CA2264414A1 - Communications receiver and method of detecting data from received signals - Google Patents
Communications receiver and method of detecting data from received signals Download PDFInfo
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- CA2264414A1 CA2264414A1 CA 2264414 CA2264414A CA2264414A1 CA 2264414 A1 CA2264414 A1 CA 2264414A1 CA 2264414 CA2264414 CA 2264414 CA 2264414 A CA2264414 A CA 2264414A CA 2264414 A1 CA2264414 A1 CA 2264414A1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03171—Arrangements involving maximum a posteriori probability [MAP] detection
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
- H04L25/0212—Channel estimation of impulse response
Abstract
A communications receiver for detecting data symbols from signals representative of the data symbols received from a communications channel, the communications receiver comprising an equaliser (19) which operates to detect the data symbols by calculating a plurality of transition probability estimates associated with transitions from first states (m') of the communications channel to at least one subsequent state (m) of the communications channel from an estimate of an impulse response of the communications channel and the received signals, wherein the communications receiver further includes a channel impulse response adapter (42) coupled to the equaliser (19,46), which operates to adapt the channel impulse response estimate in dependence upon the plurality of transition probability estimates, whereby a likelihood of correctly detecting the data symbols is substantially improved. The communications receiver may form part of a GSM or a TD-CDMA mobile radio communications receiver.
Description
Description of invention:
Communications Receiver and Method of Detecting Data from Received Signals The present invention relates to communications receivers which operate to generate data from signals representative of the data which signals have been corrupted during transmission between a transmitter and the communications receivers. In particular, but not exclusively, the present invention relates to communications receivers which operate to detect data from received radio signals representative of the data which radio signals have been corrupted during transmission via the ether. Furthermore, the present invention relates to methods of detecting data from received signals which are representative of the data.
In many known communication systems, such as mobile radio telephone systems, the integrity of data communicated by the system is reduced as a result of naturally occurring disturbances which corrupt signals representative of the data, during transmission between a transmitter and a receiver of the system. For example in mobile radio communications, disturbances such as multi-path propagation and frequency shifts of radio signals which carry the data, cause inter-symbol interference and fading. In order to communicate data effectively, receivers of the radio signals, are therefore provided with means to mitigate these disturbances.
To mitigate the effects of mufti-path propagation, radio receivers are known to use equalisers which operate to substantially cancel the detrimental effects of inter-symbol interference and fading, caused by the mufti-path propagation. An equaliser known to those skilled in the art, which provides a significant increase in the integrity of the data recovered from the radio signals, is the maximum likelihood, or near maximum likelihood sequence estimator, also known as the Viterbi equaliser. The Viterbi equaliser is well known to those skilled in the art as a sequence estimator which operates to determine a most likely sequence of symbols from all possible sequences of symbols in accordance with a comparison between the received signals and all possible symbols which could form the symbol sequence.
The Viterbi algorithm is well known, and so a detailed description will not be repeated here, however a more detailed description of this algorithm, can be found in an article published in IEEE Transactions of Information Theory, May 1972, Vol. TI 18, No 3, Pages 366-378, G D Forney, Jr:
'Maximum Likelihood Sequence Estimation of Digital Sequences in the Presence of Inter-symbol Interference'.
In some communications systems, such as for example time division multiple access mobile radio systems, an estimate of the impulse response of the communications channel through which the radio signals have passed is required to facilitate operation of the equaliser. To this end, radio signals transmitted within a predetermined time slot, also include known signals generated from a training sequence of known data symbols which when cross correlated with a locally generated reference version of the training sequence at the receiver, provide an estimate of an impulse response of the communications channel. This estimate of the channel impulse response is used by the equaliser to form error signals in dependence upon a comparison between reference signals generated from a possible sequence of symbols convolved with the channel impulse response estimate, and the received radio signals. By minimising the error signals, the equaliser operates to substantially maximise a probability that a selected sequence of symbols is that which was transmitted.
In rapidly varying communications channels, or correspondingly where the radio signals representing a sequence of data symbols have a temporal length which is greater than a coherence time of the communications channel, the estimate of the channel impulse response from the known training sequence signals at one temporal location in the radio signals may not provide an accurate representation of the communications channel at another temporal location of the radio signals. For example, in the case of the known mobile radio system the Global System for Mobiles (GSM), the known training sequence signals are arranged to be transmitted in the middle of a burst of radio signals occupying a time slot. As such, although a version of the channel impulse response generated from the training sequence may be accurate for data communicated in or around the middle of the burst, the channel impulse response at temporal positions displaced from the middle of the data sequence, may not be accurate as a result of the rapid changes in the communications channel. In this situation, the integrity of the data detected at these displaced temporal positions will be substantially reduced, as a result of the inaccuracy of the channel impulse response estimate used by the equaliser.
As a solution to this technical problem, European Patent EP
042545881 teaches an arrangement for a Viterbi equaliser, wherein a plurality of channel impulse response estimates are provided, each estimate of the channel impulse response being associated with a corresponding state of a trellis modelling the communications channel formed by the Viterbi equaliser.
Each of these channel impulse responses is separately adapted in accordance with error signals formed from a comparison of coefficients of each channel impulse response estimate and newly determined symbols estimated by the Viterbi equaliser.
As a result the adaptive Viterbi equaliser taught by EP
042545881, is able to substantially maintain the integrity of the data generated from the received radio signals, despite variations in the channel impulse response of the communications channel.
As already mentioned, the Viterbi equaliser operates to provide an estimate of the most likely sequence of symbols corresponding to a burst of received radio signals. However in some applications, a symbol estimator is preferred. An example of a symbol estimator is the Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm, disclosed in an article "Optimal Decoding of Linear Codes for Minimising Symbol Error Rate, by L. R, Bahl, J. Cocke, F. Jelinek, and J. Raviv, published in the IEEE Transactions on Information Theory, March 1974 between pages 274 to 287. A symbol estimator such as the BCJR algorithm, operates to generate an estimate of the most likely symbol, on a symbol-by-symbol basis, which facilitates the generation of soft decision information, which is particularly appropriate where turbo-detection is used in a subsequent error correction decoder when the data has been encoded in accordance with a forward error correction algorithm. Moreover, where the communications channel is rapidly changing, adaptation of the channel impulse response as taught by European patent 0425458B herein before described is also desirable. As such, providing a symbol estimator with a means for adapting a channel impulse response estimate to substantially mitigate the effect of changes in the impulse response of a communications channel represents a technical problem which is addressed by the present invention.
According to the present invention there is provided a communications receiver for detecting data symbols from signals representative of said data symbols received from a communications channel, said communications receiver comprising an equaliser which operates to detect said data symbols by calculating a plurality of transition probability estimates associated with transitions from first states of the communications channel to at least one subsequent state of the communications channel from an estimate of an impulse response of said communications channel and said received signals, wherein said communications receiver further includes a channel impulse response adapter coupled to said equaliser, which operates to adapt said channel impulse response estimate in dependence upon said plurality of transition probability estimates, whereby a likelihood of correctly detecting said data symbols is substantially improved.
S
The term state as used herein with reference to a communications channel refers to a particular sequence of data symbols, the number of which symbols is determined by the number of past transmitted symbols which affect a subsequent symbol at a receiver as a result of inter-symbol interference caused by the channel.
