper nouns related to the invention are specifically described first:

a mobile satellite network (Mobile Satellite Network, MSN);

-a ground network (TERRESTRIAL NETWORK, TN);

User Equipment (UE);

base Station (BS);

Third generation partnership project (The Third Generation Partnership Project,3 GPP);

System information blocks (System Information Block, SIBs);

Random Access (RA);

subcarrier spacing (Subcarrier Spacing, SCS);

non-terrestrial networks (Non-TERRESTRIAL NETWORK, NTN);

Enhanced Physical Random access channel (Physical Random ACCESS CHANNEL, PRACH);

frequency Offset (FO);

a cyclic shift based concatenation preamble (CYCLIC SHIFT Based Cascaded Preamble, CS-CP);

based on repeated concatenation preambles (Repetition Based CascadedPreamble, R-CP);

Time Offset (TO);

Fractional TO (FTO);

integer TO (intelger TO, ITO);

signal-to-noise Ratio (SNR);

a sequence selection pattern (Sequence Selection Pattern, SSP);

Staggered cascade preamble (INTERLEAVED CASCADEDPREAMBLE, I-CP);

SSP assisted Cross-correlation (SSP-CC) algorithm;

False positive rate (MissedDetection Rate, MDR);

cyclic Prefix (CP);

Discrete fourier transform spread orthogonal frequency division multiplexing (Discrete Fourier transform spread Orthogonal Frequency Division Multiplexing, DFTS-OFDM);

Additive white Gaussian Noise (ADDITIVE WHITE Gaussian Noise, AWGN);

A fast fourier transform (Fast Fourier Transform, FFT);

a power delay profile (Power Delay Profile, PDP);

An inverse fast fourier transform size (INVERSE FFT, IFFT);

discrete fourier transform (Discrete Fourier Transform, DFT);

double-transition element (DSE);

single-transition element (SSE);

Selecting a pattern (m-sequence Based SSP, m-SSP) based on the sequence of m-sequences;

Random Access Success Rate (RASR);

Tag-based concatenation preamble (Label Based Cascaded Preamble, L-CP).

Example 1

As shown in fig. 1, the present invention provides a random access preamble of a mobile satellite communication network, specifically: selecting staggered cascade preambles obtained by staggered arrangement of patterns with L=2 different basic sequences according to a preset sequence in a time domain; wherein the preset sequence selection pattern is a binary synchronous sequence, and the preamble consists of a useful part of a signal and a cyclic prefix with the duration of T _cp.

It is noted that when the user equipment UE attempts to access the base station BS, it transmits a preamble selected from the predefined set of preambles. When detecting the presence of the preamble, the BS estimates the time offset TO of the UE and transmits an RA response with a timing advance instruction.

Fig. 1 shows the structure of the proposed preamble, which consists of a useful part of the signal and a cyclic prefix of duration T _cp. Useful signal s _u(t)(0≤t＜T_u of duration T _u = KT) is defined as:

s_u(t)＝s_k(t-KT),kT≤t＜(k+1)T,k＝0,…,K-1 (1)

wherein s _k (T) (0.ltoreq.t < T) is the kth component signal, Is the duration of the component signal and Δf is the SCS. The general expression for using DFTS-OFDM in PRACH, s _k (t) (k=0, …, K-1) is:

Where x _k N (n=0, …, N-1) is the kth time domain discrete component sequence, and the positive integer γ represents the starting position of N PRACH subcarriers in the frequency domain. Thus, the input to the DFTS-OFDM module at the transmitter end is a preamble sequence formed of K component sequences.

In addition, each component sequence is L candidate base sequencesOne, and is determined by SSPu [ K ] (k=0, …, K-1) as:

For k ₀∈{0,…,K-1},u[k₀ epsilon {0, …, L-1} is an index of a candidate base sequence. This means that the choice of the kth component sequence is affected by the kth element of the SSP. The base sequence may be a PRACH sequence or any cyclically shifted corresponding sequence thereof. Typically, the PRACH sequence is a root Zadoff-Chu (ZC) ZC sequence of length N.

