Timing acquisition algorithm for an adaptive antenna array

A timing acquisition algorithm for locating the sync timing position of a sync word embedded in a received signal for achieving synchronization between the received signal and a base station, e.g., a base station receiving the received signal, within a wireless telecommunications system. The timing acquisition algorithm is preferably a set of programmable instructions incorporated within a software package and processed by a processor at the within the wireless telecommunications system, such as at the base station. The timing acquisition algorithm gets rid of the unlikely sync timing position for each branch of an adaptive antenna array in the first step; gets rid of the unlikely sync timing position for all branches in the second step; and uses optimal diversity combining for the remaining timing position and uses the conventional correlation or mean-square-error (MSE) approach on the combined data in the third step to finally locate the timing position of the sync word. The first two steps limit the computational load of the third step to a reasonable level. For example, if only two sync timing positions remain after the first two steps, then during the third step, weight calculations need only be performed twice, i.e., one for each sync timing position that still remains.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to wireless telecommunications systems, and more particularly to a timing acquisition algorithm for an adaptive antenna array to increase range of signals received from multiple antennas and suppress interference(s).

2. Description of the Prior Art

With the correct symbol timing and carrier frequency, an adaptive antenna array can generate weights to combine signals received from multiple antennas to increase range and suppress interference(s). However, prior to adaptive array combining, the received desired signals may be severely masked by noise and interference(s). To fully make use of the adaptive antenna array, a timing acquisition technique or algorithm is needed.

The objective of timing acquisition algorithms is to locate the correct timing position of a sync word embedded in received signals. One prior art timing acquisition algorithm uses the cross-correlation approach to identify and locate the timing position of the sync word. For each antenna, a correlation of received samples and the designated sync word is performed over a window of samples (9.5 symbol period), and the set of samples that produce the maximum cross-correlation value will be considered as the synchronization samples. However, in the interference-dominated environment, it can easily happen the signal is in deep fade on one of the diversity branches, but the interference(s) are not in a deep fade on that branch. The signal can be severely masked by the interference(s) on that branch and will cause incorrectly chosen of the sync-position on that branch.

In another prior art timing acquisition algorithm, the timing position of the sync word is identified and located using a mean-square-error (MSE) method. First, the antenna with the strongest signal energy is selected. Then, a MSE between the received samples on the selected antenna and the designated sync word is calculated over a window of samples. The set of samples that produce the minimum MSE will be considered as the synchronized samples. However, in the interference-dominated environment, the antenna that has the strongest received signal energy may not be the antenna that has the strongest desired signal energy. There is a significant chance that most of the energy is from the interference(s).

Neither the correlation approach nor the MSE approach use any weighted and combined signals from all the branches which can effectively combat fading and interference. Even though these techniques may work well for two-branch-antenna-diversity system and an low interference environment, these techniques are not suitable for a four-branch-antenna-diversity system.

Another prior art diversity combining technique is designed to combine signals from all the branches using the Maximum Ratio Combining (MRC) technique. Correlation or MSE approaches can finally be used on the combined signals to identify the position of the sync word. This diversity combining technique has been shown to be efficient under flat fading and noise limited environments, but not too efficient under an interference dominated environment.

Another prior art timing acquisition algorithm, called an interference-cancellation-first algorithm, is proposed by Cupo et al. in A Four-Element Adaptive Antenna Array for IS-136 PCS Base Station, technical memorandum, AT&T Labs and Bell Labs, 1997, and designed to combine signals from all the branches. In this algorithm, diversity combining weights are first generated using a designated sync word and the samples associated with each timing epoch. The received signals in each timing epoch are then weighted and combined. Correlation or MSE approaches can finally be used,on the combined signals to identify the sync position. The combined signal from the sample set with the right sync position should have the highest SIR and will end up with the lowest MSE or highest correlation value at the end.

Although the interference-cancellation-first algorithm is an effective algorithm, since it optimally combines signals from all the branches, the complexity of the technique is high. The combining weights have to be found for samples in each epoch. If the search window size is seven symbols (size of 6.5 symbols is used in DRM and size of 9.5 symbols is used in EDRU), the algorithm has to calculate the covariance matrix, cross-correlation matrix and combining weights 28 times (seven symbols multiplied by four over-sampling values).

Accordingly, a need exists for a non-complex timing acquisition algorithm for an adaptive antenna array which utilizes the signals from all the branches of the antenna array to increase range and suppress interference(s).

SUMMARY OF THE INVENTION

The timing acquisition algorithm is a three-step time synchronization technique for locating the sync timing position of a sync word embedded in a signal received at a base station for achieving synchronization between the received signal and the base station within a wireless telecommunications system. The timing acquisition algorithm is preferably processed by a processor located at the base station.