By adapting the coefficients of the channel impulse response estimate in accordance with a plurality of transition probability estimates associated with transitions from first states to at least one subsequent state of the communications channel, an increment by which the channel impulse response coefficients are updated is influenced by the transitions modelled by the symbol detector. The adaptation of the channel impulse response estimate is thereby effected in a way which avoids a requirement for selecting one of the plurality of transitions leading to a subsequent state, which are not made with symbol estimators.
The channel estimate adapter may have a data store in which the channel impulse response estimate is stored, and a data processor which operates to adapt said channel impulse response estimate in accordance with an adaptation algorithm in combination with said transition probability estimates.
The adaptation algorithm is provided to effect an update of the channel impulse response as the symbol detector advances in time through the radio signals detecting the data symbols.
Advantageously the channel estimate adapter may further comprise a plurality of data stores, each of which data stores is associated with a state of the communications channel and serves to store a version of the channel impulse response estimate, and the data processor may operate to adapt each version of the channel impulse response estimate, in accordance with an adaptation algorithm in combination with a corresponding plurality of the transition probability estimates for transitions from a plurality of the first states to the state with which the channel impulse response is associated.
By providing a version of the channel impulse response estimate for each state of the communications channel, and arranging for a data processor to adapt each impulse response estimate separately, a substantial improvement in the probability of correctly detecting data by a data detection algorithm which uses the adapted channel impulse response estimates is effected. This is particularly true for rapidly changing communications channels.
The adaptation algorithm may operate to generate at least one adaptation factor with which coefficients of each version of the channel impulse response are adapted. The data processor may further weight the adaptation factor by a combination of said corresponding plurality of transition probability estimates.
The data processor may further operate to adapt each version of the channel impulse response estimate by generating an intermediate up-dated version of the channel impulse response estimate for each of the transitions from the first states to the subsequent state and combining the intermediate up-dated versions of the channel impulse response estimate weighted by said corresponding plurality of transition probability estimates.
The equaliser may further operate to substantially maximise a probability of correctly detected data symbols in dependence upon a plurality of state probability estimates each of which state probability estimates is associated with one of the plurality of states of the communications channel and calculated from the received signals in combination with the adapted version of said channel impulse response estimate associated with the state.
Advantageously, the data processor may operate to generate each adapted version of the channel impulse response estimate by weighting the intermediate up-dated versions of the channel impulse response estimate by a combination of the corresponding transition probability estimates and the state probability estimate for each of the first states which determine the transitions to the state with which the channel impulse response is associated. The transition probability estimates and the state probability estimates may be calculated in accordance with a symbol-by-symbol estimator algorithm such as the BCJR algorithm.
According to an aspect of the present invention, there is provided a method of detecting data symbols from signals received from a communications channel, comprising the steps of;
- calculating a plurality of transition probability estimates associated with transitions from first states of the communications channel to at least one subsequent state of the communications channel, from an estimate of an impulse response of the communications channel in combination with the received signals;
- adapting the channel impulse response estimate associated with the subsequent state in dependence upon the transition probability estimates; and - detecting the data symbols from the plurality of transition probability estimates.
The method of detecting data may further include the steps of;
- generating a plurality of versions of the channel impulse response estimate, each of which is associated with a state of the communications channel; and - adapting each of the channel impulse response estimates in dependence upon a corresponding plurality of the transition probability estimates for transitions from a plurality of the first states to the state with which the channel impulse response is associated.
The step of adapting each of the plurality of versions of the channel impulse response estimate further comprises the steps of;
- for each transition from the plurality of first states (m') to the subsequent state associated with the channel impulse response estimate, generating an intermediate up-dated version of the channel impulse response estimate;
- weighting each of said intermediate versions with said transition probability estimates and - combining said weighted intermediate up-dated versions to generate said adapted channel impulse response estimate.
One embodiment of the present invention will now be described by way of example only with reference to the accompanying drawings, wherein, FIGURE 1 is a schematic block diagram of part of a radio communications channel used within a mobile radio telephone system, FIGURE 2 is a schematic representation of a time division multiple access frame, FIGURE 3 is a schematic block diagram of the radio communications receiver shown in figure 1, FIGURE 4 is a schematic block diagram of a data detector, which appears in figure 3, FIGURE 5 is a schematic block diagram of part of the reference signal generator shown in figure 4, FIGURE 6 is an illustration of a trellis modelled by the data detector shown in figures 3 and 4.
While the present invention finds application in many areas within the digital communications art, and therefore to receivers for corrupted signals generally, an embodiment of the present invention will be described with reference to a radio communications receiver, and in particular to a radio communications receiver operating within a time division multiple access mobile radio communications system. Examples of such systems are the Global System for Mobiles (GSM), and a system operating in accordance with a hybrid Time Division and Code Division Multiple Access system, such as that described in an article entitled "Performance of a Cellular Hybrid C-TDMA Mobile Radio System Applying Joint Detection and Coherent Receiver Antenna Diversity" by G. Blanz, A.
Klein, M. Nathan and A. Steil published in the IEEE Journal on Selected Areas in Communications, Volume 12, no. 4, May 1994 at page 568.
In figure 1, a block diagram is shown, which is representative of parts of a radio communications channel operating within a mobile radio telephone system. In figure 1 digital data s(n) to be communicated over the radio communications channel is fed to a modulator and digital to analogue converter 1, via a data encoder 2. The encoder 2, operates to transform the digital data s(n) to encoded data symbols x(n) in accordance with a forward error correction algorithm. In the GSM system for example, the encoder applies a half rate convolutional code to the most important bits of a frame of digitally encoded speech. Analogue signals generated by the modulator 1 are fed to an input of a transmitter 3, which serves to amplify and up-convert the analogue signals to a radio frequency. The radio frequency signals are thereafter radiated by an antenna 4. The radio signals radiated by the antenna 4, propagate between the antenna 4, and a receive antenna 6 via the ether.
Communications Receiver and Method of Detecting Data from Received Signals The present invention relates to communications receivers which operate to generate data from signals representative of the data which signals have been corrupted during transmission between a transmitter and the communications receivers. In particular, but not exclusively, the present invention relates to communications receivers which operate to detect data from received radio signals representative of the data which radio signals have been corrupted during transmission via the ether. Furthermore, the present invention relates to methods of detecting data from received signals which are representative of the data.
In many known communication systems, such as mobile radio telephone systems, the integrity of data communicated by the system is reduced as a result of naturally occurring disturbances which corrupt signals representative of the data, during transmission between a transmitter and a receiver of the system. For example in mobile radio communications, disturbances such as multi-path propagation and frequency shifts of radio signals which carry the data, cause inter-symbol interference and fading. In order to communicate data effectively, receivers of the radio signals, are therefore provided with means to mitigate these disturbances.
To mitigate the effects of mufti-path propagation, radio receivers are known to use equalisers which operate to substantially cancel the detrimental effects of inter-symbol interference and fading, caused by the mufti-path propagation. An equaliser known to those skilled in the art, which provides a significant increase in the integrity of the data recovered from the radio signals, is the maximum likelihood, or near maximum likelihood sequence estimator, also known as the Viterbi equaliser. The Viterbi equaliser is well known to those skilled in the art as a sequence estimator which operates to determine a most likely sequence of symbols from all possible sequences of symbols in accordance with a comparison between the received signals and all possible symbols which could form the symbol sequence.