After adding the CP, the transmitted signal becomes:

Where T _d＝T_cp+T_u is the total duration of the transmitted signal, < - > _X represents a modulo X operation, satisfying < X > _X＝<x+X>_X. In the line-of-sight channel, the preamble signal received by the satellite BS is:

Where ρ is the average power of the received signal, τ is TO, f _d is the doppler shift, θ is the random phase, w (T) is the additive white gaussian noise with power spectral density N ₀, and T ₀ and T _rw are the start time and duration of the receive window, respectively.

Note that the proposed SSP framework includes various cascading preamble designs that exist. The simple R-CP structure employs all zero SSP, [0, …,0], which means that the selected base sequence with index 0 is applied to the preamble all component sequences. In this case, SSP will remain unchanged even after cyclic shifting, and therefore cannot enjoy any SSP shift gain in the fractional time offset FTO detection window. Furthermore, during the detection, an additional window needs TO be set for the integer TO estimation. On the other hand, in a cyclic shift based concatenated preamble CS-CP scheme with SSP 0, …, K-1, the first component sequence uses a base sequence with index 0, while the other component sequences use cyclic shifted versions of the base sequence with indices from 1 to K-1. However, CS-CP performs ITO estimation on a single sub-window basis, and thus cannot achieve joint processing gain for the entire SSP.

To overcome the above problems, the present invention proposes a new preamble format under SSP framework: the cascade preamble I-CP is interleaved. I-CP is formed by interleaving l=2 different base sequences in the time domain, the arrangement rule of which is determined by a specific sequence selection pattern SSP, which in this case is a binary synchronization sequence. For convenience, H _dr is used to denote the case where the roots of the two base sequences are different. Furthermore, the case where two base sequences share the same root but have different cyclic shifts is represented by H _sr, i.e(N=0, …, N-1), where δ is a predefined shift. The accurate I-CP based ITO estimation may be achieved by an SSP-assisted cross correlation algorithm SSP-CC detector as will be described below.

Example 2

Based on the above embodiment 1, in conjunction with fig. 2-3, this embodiment describes in detail a second aspect of the present invention, a preamble detection method.

As shown in fig. 3, the method comprises the following steps:

S1, sampling a received signal, and compensating a common frequency offset corresponding to a beam center for a sampling sequence;

s2, obtaining the estimation of the normalized decimal time offset of the received signal Shifting the compensated sample sequence to the left/>Sampling points;

S3, acquiring estimation of normalized integer time offset of the received signal by adopting sequence selection pattern auxiliary cross correlation algorithm

S4, shifting according to normalized decimal timeAnd normalized integer time offset estimation/>Obtaining an estimate of the overall normalized time offset/>

In a specific embodiment, the received signal is shown in fig. 2, where the detection window contains N _dw sampling points, which can be uniformly distributed to K sub-windows. In this example, k=7 is set and SSP is chosen to be 1,0,1,1,1,0,0, which is an m-sequence denoted as u ₀ K (k=0, …, 6). The receive window starts at T ₀＝T_cp and has a duration of T _rw = (k+1) T. The received signal y (t) is sampled at t=nt _s+T_cp(n＝0,…,N_rw -1), resulting in:

y_s[n]＝y(nT_s+T_cp),n＝0,…,N_rw-1 (6)

Wherein, For the number of sampling points of the receiving window,/>For the sampling interval, N _s is the size of the fast fourier transform, and corresponds to the number of sub-window sampling points.

The normalized TO expressed in terms of the number of delayed sampling points can be written as:

ε＝ε_iN_s+ε_f (7)

Wherein, Is normalized ITO,/>Represents a maximum integer not greater than x,/>Is normalized FTO. To reduce the effect of the FO, the receiver compensates for the common FO corresponding to the beam center:

the part of the compensated sequence that falls within the kth (k=0, …, K-1) sub-window is:

y_k[n]＝y_c[n+kN_s],n＝0,…,N_s-1 (9)

The proposed SSP assisted Cross-correlation (SSP-CC) algorithm includes two steps, namely first estimating FTO and then estimating ITO. In obtaining an estimated version of ε _f After that, the compensated sequence is shifted left/>And sampling points. Since ε _f can range from 0 to N _s -1, it is desirable to set N _rw＝N_dw+N_s to accommodate all possible values of ε _f.

