By now, data transmission rates of up to 54 MBit per second are being achieved in wireless local area networks. The specifications for this can be found in “IEEE 802.11a—Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: High-speed Physical Layer in the 5 GHZ band” and in “IEEE 802.11g—Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Further Higher Speed Physical Layer Extension in the 2.4 GHz Band” or also in “ETSI TS 101 761-1 Broadband Radio Access Networks (BRAN); Hiperlan Type 2: Physical (PHY) Layer”. To detect a useful signal, a periodic signal is sought which is sent out at the beginning of a data burst of the useful signal.
FIG. 1 shows a timing diagram in which a periodic signal u(t) with a defined period occurs from a particular time t0 in addition to a noise signal n(t). Along the x axis of the diagram, the time is plotted in units of one sampling period, i.e. the sampling index, and along the y axis the amplitude of the total signal r(t) consisting of the noise signal n(t) and periodic signal u(t) is plotted. The occurrence of the periodic signal u(t) superimposed on the noise signal n(t) must be detected by means of a signal detector. If the signal detector operates faultlessly, it must find by time t0 that there is no periodic signal u(t). The probability of an erroneous detection of the periodic signal must be as low as possible in this period. Once the periodic signal u(t) has occurred at time t0, on the other hand, the signal detector must verify the presence of the periodic signal u(t) as rapidly as possible. The error rate should then also be as low as possible. The periodic signal u(t), and thus the useful signal, should be verified, for example, with a probability of 90% within 4 μs.
FIG. 2 shows a possible use of such a signal detector. The analog complex signal r(t), which contains the noise signal n(t) and may contain the periodic signal u(t), is scaled by means of an amplifier with automatic gain control 1 and supplied to an analog/digital converter 2. The complex digital signal s(t), which can be picked up at the output of the analog/digital converter 2, is supplied to the signal detector 3. In addition, the signal s(t) is supplied to a receiver 4. The signal detector 3 informs the receiver 4 via a signal present at the detector output DA whether a periodic signal has been detected.
Because the amplifier with automatic gain control (AGC) 1 changes the total power, it is not sufficient for detecting the periodic signal u(t) to monitor only the power change of the signal s(t). The amplifier with automatic gain control 1 adapts the signal gain to the requirements from time to time. For this reason, the power fluctuates at the input of the analog/digital converter 2, and thus also at the input DE of the signal detector 3 which is why the change in power in the input signal s(t) does not provide reliable information on the presence or absence of the periodic signal u(t).
FIG. 3 shows the burst structure, as defined in the above-mentioned IEEE specification, which is used for data transmission and for synchronization between transmitter and receiver. The burst structure begins with a preamble STP built up of short training sequences, which is also called PLCP preamble or OFDM training structure. An 0.8-μs-long signal (short training sequence), called t1 in FIG. 3, is repeated 10 times for a total of 8 μs within STP. In FIG. 3, the repetitions are identified by t2, t3, . . . , t10. This is followed by a preamble LTP built up of a guard interval GI2 and two long training sequences T1 and T2. LTP also extends over 8 μs. Since LTP and the burst sections SIGNAL, Data1, Data2 following LTP are of no consequence, they will not be discussed further in the text which follows. Explanations relating to these can be found in Section 17.3 of the above-mentioned specification IEEE 802.11a.
To detect a burst at the receiver end, the periodic signal t1, t2, . . . , t10 of the preamble STP is used. To detect the periodic signal in the signal s(t), the similarity of the periodic signal t1, t2, . . . , t10 to itself can be utilized during a shift according to the signal period. In the case where there is no periodic signal, the signal s(t) should also not exhibit any periodicity.
In the second above-mentioned ETSI specification, the short training sequence is defined slightly differently, but the periodicity of the periodic signal is also present here. Reference is made here to specification sections 5.7 and 5.8. For this reason, the periodic signal u(t) superimposed on the noise signal n(t) can also be detected in the same manner in the case of this specification.
FIG. 4 shows the real part 4.1 and the imaginary part 4.2 of a total of four signals t1 to t4 in the form of a timing diagram in which the sample index is plotted along the x axis and the amplitude in arbitrary units along the y axis. The sampling rate is 20 MHz, i.e. 16 samples correspond to one repetition period (0.8 μs) of the periodic signal u(t). The signals t1 to t4 of the periodic signal, shown in FIG. 4, should be detectable by means of the signal detector 3.
From the prior art “VLSI Implementation of IEEE 802.11a Physical Layer, L. Schwoerer, H. Wirz, Nokia Research Center, 6th International OFDM Workshop 2001—Hamburg, pages 28-1 to 28-4”, a signal detector is known which uses the following autocorrelation function for detecting the periodic signal:
                                          c            1                    ⁡                      (            t            )                          =                                                      ∑                              t                i                                                              t                  i                                +                T                                      ⁢                                          s                ⁡                                  (                  t                  )                                            ⁢                                                s                  *                                ⁡                                  (                                      t                    -                    τ                                    )                                                                                                  (        1        )            where τ=0.8 μs is the period of the periodic signal u(t) and T is the integration or summation period.
FIG. 5 shows two timing diagrams in which in each case the index of samples is plotted along the x axis and the amplitude along the y axis. The upper diagram shows the complex digital signal s(t). At the index of samples 20, the periodic signal u(t) occurs. In the lower diagram, the autocorrelation function c1(t) as specified above in the equation (1) is shown. The signal s(t) does not contain a noise signal in this case. The integration or summation period T is 0.8 μs. After 1.6 μs (corresponding to 32 samplings), the last 0.8 μs of the signal s(t) are correlated perfectly with the first 0.8 μs of the signal s(t), and the autocorrelation sum remains constant 1.6 μs after the occurrence of the periodic signal.