The Viterbi algorithm is well known, and so a detailed description will not be repeated here, however a more detailed description of this algorithm, can be found in an article published in IEEE Transactions of Information Theory, May 1972, Vol. TI 18, No 3, Pages 366-378, G D Forney, Jr:
'Maximum Likelihood Sequence Estimation of Digital Sequences in the Presence of Inter-symbol Interference'.
In some communications systems, such as for example time division multiple access mobile radio systems, an estimate of the impulse response of the communications channel through which the radio signals have passed is required to facilitate operation of the equaliser. To this end, radio signals transmitted within a predetermined time slot, also include known signals generated from a training sequence of known data symbols which when cross correlated with a locally generated reference version of the training sequence at the receiver, provide an estimate of an impulse response of the communications channel. This estimate of the channel impulse response is used by the equaliser to form error signals in dependence upon a comparison between reference signals generated from a possible sequence of symbols convolved with the channel impulse response estimate, and the received radio signals. By minimising the error signals, the equaliser operates to substantially maximise a probability that a selected sequence of symbols is that which was transmitted.
In rapidly varying communications channels, or correspondingly where the radio signals representing a sequence of data symbols have a temporal length which is greater than a coherence time of the communications channel, the estimate of the channel impulse response from the known training sequence signals at one temporal location in the radio signals may not provide an accurate representation of the communications channel at another temporal location of the radio signals. For example, in the case of the known mobile radio system the Global System for Mobiles (GSM), the known training sequence signals are arranged to be transmitted in the middle of a burst of radio signals occupying a time slot. As such, although a version of the channel impulse response generated from the training sequence may be accurate for data communicated in or around the middle of the burst, the channel impulse response at temporal positions displaced from the middle of the data sequence, may not be accurate as a result of the rapid changes in the communications channel. In this situation, the integrity of the data detected at these displaced temporal positions will be substantially reduced, as a result of the inaccuracy of the channel impulse response estimate used by the equaliser.
As a solution to this technical problem, European Patent EP
042545881 teaches an arrangement for a Viterbi equaliser, wherein a plurality of channel impulse response estimates are provided, each estimate of the channel impulse response being associated with a corresponding state of a trellis modelling the communications channel formed by the Viterbi equaliser.
Each of these channel impulse responses is separately adapted in accordance with error signals formed from a comparison of coefficients of each channel impulse response estimate and newly determined symbols estimated by the Viterbi equaliser.
As a result the adaptive Viterbi equaliser taught by EP
042545881, is able to substantially maintain the integrity of the data generated from the received radio signals, despite variations in the channel impulse response of the communications channel.
As already mentioned, the Viterbi equaliser operates to provide an estimate of the most likely sequence of symbols corresponding to a burst of received radio signals. However in some applications, a symbol estimator is preferred. An example of a symbol estimator is the Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm, disclosed in an article "Optimal Decoding of Linear Codes for Minimising Symbol Error Rate, by L. R, Bahl, J. Cocke, F. Jelinek, and J. Raviv, published in the IEEE Transactions on Information Theory, March 1974 between pages 274 to 287. A symbol estimator such as the BCJR algorithm, operates to generate an estimate of the most likely symbol, on a symbol-by-symbol basis, which facilitates the generation of soft decision information, which is particularly appropriate where turbo-detection is used in a subsequent error correction decoder when the data has been encoded in accordance with a forward error correction algorithm. Moreover, where the communications channel is rapidly changing, adaptation of the channel impulse response as taught by European patent 0425458B herein before described is also desirable. As such, providing a symbol estimator with a means for adapting a channel impulse response estimate to substantially mitigate the effect of changes in the impulse response of a communications channel represents a technical problem which is addressed by the present invention.
According to the present invention there is provided a communications receiver for detecting data symbols from signals representative of said data symbols received from a communications channel, said communications receiver comprising an equaliser which operates to detect said data symbols by calculating a plurality of transition probability estimates associated with transitions from first states of the communications channel to at least one subsequent state of the communications channel from an estimate of an impulse response of said communications channel and said received signals, wherein said communications receiver further includes a channel impulse response adapter coupled to said equaliser, which operates to adapt said channel impulse response estimate in dependence upon said plurality of transition probability estimates, whereby a likelihood of correctly detecting said data symbols is substantially improved.
S
The term state as used herein with reference to a communications channel refers to a particular sequence of data symbols, the number of which symbols is determined by the number of past transmitted symbols which affect a subsequent symbol at a receiver as a result of inter-symbol interference caused by the channel.
By adapting the coefficients of the channel impulse response estimate in accordance with a plurality of transition probability estimates associated with transitions from first states to at least one subsequent state of the communications channel, an increment by which the channel impulse response coefficients are updated is influenced by the transitions modelled by the symbol detector. The adaptation of the channel impulse response estimate is thereby effected in a way which avoids a requirement for selecting one of the plurality of transitions leading to a subsequent state, which are not made with symbol estimators.
The channel estimate adapter may have a data store in which the channel impulse response estimate is stored, and a data processor which operates to adapt said channel impulse response estimate in accordance with an adaptation algorithm in combination with said transition probability estimates.
The adaptation algorithm is provided to effect an update of the channel impulse response as the symbol detector advances in time through the radio signals detecting the data symbols.
Advantageously the channel estimate adapter may further comprise a plurality of data stores, each of which data stores is associated with a state of the communications channel and serves to store a version of the channel impulse response estimate, and the data processor may operate to adapt each version of the channel impulse response estimate, in accordance with an adaptation algorithm in combination with a corresponding plurality of the transition probability estimates for transitions from a plurality of the first states to the state with which the channel impulse response is associated.
By providing a version of the channel impulse response estimate for each state of the communications channel, and arranging for a data processor to adapt each impulse response estimate separately, a substantial improvement in the probability of correctly detecting data by a data detection algorithm which uses the adapted channel impulse response estimates is effected. This is particularly true for rapidly changing communications channels.
The adaptation algorithm may operate to generate at least one adaptation factor with which coefficients of each version of the channel impulse response are adapted. The data processor may further weight the adaptation factor by a combination of said corresponding plurality of transition probability estimates.
The data processor may further operate to adapt each version of the channel impulse response estimate by generating an intermediate up-dated version of the channel impulse response estimate for each of the transitions from the first states to the subsequent state and combining the intermediate up-dated versions of the channel impulse response estimate weighted by said corresponding plurality of transition probability estimates.
The equaliser may further operate to substantially maximise a probability of correctly detected data symbols in dependence upon a plurality of state probability estimates each of which state probability estimates is associated with one of the plurality of states of the communications channel and calculated from the received signals in combination with the adapted version of said channel impulse response estimate associated with the state.
Advantageously, the data processor may operate to generate each adapted version of the channel impulse response estimate by weighting the intermediate up-dated versions of the channel impulse response estimate by a combination of the corresponding transition probability estimates and the state probability estimate for each of the first states which determine the transitions to the state with which the channel impulse response is associated. The transition probability estimates and the state probability estimates may be calculated in accordance with a symbol-by-symbol estimator algorithm such as the BCJR algorithm.