First, consider the case H _dr where the PDP alone is calculated as:

Λ_l,k[n]＝|c_l,k[n]|²,l＝0,1,k＝0,…,K-1,n＝0,…,N_d-1, (10)

Wherein c _l,k[n](n＝0,…,N_d -1) is a cross-correlation function, Is the IFFT size applied to PDP calculation,/>Representing a minimum integer not less than x. In addition, c _l,k [ n ] can be calculated as follows:

Wherein, And/>By respectively at/>And/>The tail is filled with N _d -N zeros, and the local frequency domain sequence/>Is/>N-point DFT of (d). Furthermore,/>By extracting the N symbols from Y _k[m](m＝0,…,N_s -1) starting with index gamma, Y _k [ m ] is the N _s -point FFT of Y _k [ N ]. To maximize the chance of identifying peaks associated with FTO, a total PDP is generated by:

Wherein the method comprises the steps of Is the first cumulative PDP, given by:

Second, for case H _sr, note Is/>Is used for cyclic shift of (a). Therefore, it is possible to calculate/>, using only the first ₀ (l ₀ =0or1) cumulative PDPsThe method comprises the following steps:

Wherein R (·) represents a numerical rounding operator. In this case, the number of PRACH sequences may be reduced as compared to case H _dr. In addition, no calculation is required Thereby reducing the computational cost. Note that for both cases H _sr and H _dr, when the number of p (p=0or1) in SSP is much larger than the number of 1-p, the/>, can be simply setTo avoid introducing more noise into the overall PDP unnecessarily.

Then, obtainThe index of the maximum value of (c) is:

Let σ ²＝N₀ B be the noise power, where b=n _s Δf be the system bandwidth. If it is An alarm occurs meaning that the preamble is considered to exist, where lambda is a predefined threshold that depends on the target false alarm rate. Thus, the normalized FTO estimate is:

Based on equation (16), the compensated sample sequence can be shifted back The sampling points compensate their FTO. The K (k=0, …, K-1) subsequence after shifting is:

Then, the time-domain cross-correlation of each of the K shifted sub-sequences with each of the L candidate base sequences is calculated as follows:

wherein the local time domain sequence Is/>Is an N _s point IFFT of (a),By respectively at/>Is obtained by filling y-1 and N _s -N-y +1 zeros at the beginning and end of (c). If/>With sufficient accuracy, y' _k [ n ] will be equal to/>Alignment, where z=u [ < k-epsilon _i>_K ] and has C _z[k]＞＞C_1-z [ k ].

Next, SSP is utilized to maximize the robustness of the detection. In particular, a cross-correlation function associated with SSP may be used to indicate ITO, which is:

Wherein, U [ K ] = - (-1) ^u[k] (k=0, …, K-1) is an effective SSP generated by converting {0,1} to { ±1 }/>Representing the detected SSP, is given by the following formula:

Note that since a priori parameter T _cp should be chosen that satisfies τ < T _cp, there is ε _i≤K_cp -1, so the length of ψi in equation (19) is set to K _cp instead of K.

By equation (20), the difference between the correlation peak and the normal value can be maximized. Due to channel effects and preamble structure, it is possible toTreated as U [ k ] after interference and cyclic shift. Thus, normalized ITO can be estimated by searching for the maximum value of ψ [ i):

the overall normalized time offset is then estimated as:

It should be noted that due to its excellent autocorrelation properties, the m-sequence is a good candidate for SSP of the I-CP scheme, which helps to minimize ITO estimation errors. However, the performance of the TO estimation requires the balanced quality of the FTO and ITO estimation, as described below.

For a given element u [ K ₀](k₀ E {0, …, K-1} ] of SSP, if u [ K ₀]≠u[<k₀-1>_K ] and u [ K ₀]≠u[<k₀+1>_K ], it is called a Double-transition element (Double-SWITCHING ELEMENT, DSE); if u [ < k ₀-1>_K]≠u[<k₀+1>_K ], it is referred to as Single transition element (SSE). Assuming that the received signal is undistorted and the maximum value of Λ _z,k[n](n＝0,…,N_d -1) when epsilon _f = 0 is denoted as P, where z = u [ < k-epsilon _i>_K ]. The kth detection window may contain two sequences derived from different base sequences due to the presence of transitions in the element values in FTO and SSP, as shown in y ₀[n],y₂[n],y₃[n],y₄[n](n＝0,…,N_s -1 of fig. 2). For case H _dr, this event will result in two peaks appearing in Λ _0,k [ n ] and Λ _1,k [ n ], respectively; for case H _sr, this event will cause two peaks to appear atIs a kind of medium. More specifically, as ε _f increases, the sum of the two peaks first assumes a decreasing trend and then bounces back. Furthermore, when/>Both peaks are approximately equal to/>And their sum reaches a minimum value/>