The algorithm gets rid of the unlikely sync timing position for each branch in the first step; gets rid of the unlikely sync timing position for all branches in the second step; and uses optimal diversity combining for the remaining timing position and uses the conventional correlation or mean-square-error (MSE) approach on the combined data in the third step to finally locate the timing position of the sync word. The first two steps limit the computational load of the third step to a reasonable level. For example, if only two sync timing positions remain after the first two steps, then during the third step, weight calculations need only be performed twice, i.e., one for each sync timing position that still remains.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring now in detail to the drawings, in which like reference numerals represent similar or identical elements throughout the several views, and with particular reference to FIG. 1 , there is shown a block diagram of a baseband simulation model used to generate the four-times over-sampled received signal used by the present invention. Even though FIG. 1 illustrates the received signal being sampled four times, it is contemplated that the principles and teachings of the present invention can be used to locate the position of the sync word for a received signal which is sampled more or less than four times.

Modulated signals 12 from a user, e.g., a mobile station, or from a plurality of co-channel interferers 14 , e.g., co-channel interference signal(s), are first passed through transmit filters 16 . Transmit filters 16 are preferably root-raised-cosine transmit filters with an 0.35 excess bandwidth factor. Each signal is then passed through four independent channels 18 . The channels 18 are preferably Rayleigh flat-fading channels generated by Jakes' model to model the signal received at four antennas. The faded signal, interference signal(s) and white noise are added together by summation blocks 20 at each receiving antenna 22 . The combined signals are then passed through receive filters 24 . The receive filters 24 are preferably root-raised cosine receive filters with an 0.35 excess bandwidth factor. The signals are hence four times over-sampled. The over-sampled base-band signals corrupted by the co-channel interference signal(s) and white noise are used later for time-synchronization and demodulation.

There are two possible ways that the faded signal and interference signal(s) can be added by summation blocks 20 . In a first case, the base stations are all synchronized and optimally planned. The faded signal and interference signal(s) are not only synchronized, but also use a different synchronization word. The first case is illustrated in FIG. 2 . In a second case, the base stations are not synchronized and neither are the faded signal and interference signal(s). The time offset, T off , between the faded signal and interference signal(s) is arbitrary. During one slot interval, the desired signal can be interfered by co-channel signals from two different mobile stations. The second case is illustrated in FIG. 3 .

With reference to FIG. 4 , there is shown the three-step timing acquisition algorithm of the present invention for locating the timing position of a sync word embedded in a received signal (i.e., timing position of the received signal) for achieving synchronization between the received signal and the base station within the wireless telecommunications system. The timing acquisition algorithm is preferably a set of programmable instructions incorporated within a software package and processed by a processor at the base station.

The three-step timing acquisition algorithm in step one gets rid of the unlikely sync timing positions for each antenna branch (the positions which are not indicated by an arrow). In step two, the algorithm gets rid of the unlikely sync timing positions for all branches. Finally, in step three, the algorithm uses diversity combining for the remaining timing positions and uses the conventional correlation or mean-square-error (MSE) approach on the combined data to finally locate the timing position of the sync word. Accordingly, timing acquisition is performed by steps one and two prior to antenna array combining by step three. Hence, steps one and two limit the computational load of the third step to a reasonable level. For example, if only two sync timing positions remain after the first two steps, then during the third step, weight calculations need only be performed twice, i.e., one for each sync timing position that still remains.

It is also contemplated to first determine x number of the highest peaks across all antennas, e.g., determine the four highest peaks across all antennas, and then eliminate all peaks except y number of the highest peaks, e.g., eliminate all peaks except the two highest peaks, where x>y (in the example, x 4 and y 2) and the peaks remaining are the highest peaks. Finally, the timing position of the received signal is located by combining the remaining sync timing positions (in the example, combining the two remaining sync timing positions).

FIG. 4 illustrates the three-step timing acquisition algorithm for an adaptive antenna array having four branches. It is contemplated that the timing acquisition algorithm of the present invention can be used to locate the timing position of the sync word for adaptive antenna arrays having any number of branches.

In a preferred embodiment, the three-step timing acquisition algorithm in step one computes the cross-correlation of received samples and the designated sync word over a range of samples. Preferably, the algorithm computes a 14-symbol cross-correlation of received samples and the designated sync word over a predetermined range of samples, e.g., 7-symbol periods. Further, in this step, the algorithm computes the magnitude of the correlation value and finds the m largest correlation values and corresponding positions. (m 2 was used in the simulation model (see FIGS. 5 - 20 )).

In step two, the three-step timing acquisition algorithm finds the n positions which generated the n largest correlation values from among the m times the number of antenna branches positions, i.e., 2*4 8 positions for the simulation model (n 2 was used in the simulation model (see FIGS. 5 - 20 )). In step three, the three-step timing acquisition algorithm uses the diagonal loading Minimum Mean Square Error (MMSE) algorithm, as known by one ordinarily skilled in the art, to find the antenna weights for the selected n sample sets. Further, in this step, the algorithm combines the antenna samples with the corresponding weights and uses the correlation or MSE technique on each of the n combined sample sets. Further, in step three, the algorithm identifies the final timing position of the sync word that is associated with the largest correlation value or lowest MSE value among the n values.

Simulation results are presented by FIGS. 5-30 . These figures also compare the performance of the inventive three-step timing acquisition algorithm with several prior art algorithms and an ideal synchronization case. T/ 4 is used as the step size in all the sync position search algorithms. The search window size is seven symbols.