According to an aspect of the present invention, there is provided a method of detecting data symbols from signals received from a communications channel, comprising the steps of;
- calculating a plurality of transition probability estimates associated with transitions from first states of the communications channel to at least one subsequent state of the communications channel, from an estimate of an impulse response of the communications channel in combination with the received signals;
- adapting the channel impulse response estimate associated with the subsequent state in dependence upon the transition probability estimates; and - detecting the data symbols from the plurality of transition probability estimates.
The method of detecting data may further include the steps of;
- generating a plurality of versions of the channel impulse response estimate, each of which is associated with a state of the communications channel; and - adapting each of the channel impulse response estimates in dependence upon a corresponding plurality of the transition probability estimates for transitions from a plurality of the first states to the state with which the channel impulse response is associated.
The step of adapting each of the plurality of versions of the channel impulse response estimate further comprises the steps of;
- for each transition from the plurality of first states (m') to the subsequent state associated with the channel impulse response estimate, generating an intermediate up-dated version of the channel impulse response estimate;
- weighting each of said intermediate versions with said transition probability estimates and - combining said weighted intermediate up-dated versions to generate said adapted channel impulse response estimate.
One embodiment of the present invention will now be described by way of example only with reference to the accompanying drawings, wherein, FIGURE 1 is a schematic block diagram of part of a radio communications channel used within a mobile radio telephone system, FIGURE 2 is a schematic representation of a time division multiple access frame, FIGURE 3 is a schematic block diagram of the radio communications receiver shown in figure 1, FIGURE 4 is a schematic block diagram of a data detector, which appears in figure 3, FIGURE 5 is a schematic block diagram of part of the reference signal generator shown in figure 4, FIGURE 6 is an illustration of a trellis modelled by the data detector shown in figures 3 and 4.
While the present invention finds application in many areas within the digital communications art, and therefore to receivers for corrupted signals generally, an embodiment of the present invention will be described with reference to a radio communications receiver, and in particular to a radio communications receiver operating within a time division multiple access mobile radio communications system. Examples of such systems are the Global System for Mobiles (GSM), and a system operating in accordance with a hybrid Time Division and Code Division Multiple Access system, such as that described in an article entitled "Performance of a Cellular Hybrid C-TDMA Mobile Radio System Applying Joint Detection and Coherent Receiver Antenna Diversity" by G. Blanz, A.
Klein, M. Nathan and A. Steil published in the IEEE Journal on Selected Areas in Communications, Volume 12, no. 4, May 1994 at page 568.
In figure 1, a block diagram is shown, which is representative of parts of a radio communications channel operating within a mobile radio telephone system. In figure 1 digital data s(n) to be communicated over the radio communications channel is fed to a modulator and digital to analogue converter 1, via a data encoder 2. The encoder 2, operates to transform the digital data s(n) to encoded data symbols x(n) in accordance with a forward error correction algorithm. In the GSM system for example, the encoder applies a half rate convolutional code to the most important bits of a frame of digitally encoded speech. Analogue signals generated by the modulator 1 are fed to an input of a transmitter 3, which serves to amplify and up-convert the analogue signals to a radio frequency. The radio frequency signals are thereafter radiated by an antenna 4. The radio signals radiated by the antenna 4, propagate between the antenna 4, and a receive antenna 6 via the ether.
A characteristic of mobile radio communications systems, is that radio signals travel between the transmit antenna 4, and the receive antenna 6, via a plurality of paths, such as a direct path represented by the line 8, and indirect paths 10 reflected from objects, such as a house 10. The example indirect path is represented by the line 12. Inter-symbol interference is generated in the received radio signals, as a result of the radio signals travelling between the transmit and the receive antennas 4, 6, by multi-paths. The received signals detected by the receive antenna 6, are fed to a down-conversion and base band unit 14 which operates to convert the received radio signals from the radio frequency to a base band frequency, and furthermore the base band unit 14, operates to analogue to digital convert the base band signals. As such digital samples of the base band signals represented as z(n), are generated at an output of the base band unit 14. The digital samples of the received base band signals z(n), are thereafter fed to a data detector 16, which operates to generate an estimate of the digital data fed to the modulator 1 which is designated as .z(n). The estimate of the digital data is thereafter fed to a decoder 18 which serves to operate in accordance with a decoding algorithm to effect a reverse of the encoding operation performed by the data encoder 2. In the case of GSM the decoder 18, operates in accordance with a Viterbi decoding algorithm to decode the convolutional code. Thus, at an output of the decoder 18, an estimate of the data communicated over the channel is generated which is represented as s(n).
Time division multiple access systems are characterised in that signals transmitted on a radio frequency carrier signal are divided into a plurality of time slots in which each slot represents a channel allocated to a different mobile unit.
This is illustrated in figure 2, where the transmission of data on a radio frequency carrier is represented by the lines 22, 24. As is illustrated in figure 2, where time is represented by the lines 22, 24, going from left to right across the diagram, the carrier signal is divided into a plurality of time slots 1 to M. As illustrated in figure 2 a mobile communicates a burst of radio frequency signals in one of the time slots, which is illustrated for the time slot 2, by the burst of radio signals 28. The burst of radio frequency signals 28, comprises data bearing parts 30, and a part in which known signals corresponding to the aforementioned training sequence are transmitted. The training sequence 32, provides the data detector 16 with a means for estimating an impulse response of the channel through which the burst of radio signals 28, has passed between the transmitter 3 and the receiver 14.
As already explained, in a situation where a mobile unit is travelling at high speed, a Doppler shift, that is, a change in the frequency of the communicated radio signals with respect to time, is large enough to cause a significant change in the impulse response of the communications channel with respect to time which is experienced by the radio signals. As such data symbols transmitted at temporal positions removed from a temporal location of the training sequence in the middle of the burst 28, will experience a substantially different channel impulse response than the channel impulse response estimate determined at the temporal position of the training sequence. Therefore, for example, the channel impulse response estimate generated from the training sequence will no longer be representative of the channel impulse response at either end of the burst of radio communications signals 28. The equaliser which forms part of the data detector 16, must therefore mitigate these effects.
Furthermore, in some applications, such as in a case where the decoder 18, is required to operate in accordance with a turbo detection technique, a symbol detector such as the BCJR-detector is preferred as a means for equalising the received signals. The BCJR-detector is an example of a symbol estimator which operates to maximise the likelihood of a symbol on a symbol-by-symbol basis as opposed to a Viterbi equaliser which operates to maximise the likelihood of a sequence of symbols. However a problem with the symbol-by-symbol type equalisers is that there are no decisions made as to which of the plurality of transitions leading to a subsequent state is selected for further processing of the algorithm because the symbol estimated at the latest step through the trellis diagram is determined from a combination of predecessor states. However, a data detector including an equaliser which operates as a symbol-by-symbol detector and which adapts the channel impulse response in accordance with an example embodiment of the present invention is presented in figure 3 where parts also appear in the figures 1 and 2 bear identical numerical designations.
