Frequency and phase estimation for MPSK signals

Pulse or digital communications – Receivers – Angle modulation

Reexamination Certificate

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C375S260000, C375S343000

Reexamination Certificate

active

06421399

ABSTRACT:

FIELD OF THE INVENTION
The present invention relates generally to data communications signal processing and, more specifically, concerns a frequency and phase estimation method and apparatus for an MPSK modulated carrier.
BACKGROUND OF THE INVENTION
Many types of data communications systems transfer information (e.g., audio or video signals) by modulating the information onto a carrier signal such as a sine wave. The carrier is modulated by varying one or more of its parameters, such as amplitude, frequency, or phase, according to the information being transmitted.
Phase shift keying (“PSK”) modulation is frequently used to transmit digital data. PSK involves shifting the phase of the carrier according to the value of the digital data. For example, in binary PSK (“BPSK”) the “zeros” in the digital data may be represented by a 180° shift in the phase of the carrier, while the “ones” in the digital data may be represented by no phase shift. Other degrees of phase shifting may be used. Quadrature PSK (“QPSK”) involves phase shifts of 0°, 90°, 180° and 270°. PSK typically is referred to as “MPSK” where the “M” represents the number of phases.
After a transmitter sends an MSPK signal over the selected transmission medium (e.g., telephone lines or radio frequency waves), a receiver detects the phase changes in the accurately, the receiver must extract the unmodulated frequency and phase (commonly referred to as the reference frequency and phase) of the carrier from the received signal.
Traditionally, phase-locked loop (“PLL”) circuits have been used to acquire carrier phase in many types of MPSK modems. PLLs are relatively easy to implement with either analog or digital technology and, in general, are considered to have good “steady state” performance.
However, PLLs are not effective for “bursty” transmissions. That is, transmissions where the signal is received in bursts (e.g., time-division multiple access, “TDMA,” signals), rather than as a continuous signal. In many cases, PLLs cannot achieve fast phase acquisition with a high probability of accuracy due to a phenomenon known as “hang-up.” Moreover, PLLs typically have a limited frequency acquisition range unless they are augmented with search schemes. These search schemes, however, introduce significant delay into the phase acquisition process.
Due to the above problems and the proliferation of digital technology and more powerful digital signal processors, many modern burst-mode modems acquire carrier phase using open-loop algorithms instead of PLLs. Open-loop solutions typically use a preamble at the beginning of each burst. A modem that processes burst-type transmissions that include a sufficiently long preamble may acquire phase using some form of correlator searching for a known preamble or using a decision directed solution. Some of these techniques are described in M. P. Fitz, “Equivocation in Nonlinear Digital Carrier Synchronizers,” IEEE Transaction on Communications, vol. 39, no. 11, November 1991; and M. P. Fitz and W. C. Lindsey, “Decision-Directed Burst-Mode Carrier Synchronization Techniques,” IEEE Transactions on Communications, vol. 40, no. 10, October 1992, the contents of which are hereby incorporated herein by reference.
The preamble technique is an unsuitable solution for many applications. For example, long preambles may take up a relatively large portion of the burst (particularly for short bursts). This reduces the effective bandwidth that is available for data transmission. Moreover, in some applications there is a need to acquire phase and frequency at any point during the burst or to reacquire it, once it is lost. Inherently, the preamble technique is ineffective for these applications.
Alternatively, a scheme based on a maximum likelihood algorithm may be employed. This scheme removes the data dependency of the received signal using a nonlinear operation. It has been shown for the case of an MPSK modulated carrier with an unknown phase that when the frequency is known (down to a small error) the phase can be efficiently estimated using a nonlinear algorithm. This technique may lead to results which are only moderately less accurate than those achievable by an optimal linear estimator operating on an unmodulated carrier. See, for example, the article by A. J. Viterbi and A. M. Viterbi entitled “Nonlinear Estimation of PSK-Modulated Carrier Phase with Application to Burst Digital Transmission,” IEEE Transactions on Information Theory, vol. IT-29, no. 4, pp. 543-551, July 1983, the contents of which is hereby incorporated herein by reference.
The above techniques provide phase estimates for signals where the frequency is known. However, many applications require frequency and phase estimation for MPSK signals with a relatively wide frequency uncertainty range. For example, due to the instability of oscillators in the transmitters and receivers, the frequency of the received signal may be different than the expected frequency. Under certain circumstances, the frequency uncertainty range (i.e., range of possible frequencies of the received signal due to the instability) may be a significant fraction of the signal symbol rate. (In PSK, the information transfer rate is defined in terms of symbols per second.) Moreover, the frequency of the received signal typically will change over time due to the instability. Thus, the receiver must produce continuous phase and frequency estimates to maintain synchronization between the transmitter and receiver.
Various techniques have been proposed to determine the frequency of a signal within a known frequency uncertainty range. For example, it has been shown that a maximum-posterior-probability frequency estimator may consist of a bank of equally spaced envelope correlation detectors followed by “choose largest” logic. Viterbi, A. J.,
Principles of Coherent Communications,
McGraw-Hill Book Co., New York, 1966, the contents of which is hereby incorporated herein by reference. However, this technique only dealt with an unmodulated sinusoid and did not detect the phase of the signal.
Thus, a need exists for an efficient frequency and phase estimator for signals that have a frequency uncertainty range that is a significant fraction of the symbol rate. Moreover, the estimator needs to produce estimates for each symbol following the initial acquisition of the signal and do so with high probability and within a relatively small number of symbols.
In accordance with a preferred embodiment of the invention, a frequency and phase estimator divides the frequency uncertainty range of the signal into a plurality of narrower frequency bands, the width of which is dictated by the required frequency resolution. For example, if the frequency uncertainty range covers 10 kHz, one band could cover the first 1 kHz in the range, another band could cover the second 1 kHz, and so forth. The estimator processes the signal and generates a frequency estimate by determining the band into which the incoming signal falls. The estimator then calculates a phase estimate.
The estimator shifts the frequency of, filters and samples the incoming signal, to produce a continuous sequence of discrete-time signal samples for each band. The frequency shift operation involves shifting the frequency of the incoming signal by an amount determined by the center frequency of each band relative to the center frequency of the uncertainty range. For example, when there are ten bands defined, the incoming signal is frequency shifted by a different amount for each band resulting in ten different shifts. Depending on the implementation, the incoming signal may be frequency shifted either before or after the signal is converted to a digital format by analog-to-digital conversion. Preferably, a pair of analog-to-digital converters is utilized. Each symbol in the incoming signal is sampled one or more times to produce the sequence of samples.
Next, the estimator removes the PSK modulation and accumulates the samples for each band. The modulation is removed by processing the samples with a nonlinear algorithm. A complex ac

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