As shown in FIG. 2, SSPs may be constructed from a typical m-sequence. Order theRepresents an M-sequence of length m=2 ^a -1, where positive integers a and b represent the series and octal feedback coefficients, respectively. However, if such an SSP is modified, for example, by reversing the first element of the sequence u ₀ [ k ], i.e., changing u ₀ [0] to 1-u ₀ [0], the number of transitions in the element values in the SSP is reduced by 2. In this case, the maximum value of the total PDP may be increased, thereby improving the performance of FTO estimation. The modified SSP (m-sequence Based SSP, m-SSP) based on m-sequences is noted asWhere Φ is the set consisting of the index of the inverted elements.

The inversion operation of DSE described above is advantageous for alarm triggering and FTO estimation. However, this is detrimental to ITO estimation due to reduced autocorrelation performance of SSP. For SSE, inversion only results in a decrease in TO estimation success rate, becauseWithout increasing the maximum value of ψi (i=0, …, K _cp -1) and the interference peak becomes large. Furthermore, given the number of inverted DSEs, a balanced 0 and 1 number of m-SSPs have better autocorrelation performance than an unbalanced m-SSP. Based on the inversion rules and the limited number of DSEs, several candidate m-SSPs can be generated from the original m-sequence. Through simulation, the choice of m-SSP that trades off FTO and ITO estimation performance can be achieved empirically.

It should be noted that the performance of the detector of the existing CS-CP scheme is easily affected by noise and FO, and the timing detection method of the R-CP scheme including two consecutive steps may cause a problem of unbalanced detection performance of ITO and FTO. None of the above schemes can achieve accurate estimation of ITO at low signal to noise ratios.

According to the technical characteristics, compared with the prior art, the invention has the following characteristics:

The present invention proposes a generic preamble design framework using SSP-based preambles consisting of a series of component sequences, the order of which can be arranged according to different design objectives. The new mechanism is helpful to obtain SSP-oriented correlation gain, and provides better performance than the traditional cascade preamble design; unlike most existing preamble designs, which typically have poor ITO estimation performance, the present invention proposes a new I-CP in which SSP consists of a binary sync sequence. This effectively facilitates the acquisition of accurate time synchronization.

Furthermore, the invention designs a preamble detection method for the proposed I-CP. With the help of the proposed SSP auxiliary cross correlation algorithm, ITO estimation performance can be remarkably improved, and false detection rate is effectively reduced;

Example 3

The effectiveness and advancement of the present invention are further described below in connection with simulation results and analysis of specific embodiments, as shown in fig. 4-6.

In this embodiment, the main simulation parameters are shown in table 1. The present embodiment considers the edge beam of the LEO satellite, assuming that the satellite and the uniformly distributed UEs move in the same plane, and the angular velocity directions of the satellite and the UEs are opposite.

Table 1 simulation parameters

In FIG. 4, the performance of I-CPs of different candidate m-SSPs is evaluated. The m-SSP used isWherein/>Φ₁＝{21},Φ₂＝{10,21},Φ₃＝{10,18,21},Φ₄＝{6,10,18,21},Φ₅＝{6,10,13,18,21}. Fig. 4 (a) shows single user MDR performance. When the preamble of the transmission does not trigger an alarm or TO estimate the error/>Exceeding a time error margin/>If so, the detection is regarded as missed.

Fig. 4 (b) shows RA Success Rate (RASR) performance in a multi-user configuration with a signal-to-noise ratio of-14 dB. The number of available preambles is N _p. If the preamble of the transmission does not collide or miss, the RA attempt of the UE is considered successful. As shown in fig. 4, u ₃ generally provides the best MDR/RASR performance in most cases. Therefore, it is selected as the m-SSP in the present invention.