A receiver for detecting a burst of radio communications signals and for recovering the data conveyed by the radio signals, is shown in block diagram form in Figure 3. In Figure 3 the radio signals 8, 10, are detected by the antenna 4 and fed to the down conversion and baseband processing unit 14. The digital samples of the burst of radio signals are thereafter fed to a data detector 19 which operates to determine a sequence of digital data symbols corresponding to the digital samples z(n) by processing the digital signal samples z(n) to the effect that the inter-symbol interference and fading effects are substantially mitigated. At an output of the data detector 19, the estimates of the detected digital symbols x(n) are presented on a conductor 34 to the decoder 18. A final estimate of the communicated data s(n) is presented on a conductor 36.
Also generated at the output of the data detector 19 is a set of soft decision metrics associated with each of the detected data symbols x(n) which are fed on a further conductor 38 from the data detector 19. On a conductor 40, the data detector 19, generates a vector of error signals e(n) comprising an error signal em(n) associated with each of the states m modelled by the data detector, as will shortly be described.' The error signals are fed on conductor 40' to an input of a channel estimate adapter 42. A further input to the channel estimate adapter 42 is provided by the soft decision data from the conductor 38'. The channel estimate adapter 42 operates to generate at an output conductor 44, a set of channel impulse response estimates which are fed to a reference signal former 46. The signals generated on a conductor 44 from the channel estimate adapter 42, are representative of a set of channel impulse response estimates, each state of the channel modelled by the data detector 19, being provided with one of the set of separately adapted channel estimate, as will shortly be explained. The reference signal former 46, therefore operates to convolve each of the set of sequences associated with a corresponding state of the channel modelled by the data detector 19, with an adapted version of the channel impulse response provided by the channel estimate adapter 42. The reference signal former 46, generates at an output conductor 70, a set of reference signals each of which is associated with a corresponding state transition of the trellis modelled by the data detector 19 and which is formed for each transition from a first state of the channel to a subsequent state of the channel. In order to provide an initial estimate of the channel impulse response, channel initialiser 50, is coupled to the output of the down conversion and base band unit 14, and serves to extract the mid-amble training sequence from the sequence of signal samples z(n), and to convolve this with a locally generated version of the training sequence which serves to yield an initial estimate of the channel impulse response, in accordance with a technique well known to those skilled in the art. This channel impulse response estimate is fed via conductor 51 to the channel estimate adapter 42. Also fed to the channel estimate adapter 42, via conductor 52, is a set of adaptation tap weight coefficients f~~ =~f~o~~m~w~w~a~ Provided to an adaptation algorithm which up dates the channel impulse response estimate. The adaptation coefficients ,u;";t =~~o"u,,.....,fc4~ are fixed for the operation of the data detector 16, in accordance with pre-determined operating parameters.
As will be appreciated, the embodiment of the present invention may be understood principally with reference to the operation of the data detector 19, the channel estimate adapter 42 and the reference signal former 46 shown in Figure 3. To facilitate a better understanding a more detailed block diagram of these blocks 19, 42 and 46 is presented in Figure 4, where parts also appearing in Figure 3 bear identical numerical designations.
In Figure 4 the channel estimate adapter 42, is shown to be comprised of a data processor 41, and a plurality of data stores 43, coupled thereto. Two vectors of data from the first and second conductors are 40', 38', are fed to the data processor 41. On the first input 40', is a vector comprised of the soft decision data SD (n), with a soft decision datum SD (n) associated with each of the states m modelled by the m data detector 19. On the second input 38', a vector of the error data a (n), is fed to the data processor 41. The error data comprises an error datum em(n) associated with each of the states m modelled by the data detector 19. Fed on the third conductor 51, to the data processor 41, is a further vector comprising the set of adaptation coefficients ,u, which may be switched between two values in dependence upon which of the mid-amble and the data symbols are being processed by the data detector. The adaptation coefficients are otherwise fixed for the operation of the equaliser. The data processor 41, adapts each of the channel impulse response estimates stored in the data stores.
The reference signal generator 46, comprises a plurality cf finite impulse response filters 56, an example of which 58, is shown in Figure 5, where parts also appearing in Figure 4 bear identical numerical designations. As shown in Figure 5, 5 the finite impulse response filter 58, is fed on an input 59, with possible data symbols bE{-1, +1} corresponding to a possible values of the latest symbol, resulting in transitions from a first state of the channel to a subsequent state of the channel modelled by the trellis. In this 10 example, we assume a binary modulation scheme, so that, the possible data symbols are -1, +1. Thus for each possible symbol that could form the latest detected data symbol, b there is generated a corresponding reference symbol yi ~, associated with the i-th symbol for the j-th state. The 15 example reference signal generator shown in Figure 5 corresponds to state 0 of the channel. The finite impulse response filter 58, is formed from a shift register 60, having a plurality of symbol delays 62, and a corresponding set of multipliers 64 and adders 66, which operate to scale symbols present at the corresponding output of the symbol delays 62 of the shift register 60, with a set of impulse response coefficients wi. The data symbols multiplied by the impulse response coefficients wi are thereafter summed by the adders 66, and form the reference signals y_I,o y+~,o at an output 68 of the finite impulse response filter 58.
Correspondingly, each state of the states of the channel modelled by the data detector 19, has a finite impulse response filter thereby providing at each output thereof a number of reference signals corresponding to the number of transitions from a first state (m') entering a subsequent state (m) modelled by the data detector 19. The reference signals are fed to the data detector 19, via parallel conductors 70 as shown in Figure 4.
As already mentioned, a state of the channel is determined by the number of symbols which have an influence on a detected symbol. Thus, if the inter-symbol interference causes a current symbol to be influenced by V-1 earlier symbols, then the number of possible states of the channel will be Bv-i, where B is the alphabet size of the data bearing symbols.
Thus for a binary modulation scheme B = 2. For the present example the finite impulse response filter models a channel with inter symbol interference corresponding to V = 5 symbols. Thus the number of states modelled by the data detector is 24 = 16.
An example of a trellis diagram modelled by the channel equaliser is shown in figure 6. In figure 6 one stage in the trellis diagram is represented with example transitions with between each state. The example trellis diagram has 16 states corresponding to a channel which has a memory V of five symbols. On the left side of the trellis diagram first states associated with a time t-1 or correspondingly n-1 in terms of signal samples are denoted m' with new or subsequent states on the right side denoted m. Between each of the states of the trellis is a corresponding transition associated with a latest symbol to be detected by the equaliser. It is the latest symbol which determines the new or subsequent state m provided that the old or first state is m'.
The exemplified embodiment of the present invention will be described for a symbol-by-symbol detector which operates in accordance with the BCJR-algorithm well known to those skilled in the art. In the aforementioned article, published in IEEE Transactions on Information Theory, a full description of the BCJR algorithm is presented with reference to the decoding of convolutional codes. For completeness of the description of the embodiment of the invention, a brief out line of the BCJR algorithm will be given in the following paragraphs. However, a full explanation is provided in the aforementioned prior art disclosure which is incorporated herein by reference.