In FIG. 6, two timing diagrams are also shown, the upper timing diagram again showing the signal s(t) and the lower timing diagram showing the autocorrelation function c1(t). The sampling rate is again 20 MHz but the signal s(t) now exhibits a noise signal component. The autocorrelation value c1(t) is now no longer stable. In addition, the autocorrelation value c1(t) also deviates from the value 0 even before the periodic signal occurs. To reliably detect the periodic signal, a threshold value must be taken into consideration. If the autocorrelation value c1(t) exceeds the threshold value, it is assumed that the periodic signal is present. The higher the threshold value, the lower the probability that the autocorrelation according to the abovementioned function c1(t) falsely detects a periodic signal. The consequence of this is, however, that the higher the threshold value thr_ac, the longer it takes until the periodic signal is detected.
The value of the autocorrelation c1(t) is also dependent on the power of the signal s(t). The threshold value must, therefore, be matched to the signal power. The mean value of the power of the signal s(t) is not constant because the variable-gain amplifier 1 arranged upstream of the signal detector 3 attempts to keep the output signal within an interval. This is necessary in order to avoid overdriving the analog/digital converter 2. Even if the input signal, r(t) as shown in FIG. 2 exhibits a constant mean power, it is not possible to set the variable-gain amplifier 1 immediately to the correct value. This first requires a number of adjustments. Due to the gain variation, fluctuations will thus occur in the mean power of the signal s(t) at the input of the signal detector 3 in any case. To this is added that the variable-gain amplifier 1 is normally only set to a fixed final value when the periodic signal has been detected and the useful signal is being received. For this reason, the power must be estimated during the detection process. In the prior art, the following formula is used for estimating the power of the signal s(t):
                              p          ⁡                      (            t            )                          =                                                      ∑                              t                i                                                              t                  i                                +                T                                      ⁢                                          s                ⁡                                  (                  t                  )                                            ⁢                                                s                  *                                ⁡                                  (                  t                  )                                                                                                  (        2        )            
The power p(t) is estimated over the last T seconds of the signal s(t) used during the autocorrelation.
The decision as to whether the periodic signal is present or not is made by means of the conditionc1(t)≧p(t)*thr—ac  (3)where thr_ac designates the threshold value (not scaled to power) for the autocorrelation. If c1(t) is greater than or equal to the product of power p(t) and threshold value thr_ac, it is assumed that a periodic signal is present.
The magnitude of the threshold value thr_ac is the result of a trade-off between the desired high reliability of detection of the periodic signal and, on the other hand, the quickest possible detection of the periodic signal.
The block diagram in FIG. 7 shows the configuration of a signal detector 3 which implements the equations specified in the above-mentioned prior art.
The thick lines identify complex signals whereas the thin lines identify real signals.
The signal detector 3 shown as a block diagram in FIG. 7 has an input DE at which the input signal s(t), which is the complex digital output signal of the analog/digital converter 2, is present. The input signal s(t) is supplied to a unit for power estimation 13 which provides at its output the power estimation signal p(t) which was calculated according to equation (2). For this purpose, the unit for power estimation 13 has a unit for squaring an amount 5 and an analog adder 6. At the same time, the signal s(t) is supplied to an autocorrelation unit 15. The autocorrelation unit 15 comprises a unit 9 for forming the conjugate complex signal, a delay unit 10 for delaying the signal s(t) by the period τ, and a multiplier 16 which multiplies the signal s(t) by the delayed complex conjugate signal s*(t−τ). Following the multiplier 16, an analog adder 11 with the adding period T and a unit for absolute-value generation 12 are arranged. The output of the autocorrelation unit 15 is connected to a first input of a decision unit 14. At a second input of the decision unit 14, the threshold value thr_ac is present. A third input of the decision unit 14 is connected to the output of the unit for power estimation 13. The threshold value thr_ac is scaled by means of the multiplier 7. The threshold value condition according to equation (3) is checked by the comparator 8. At the output DA of the signal detector 3, a detector signal d(t) can be picked up which specifies whether a periodic signal has been detected.
Using autocorrelation for detecting signals has the advantage that the shape of the periodic signal does not need to be known for detecting the periodic signal. To detect the periodic signal, only its period τ must be known. In the case of transmission channels with great distortion or interference, the shape of the received signal is considerably changed compared with the signal transmitted. The period of the transmitted signal remains intact, however. Under these transmission conditions, the signal to noise ratio (SNR), which is needed for the receiver to operate correctly, is normally relatively high—but in any case of such a magnitude that signal detection by autocorrelation can be achieved without problems. In other words: in the case of a channel with high distortion, the problem is not to verify the presence of the (greatly distorted) useful signal by autocorrelation in the detector but to decode the useful signal in the receiver 4.
The conditions are different in the case of an approximately ideal transmission channel. In this case, the SNR required for the receiver to be operable can be very low, possibly down to 0 dB. This means that the receiver can still decode a very noisy useful signal. The situation may occur where even though the receiver could decode the almost distortion-free, very noisy useful signal, the detector performing the autocorrelation is not capable of indicating the presence of the useful signal. In other words: in the case of an approximately ideal channel, the problem consists in detecting the signal (verification of the presence of the useful signal) in the signal detector 3, not in the subsequent signal decoding in the receiver 4.
The problems in signal detection impair the performance of the system consisting of receiver 4 and detector 3. Receiver 4 and detector 3 form a total system which appears to exhibit an increased error rate. The increased error rate disadvantageously results in additional retransmissions. This lastly results in a reduction in the data throughput for the overall system.