In FIG. 5, the performance of the I-CP versus CS-CP, R-CP, and label-based cascading preamble (Label Based Cascaded Preamble, L-CP) etc. is compared by simulation. As a special case of using an I-CP with SSP of 1,0, …,0, the L-CP scheme is implemented by replacing the first component sequence of the R-CP with another sequence as a timing tag. In addition, R-CP has two sub-versions. For the estimate of ε _i, R-CP-TH extends the detection window back and finds the last component sequence using a threshold-based detection method, while R-CP-SW extends the detection window forward and back and uses a sliding window-based packet capture method. The L-CP-LS searches the timing label by using a CS-CP position searching method, and the L-CP-CC uses the proposed SSP-CC algorithm. Note that R-CP and L-CP use the same parameters as I-CP, while SC-CP uses different parameters, because the SC-CP scheme only provides a set of sufficient cyclic shift offsets at k=8.

As shown in fig. 5 (a), the proposed I-CP scheme achieves a signal-to-noise ratio gain of more than 4dB over the existing scheme, with a typical MDR of 10 ^-2. Furthermore, at a signal-to-noise ratio of-14 dB, the RASR performance of various schemes is shown in FIG. 5 (b), wherein the RASR upper bound determined by the collision probability passesAnd calculating, wherein N _u is the number of access UEs. Note that the proposed I-CP scheme is very close to the theoretical RASR upper bound and superior to its cognate scheme.

In addition, the I-CP scheme was tested in an experimental demonstration system, as shown in fig. 6. Specifically, one USRP-2944 was experimentally configured as a BS and the other 25 USRP-2944 were configured as UEs. Fig. 5 verifies that the experimental results of the I-CP agree with the simulation results.

In the embodiments provided herein, it should be understood that the disclosed systems and methods can be implemented in other ways. Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments can be implemented by hardware associated with program instructions, and the foregoing program can be stored in a computer readable storage medium, which when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or a optical disk, or the like, which can store program codes.

Or the above-described embodiments of the present invention can be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied essentially or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device to perform all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.

It is to be understood that the above examples of the present invention are provided by way of illustration only and not by way of limitation of the embodiments of the present invention. The drawings are for illustrative purposes only and are not to be construed as limiting the invention. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the invention are desired to be protected by the following claims.

Claims (10)

1. A random access preamble for a mobile satellite communication network, comprising: selecting staggered cascade preambles obtained by staggered arrangement of patterns with L=2 different basic sequences according to a preset sequence in a time domain; wherein the preset sequence selection pattern is a binary synchronous sequence, and the preamble consists of a useful part of a signal and a cyclic prefix with the duration of T _cp.

2. A mobile satellite communication network random access preamble according to claim 1, characterized in that the useful part of the signal is a useful signal s _u(t)(0≤t<T_u of duration T _u = KT) expressed as:

s_u(t)＝s_k(t-KT),kT≤t<(k+1)T,k＝0,…,K-1 (1)

Wherein s _k (T) (0.ltoreq.t < T) is the kth component signal, Is the duration of the component signal, Δf is the subcarrier spacing; orthogonal frequency division multiplexing using discrete fourier transform spreading in an enhanced physical random access channel, s _k (t) (k=0, …, K-1) has the general expression:

Where x _k N (n=0, …, N-1) is the kth time domain discrete component sequence, and the positive integer γ represents the starting position of N enhanced physical random access channel subcarriers in the frequency domain.

3. A mobile satellite communications network random access preamble as claimed in claim 2, wherein each component sequence is L candidate base sequencesOne, and is determined by the sequence selection pattern u [ K ] (k=0, …, K-1) as:

For k ₀∈{0,…,K-1},u[k₀ epsilon {0, …, L-1} is an index of a candidate base sequence.

4. A mobile satellite communications network random access preamble according to claim 3, wherein after addition of the cyclic prefix, the transmitted signal is:

Wherein T _d＝T_cp+T_u is the total duration of the transmitted signal, < - > _X represents the modulo X operation, satisfying < X > _X＝<x+X>_X, and the preamble received by the satellite base station in the line-of-sight channel is:

Where ρ is the average power of the received signal, τ is the time offset, f _d is the Doppler shift, θ is the random phase, w (T) is the additive Gaussian white noise with power spectral density N ₀, and T ₀ and T _rw are the start time and duration of the receive window, respectively.