The BCJR algorithm is based on the calculation of the a-posteriori probabilities of the communications channel being in states PSSn =ml z(n)t (with Sn representing the states at symbol sample n, and Jm representing one subsequent state) and the probability of transitions between states PjSn-1 =m';Sn =ml z(n)~ , where m' is a first or old state at salmple n-1, and z (n) - z (1) , z (2) , z (3) , . . . . . , z (n) are the digital signal samples, and for the present explanation, each sample corresponds to a transmitted symbol. The detection algorithm is therefore based on the calculation of the joint probabilities given in equations (1) and (2), where equation (1) is the probability of the channel being in state m, and equation (2) is the probability of a transition from state m' at symbol sample n-1 to state m at symbol sample n. For simplicity, the following explanation is given in terms of samples n, instead of time t, and with one sample per symbol, n also corresponds to detected symbols.
~.n (m) = P {Sn = m; z(n)} ( 1 ) n (m', n) = P {Sn _ 1 = m'; Sn = m; z(n)~ ( 2 ) The probabilities associated with equations (1) and (?_) are calculated using equations (3), (4) and (5):
an (m) = P S Sn = m; z(n)~ ( 3 ) ~3n (m) = P{z(n + 1) l Sn = m} ( 4 ) yn(m',m)=PjSn =m;z(n)l n_1 =m'~ (5) It can be shown that equations (1) and (2) can be described from equations (3), (4) and (5) as shown in equations (6) and (7) ~,n (m) = an (m) ~ ~n (m) ~n (m~ m) - an _ 1 (m') ~ yn (m', m) ~ ~n (m) The function given by equation (3) is calculated in a forward recursion procedure of the BCJR algorithm, that is to say, moving recursively through the corresponding trellis diagram of the trellis from states at symbol samples n-1 to states at symbol samples n. The forward recursion may be represented by equation (8):
an (m) _ ~ an _ 1 (m') ~ yn _ 1 (m', m) ( 8 ) all statesm' The function given by equation (4) is calculated in a backward recursion procedure of the BCJR-algorithm, that is to say, moving recursively through the corresponding trellis diagram of the trellis from states at samples n to states at samples n+1. The backward recursion may be represented by equation ( 9 ) .
~n(m~)= ~~n+1(m)~yn+1(m~'m) all statesm To effect calculation of the functions according to equations (8) and (9), it remains to define the function yn(m',m) which is the conditional probability of state m at sample n and the received symbol z(n), under the condition that the predecessor state is m~. This is calculated from equation (10) .
Yn(m',m)= ~ P{X(n)=blSn =m;Sn-1 =m'}~P{Sn =mlSn-1 =m'~~P{z(n)l x(n)=bj allx(n) (10) In equation (10) the factor Ptx(n)=blSn=m;Sn-1=m'~ will be either 0 or 1, in dependence utpon whether or not a branch transition in the trellis diagram is present or not. If the modulation scheme is binary (b E (-l, +1}) , with the effect that the modulating symbols are binary (such as Binary Phase Shift Keying or Gaussian Minimum Phase Shift Keying) then there will only be two values per state Sn = m which are non zero.
The factor PjSn =mlSn-1 =m'~ is determined in accordance with a priory infotrmation of the transmitted data sequence.
If a part of the data sequence is known, then this can be used to determine P(Sn =mlSn-1 =m'~ . For example, P{Sn=mlSn-1=m'~=P{x(n)=-1} for a transition from state m' to m where a known data symbol is -1, and P{Sn =mlSn-1 =m'~=P{x(n)=+1} for a transition from state m' to m where a known data symbol is +1. Thus, if a modulating data symbol is known to be x(n) - -1 or +1, then Pfx(n)) will be 1. Otherwise these probabilities are set to 1/B where B =
2 for a binary modulation scheme. Finally the factor P{z(n) l x(n) = b} is a factor which depends on the channel .
As an approximation the error signal em(n) is used as an approximation for the latest detected symbol, formed by a comparison between the received signal sample per symbol z(n) and the reference signal y(n), which is expressed by equation (11) (z(n) -Yb,m~ ) P{z(n) l x(n) = b} _ ( 11 ) (z(n) -.Yb~m~) all m' where as before (b E {-1, +1}) for a binary symbol sequence.
The function yn(m',m) can be split into two parts, where each part is associated with the latest symbol being one of two 5 values (-1, +1) for the binary case. This is given in equation (12):
yn(m~.m) =Yn~-1(m~~m~X(n) _ -1)+Yn~+1(m~~m~x(n) _ +1) ( 12 ) 10 Finally soft decision detection is effected using the BCJR
algorithm by equation (13), where the top part of the function is generated by summing the probabilities of transitions associated with the symbol x(n) being -1, and the bottom part of the function is generated by summing the 15 probabilities of transitions associated with the symbol x(n) being +1.
(-1 ~ transitions~.n (m)) SD(n) = log m ( 13 ) (+1 ~ transitions~.n (m)) m Hard division output from the BCJR algorithm is determined 20 with reference to a threshold at zero, so that the hard decision output is estimated in accordance with equation (14) _ -1 if SD(n))0 x(n) + 1 if SD(n)(0 ( 14 ) It is however the soft decision outputs which makes the BCJR
algorithm particularly useful for turbo decoding used in a subsequent error detection stage, such as that shown in figures 1 and 3 as decoder 18.
As will be appreciated from the above discussions, symbol-by-symbol detectors such as the BCJR algorithm are characterised in that there are no decisions made as to which of the plurality of transitions leading to a subsequent state is selected for further processing of the algorithm because the symbol estimated at the latest step through the trellis diagram is determined from a combination of predecessor states. Thus, unlike the Viterbi algorithm no unique survivor path is selected, so that the new metric is formed as a combination of rather than a selection from two candidates.