In FIGS. 5-12 , 500 frames are used for data point at INR (Interference to Noise Ratio) 20 dB and 3000, 5500, 8000 and 10,000 are used for data point at INR 15, 10, 5 and 0 dB, respectively.

In FIGS. 5-30 , perf represents the ideal synchronization case; corr 1 represents the single antenna correlation based sync algorithm; mse represents the MSE based sync algorithm; corr 2 represents a correlation based sync algorithm in which the single antenna correlation based algorithm is used first, and then the final unique sync position is located by choosing the one with the highest correlation value among the four; icf represents the interference-cancellation-first algorithm; and 3step represents the three-step timing acquisition algorithm of the present invention.

In FIGS. 5-8 , the diagonal loading MMSE algorithm-Four Branch Intelligent Antenna (FBIA) and differential decoding are used for the diversity combining and demodulation after the time synchronization is finished. The diagonal loading factor is chosen to be 0.0322 (same value as used in the Two Branch Intelligent Antenna (TBIA)). Two interferers are simulated. In FIGS. 5-6 , both interferers appear in the whole time slot. In FIGS. 7-8 , one interferer appears in part of the time slot and the other interferer appears in the rest of the time slot. The SNR is 20 dB. The fading rate is 50 Hz in FIGS. 5 and 7 and 180 Hz in FIGS. 6 and 8 for the fading signal and interference signal(s).

In FIGS. 9-12 , maximum ratio combining (MRC) and differential decoding is used for the diversity combining and demodulation after the symbol time synchronization. Two interferers are simulated. In FIGS. 9-10 , both interferers appear in the whole time slot. In FIGS. 11-12 , one interferer appears in part of the time slot and the other interferer appears in the rest of the time slot. The SNR is 20 dB. The fading rate is 50 Hz in FIGS. 9 and 11 and 180 Hz in FIGS. 10 and 12 for the fading signal and interference signal(s).

In FIGS. 13-20 , 1000 to 5000 frames are used for each data point in the simulations with the larger number of frames used at lower BER to get more accurate results.

In FIGS. 13-16 , FBIA and differential decoding are used for the diversity combining and demodulation after the time synchronization is finished. The diagonal loading factor is chosen to be 0.0322. One interferer is simulated. In FIGS. 13-14 , the interference appears in the whole time slot. In FIGS. 15-16 , the interference appears only in part of the time slot. The SNR is 20 dB. The fading rate is 50 Hz in FIGS. 13 and 15 and 180 Hz in FIGS. 14 and 16 for both the fading signal and interference signal(s).

In FIGS. 17-20 , Maximum Ratio Combining (MRC) and differential decoding is used for the diversity combining and demodulation after the symbol time synchronization. One interferer is simulated. In FIGS. 17-18 , the interference appears in the whole time slot. In FIGS. 19-20 , the interference appears only in part of the time slot. The SNR is 20 dB. The fading rate is 50 Hz in FIGS. 17 and 19 and 180 Hz in FIGS. 18 and 20 for both the fading signal and interference signal(s).

In FIGS. 23-28 , the performance of different algorithms at noise limited cases are evaluated. 1000 frames are used for each data point in the simulations.

In FIGS. 23-25 , FBIA and differential decoding are used for diversity combining and demodulation after the time synchronization is finished. The diagonal loading factor is chosen to be 0.0322. The fading rate is 0, 50 and 180 Hz in FIGS. 23 , 24 and 25 , respectively.

In FIGS. 26-28 , MRC and differential decoding are used for diversity combining and demodulation after the time synchronization is finished. The fading rate is 0, 50 and 180 Hz in FIGS. 26 , 27 and 28 , respectively.

All the simulation results in FIGS. 5-20 show that there is a significant performance improvement provided by the three-step algorithm over the prior art techniques. The interference-cancellation-first (ICF) technique causes negligible BER performance degradation compared to the ideal case. Although the ICF technique provides the best performance, the performance of three-step with m 2 and n 2 is very close to the ICF technique in almost all the cases; the exceptions are some conditions with one strong interferer. Even in that case, the three-step technique is still better than the prior art approaches. Either the three-step or the ICF technique is more effective in the first case (see FIG. 2 ) where the fading signal and interference signal(s) are synchronized.

In the worst case of one strong interferer, performance can be improved by increasing n.

The simulation results in FIG. 21 show the worst case scenario where there is only one interferer and it is as strong as the desired signal. The interference appears in the whole time slot as shown in FIG. 2 . The diagonal loading MMSE algorithm (FBIA) and differential decoding are used for the interference cancellation and demodulation after the time synchronization is finished. The diagonal loading factor is chosen to be 0.0322. The SNR is 20 dB. The fading rate is 50 Hz.

The simulation results in FIG. 22 show that the performance of three-step can be improved by increasing n. At n 3, its performance is already close to that of ICF and at n 8, its performance is extremely close to that of ICF. The three-step technique requires lower computations than the ICF technique in general and requires far less computations when m 2 and n 2.

What has been described herein is merely illustrative of the application of the principles of the present invention. For example, the functions described above and implemented as the best mode for operating the present invention are for illustration purposes only. Other arrangements and methods may be implemented by those skilled in the art without departing from the scope and spirit of this invention.