5. A preamble detection method for detecting a time offset of a random access preamble of a mobile satellite communication network according to any of claims 1-4, comprising the steps of:

S1, sampling a received signal, and compensating a common frequency offset corresponding to a beam center for a sampling sequence;

s2, obtaining the estimation of the normalized decimal time offset of the received signal Shifting the compensated sample sequence to the left/>Sampling points;

S3, acquiring estimation of normalized integer time offset of the received signal by adopting sequence selection pattern auxiliary cross correlation algorithm

S4, shifting according to normalized decimal timeAnd normalized integer time offset estimation/>Obtaining an estimate of the overall normalized time offset/>

6. The preamble detection method according to claim 5, wherein in step S1, during the process of sampling the received signal, the detection window includes N _dw sampling points, and all the sampling points are uniformly distributed to K sub-windows; the receive window starts at T ₀＝T_cp, with a duration of T _rw = (k+1) T, and the received signal y (T) is sampled at t=nt _s+T_cp(n＝0,…,N_rw -1), resulting in:

y_s[n]＝y(nT_s+T_cp),n＝0,…,N_rw-1 (6)

Wherein, For the number of sampling points of the receiving window,/>For the sampling interval, N _s is the size of the fast fourier transform, and corresponds to the number of sub-window sampling points.

7. The preamble detection method as claimed in claim 6, wherein the expression for compensating the common frequency offset corresponding to the beam center for the sampling sequence is:

y_k[n]＝y_c[n+kN_s],n＝0,…,N_s-1 (8)

where y _k [ n ] denotes the portion of the compensated sample sequence that falls within the kth (k=0, …, K-1) sub-window.

8. The preamble detection method according to claim 7, wherein the step S3 is specifically: for the case H _dr where the roots of the two base sequences are different, the individual power delay profile is calculated as:

Λ_l,k[n]＝|c_l,k[n]|²,l＝0,1,k＝0,…,K-1,n＝0,…,N_d-1, (9)

Wherein c _l,k[n](n＝0,…,N_d -1) is a cross-correlation function, Is the inverse fast Fourier transform size applied to power delay spectrum calculation,/>Represents a minimum integer not less than x;

Wherein, And/>By respectively at/>And/>The tail is filled with N _d -N zeros, and the local frequency domain sequence/>Is/>N-point discrete Fourier transform of/(By extracting from Y _k[m](m＝0,…,N_s -1) the N symbols starting from index gamma, Y _k [ m ] is the N _s -point fast Fourier transform of Y _k [ N ]; the total power delay profile is generated by:

Wherein, Is the first cumulative power delay spectrum, H _sr for the case where the roots of the two base sequences are identical,Is/>Calculates/>, using the first ₀ (l ₀ =0 or 1) cumulative power delay profileThe method comprises the following steps:

wherein R (·) represents a numerical rounding operator; obtaining The index of the maximum value of (c) is:

σ ²＝N₀ B is the noise power, where b=n _s Δf is the system bandwidth if The preamble exists where λ is a predefined threshold that depends on the target false alarm rate, and the normalized fractional time offset is estimated as:

and moving the compensated sample sequence back The sampling points compensate for their fractional time offsets.

9. The preamble detection method according to claim 8, wherein the step S3 is specifically: calculating K shifted subsequencesTime-domain cross-correlation of each of the L candidate base sequences as shown in the following equation:

wherein the local time domain sequence Is/>N _s point inverse fast Fourier transform,/>By respectively at/>Is obtained by filling y-1 and N _s -N-y +1 zeros at the beginning and end of (c).

10. The preamble detection method as claimed in claim 9, characterized in that the robustness of the detection is maximized by using a sequence selection pattern as shown in the following formula:

Wherein, U [ K ] = - (-1) ^u[k] (k=0, …, K-1) is an effective sequence selection pattern generated by converting {0,1} to { ±1}, v >Representing the detected sequence selection pattern; since the a priori parameter T _cp should be chosen to satisfy τ < T _cp, there is ε _i≤K_cp -1, setting the length of ψi in equation (18) to K _cp; estimating a normalized integer time offset by searching for a maximum value of ψ [ i ]:

The estimation of the overall normalized time offset in step S4 is shown.