Returning to the description of the example embodiment of the present invention, adaptation of the channel impulse response estimate so as to substantially mitigate effects associated with Doppler frequency shift causing changes in the channel impulse response with time, will now be described. As already explained, the new state metric during the forward and also the backward recursions in the BCJR algorithm is the sum of contributions from several candidates (two for binary symbols). Adaptation of the channel impulse response, for a symbol-by-symbol detector is effected by calculating the new tap coefficients using contributions from transitions from all possible first states (m') and the probability of these candidate first states as a weighting factor. As such, the adaptation principle is expressed by equations (14), (15), and ( 16 ) wm -1 = Lwm, _1 +Om, -1 ( 14 ) > > >
wm +1 = Lwm, ,+1 + ~m'~+1 ( 15 ) 3 0 wm = Wn,-1 ~ wm~_1 +Wn~+1 ~ wm,+1 ( 16 ) Where weighting factors Wn-1 and m +1 are given by > >
equations (17) and (18):
an,-1 (m).Yn~_1 (m. ~ m) a (m), y (m~ , m) + a (m). y (m' ~ m) ( 17 ) n,-1 n,-1 n,+1 n,+1 an~+1 (m)' Yn,+1 (m~' m) m,+ 1 a (m). Y (m' , m) + a (m). y (m' ~ m) ( 18 ) n,-1 n,-1 n,+1 n,+1 In equations ( 14 ) and ( 15 ) wm,-1 and H'm,+1 are intermediate up-dated versions of the channel impulse response estimate, generated by up-dating the versions of the channel impulse response estimate wm, -1' wm',+1' associated with the first states m', in accordance with adaptation factors Om~-1' ~m~ +1 calculated according to equations ( 19 ) and ( 20 ) . The adaptation factors ~m~ -1' Vim',+1' are calculated by the data processor 41, of the channel impulse response adapter 42, in dependence upon the data symbol (-1, +1) associated with transitions from the first states m' to the subsequent state m. The intermediate up-dated versions of the channel impulse response estimate u'm,-1' Wm,+1' are formed by adding adaptation factors Om~,_1' Vim',+1' to the versions of the channel impulse response estimate associated with the first states m', in some way. For example, one such way is given as an example in equations (14) and (15). The equations (14) and (15), correspond to the well-known leaky Least Mean Sequences equation, with a leakage factor L, for example with L = (1 - lleast significant bit) being used for improved stability. However, as will be appreciated, other adaptation algorithms may be used. The adaptation factors Om~,_1' Vim',+1' in equations ( 14 ) and ( 15) correspond to changes to the channel impulse response coefficients associated with the adaptation step size ~, for a corresponding error signal, in accordance with the least mean squares algorithm, as expressed by equations (19) and (20):
_ (19) Vim',-1 Vim' ~ xm',-1 Vim',+1 Vim' ~ xm',+1 ( 2 0 ) Where a is the error signal' xm'-1 is a symbol vector associated with the first state m' where the new symbol is -1, and xm',+1 is a symbol vector associated with the first state m', where the new symbol is +1. The adapted version of the channel impulse response estimate wm is formed in accordance with equation (16), by scaling the intermediate up-dated versions of the channel impulse response estimates 'vm,-1' wm,+1' by the weighting factors m-1' Wn,+1' and summing the result.
As will be appreciated by those skilled in the art other symbol-by-symbol detectors may also be used with the present invention. A further example of a symbol-by-symbol detector is a detector which operates in accordance with the Maximum A-Posteriors (MAP) algorithm. Symbol-by-symbol detectors are characterised in that transitions in a trellis diagram modelling the state of the channel are retained, in that all possible paths into a subsequent state contribute to the subsequent state metric. Adaptation of the channel impulse response used in the detection of the data with a symbol-by-symbol detector in accordance with the example embodiment of the present invention can be interpreted as calculating an average coefficient vector that results from averaging over all candidate old states. The probability ratio (equations (17) and (18)) is proposed as a weighting factor for adaptation, as this provides an average value calculated from the probability of occurrence. The two extreme cases are the following: If one candidate is much more likely than the other' the influence of the other is suppressed and the result is equivalent to the case for an adaptive Viterbi equaliser as herein before described. If both candidates (differing in the latest impulse response tap) are equally likely no effective update is performed for the latest detected symbol, and the new coefficient vector just becomes the (unweighted) average of both contributions Wn,-1 and Wn~+1.
As will be appreciated by those skilled in the art, various modifications may be made to the aforementioned embodiment without departing from the scope of the present invention.
For example, although the example embodiment has been described with a separate channel impulse response estimate per state modelled by the data detector, it will be appreciated that a single channel impulse response estimate could be adapted in accordance with the principles of the invention, and used by the data detector to estimate the symbols. Furthermore, the present invention finds application for detecting data received from a variety of communications channels, where a limitation in the bandwidth of the channel or other effects cause inter-symbol interference.
Time division multiple access systems are characterised in that signals transmitted on a radio frequency carrier signal are divided into a plurality of time slots in which each slot represents a channel allocated to a different mobile unit.
This is illustrated in figure 2, where the transmission of data on a radio frequency carrier is represented by the lines 22, 24. As is illustrated in figure 2, where time is represented by the lines 22, 24, going from left to right across the diagram, the carrier signal is divided into a plurality of time slots 1 to M. As illustrated in figure 2 a mobile communicates a burst of radio frequency signals in one of the time slots, which is illustrated for the time slot 2, by the burst of radio signals 28. The burst of radio frequency signals 28, comprises data bearing parts 30, and a part in which known signals corresponding to the aforementioned training sequence are transmitted. The training sequence 32, provides the data detector 16 with a means for estimating an impulse response of the channel through which the burst of radio signals 28, has passed between the transmitter 3 and the receiver 14.
As already explained, in a situation where a mobile unit is travelling at high speed, a Doppler shift, that is, a change in the frequency of the communicated radio signals with respect to time, is large enough to cause a significant change in the impulse response of the communications channel with respect to time which is experienced by the radio signals. As such data symbols transmitted at temporal positions removed from a temporal location of the training sequence in the middle of the burst 28, will experience a substantially different channel impulse response than the channel impulse response estimate determined at the temporal position of the training sequence. Therefore, for example, the channel impulse response estimate generated from the training sequence will no longer be representative of the channel impulse response at either end of the burst of radio communications signals 28. The equaliser which forms part of the data detector 16, must therefore mitigate these effects.
Furthermore, in some applications, such as in a case where the decoder 18, is required to operate in accordance with a turbo detection technique, a symbol detector such as the BCJR-detector is preferred as a means for equalising the received signals. The BCJR-detector is an example of a symbol estimator which operates to maximise the likelihood of a symbol on a symbol-by-symbol basis as opposed to a Viterbi equaliser which operates to maximise the likelihood of a sequence of symbols. However a problem with the symbol-by-symbol type equalisers is that there are no decisions made as to which of the plurality of transitions leading to a subsequent state is selected for further processing of the algorithm because the symbol estimated at the latest step through the trellis diagram is determined from a combination of predecessor states. However, a data detector including an equaliser which operates as a symbol-by-symbol detector and which adapts the channel impulse response in accordance with an example embodiment of the present invention is presented in figure 3 where parts also appear in the figures 1 and 2 bear identical numerical designations.
A receiver for detecting a burst of radio communications signals and for recovering the data conveyed by the radio signals, is shown in block diagram form in Figure 3. In Figure 3 the radio signals 8, 10, are detected by the antenna 4 and fed to the down conversion and baseband processing unit 14. The digital samples of the burst of radio signals are thereafter fed to a data detector 19 which operates to determine a sequence of digital data symbols corresponding to the digital samples z(n) by processing the digital signal samples z(n) to the effect that the inter-symbol interference and fading effects are substantially mitigated. At an output of the data detector 19, the estimates of the detected digital symbols x(n) are presented on a conductor 34 to the decoder 18. A final estimate of the communicated data s(n) is presented on a conductor 36.
Also generated at the output of the data detector 19 is a set of soft decision metrics associated with each of the detected data symbols x(n) which are fed on a further conductor 38 from the data detector 19. On a conductor 40, the data detector 19, generates a vector of error signals e(n) comprising an error signal em(n) associated with each of the states m modelled by the data detector, as will shortly be described.' The error signals are fed on conductor 40' to an input of a channel estimate adapter 42. A further input to the channel estimate adapter 42 is provided by the soft decision data from the conductor 38'. The channel estimate adapter 42 operates to generate at an output conductor 44, a set of channel impulse response estimates which are fed to a reference signal former 46. The signals generated on a conductor 44 from the channel estimate adapter 42, are representative of a set of channel impulse response estimates, each state of the channel modelled by the data detector 19, being provided with one of the set of separately adapted channel estimate, as will shortly be explained. The reference signal former 46, therefore operates to convolve each of the set of sequences associated with a corresponding state of the channel modelled by the data detector 19, with an adapted version of the channel impulse response provided by the channel estimate adapter 42. The reference signal former 46, generates at an output conductor 70, a set of reference signals each of which is associated with a corresponding state transition of the trellis modelled by the data detector 19 and which is formed for each transition from a first state of the channel to a subsequent state of the channel. In order to provide an initial estimate of the channel impulse response, channel initialiser 50, is coupled to the output of the down conversion and base band unit 14, and serves to extract the mid-amble training sequence from the sequence of signal samples z(n), and to convolve this with a locally generated version of the training sequence which serves to yield an initial estimate of the channel impulse response, in accordance with a technique well known to those skilled in the art. This channel impulse response estimate is fed via conductor 51 to the channel estimate adapter 42. Also fed to the channel estimate adapter 42, via conductor 52, is a set of adaptation tap weight coefficients f~~ =~f~o~~m~w~w~a~ Provided to an adaptation algorithm which up dates the channel impulse response estimate. The adaptation coefficients ,u;";t =~~o"u,,.....,fc4~ are fixed for the operation of the data detector 16, in accordance with pre-determined operating parameters.
As will be appreciated, the embodiment of the present invention may be understood principally with reference to the operation of the data detector 19, the channel estimate adapter 42 and the reference signal former 46 shown in Figure 3. To facilitate a better understanding a more detailed block diagram of these blocks 19, 42 and 46 is presented in Figure 4, where parts also appearing in Figure 3 bear identical numerical designations.
In Figure 4 the channel estimate adapter 42, is shown to be comprised of a data processor 41, and a plurality of data stores 43, coupled thereto. Two vectors of data from the first and second conductors are 40', 38', are fed to the data processor 41. On the first input 40', is a vector comprised of the soft decision data SD (n), with a soft decision datum SD (n) associated with each of the states m modelled by the m data detector 19. On the second input 38', a vector of the error data a (n), is fed to the data processor 41. The error data comprises an error datum em(n) associated with each of the states m modelled by the data detector 19. Fed on the third conductor 51, to the data processor 41, is a further vector comprising the set of adaptation coefficients ,u, which may be switched between two values in dependence upon which of the mid-amble and the data symbols are being processed by the data detector. The adaptation coefficients are otherwise fixed for the operation of the equaliser. The data processor 41, adapts each of the channel impulse response estimates stored in the data stores.
The reference signal generator 46, comprises a plurality cf finite impulse response filters 56, an example of which 58, is shown in Figure 5, where parts also appearing in Figure 4 bear identical numerical designations. As shown in Figure 5, 5 the finite impulse response filter 58, is fed on an input 59, with possible data symbols bE{-1, +1} corresponding to a possible values of the latest symbol, resulting in transitions from a first state of the channel to a subsequent state of the channel modelled by the trellis. In this 10 example, we assume a binary modulation scheme, so that, the possible data symbols are -1, +1. Thus for each possible symbol that could form the latest detected data symbol, b there is generated a corresponding reference symbol yi ~, associated with the i-th symbol for the j-th state. The 15 example reference signal generator shown in Figure 5 corresponds to state 0 of the channel. The finite impulse response filter 58, is formed from a shift register 60, having a plurality of symbol delays 62, and a corresponding set of multipliers 64 and adders 66, which operate to scale symbols present at the corresponding output of the symbol delays 62 of the shift register 60, with a set of impulse response coefficients wi. The data symbols multiplied by the impulse response coefficients wi are thereafter summed by the adders 66, and form the reference signals y_I,o y+~,o at an output 68 of the finite impulse response filter 58.
Correspondingly, each state of the states of the channel modelled by the data detector 19, has a finite impulse response filter thereby providing at each output thereof a number of reference signals corresponding to the number of transitions from a first state (m') entering a subsequent state (m) modelled by the data detector 19. The reference signals are fed to the data detector 19, via parallel conductors 70 as shown in Figure 4.
As already mentioned, a state of the channel is determined by the number of symbols which have an influence on a detected symbol. Thus, if the inter-symbol interference causes a current symbol to be influenced by V-1 earlier symbols, then the number of possible states of the channel will be Bv-i, where B is the alphabet size of the data bearing symbols.
Thus for a binary modulation scheme B = 2. For the present example the finite impulse response filter models a channel with inter symbol interference corresponding to V = 5 symbols. Thus the number of states modelled by the data detector is 24 = 16.
An example of a trellis diagram modelled by the channel equaliser is shown in figure 6. In figure 6 one stage in the trellis diagram is represented with example transitions with between each state. The example trellis diagram has 16 states corresponding to a channel which has a memory V of five symbols. On the left side of the trellis diagram first states associated with a time t-1 or correspondingly n-1 in terms of signal samples are denoted m' with new or subsequent states on the right side denoted m. Between each of the states of the trellis is a corresponding transition associated with a latest symbol to be detected by the equaliser. It is the latest symbol which determines the new or subsequent state m provided that the old or first state is m'.
The exemplified embodiment of the present invention will be described for a symbol-by-symbol detector which operates in accordance with the BCJR-algorithm well known to those skilled in the art. In the aforementioned article, published in IEEE Transactions on Information Theory, a full description of the BCJR algorithm is presented with reference to the decoding of convolutional codes. For completeness of the description of the embodiment of the invention, a brief out line of the BCJR algorithm will be given in the following paragraphs. However, a full explanation is provided in the aforementioned prior art disclosure which is incorporated herein by reference.
The BCJR algorithm is based on the calculation of the a-posteriori probabilities of the communications channel being in states PSSn =ml z(n)t (with Sn representing the states at symbol sample n, and Jm representing one subsequent state) and the probability of transitions between states PjSn-1 =m';Sn =ml z(n)~ , where m' is a first or old state at salmple n-1, and z (n) - z (1) , z (2) , z (3) , . . . . . , z (n) are the digital signal samples, and for the present explanation, each sample corresponds to a transmitted symbol. The detection algorithm is therefore based on the calculation of the joint probabilities given in equations (1) and (2), where equation (1) is the probability of the channel being in state m, and equation (2) is the probability of a transition from state m' at symbol sample n-1 to state m at symbol sample n. For simplicity, the following explanation is given in terms of samples n, instead of time t, and with one sample per symbol, n also corresponds to detected symbols.
~.n (m) = P {Sn = m; z(n)} ( 1 ) n (m', n) = P {Sn _ 1 = m'; Sn = m; z(n)~ ( 2 ) The probabilities associated with equations (1) and (?_) are calculated using equations (3), (4) and (5):
an (m) = P S Sn = m; z(n)~ ( 3 ) ~3n (m) = P{z(n + 1) l Sn = m} ( 4 ) yn(m',m)=PjSn =m;z(n)l n_1 =m'~ (5) It can be shown that equations (1) and (2) can be described from equations (3), (4) and (5) as shown in equations (6) and (7) ~,n (m) = an (m) ~ ~n (m) ~n (m~ m) - an _ 1 (m') ~ yn (m', m) ~ ~n (m) The function given by equation (3) is calculated in a forward recursion procedure of the BCJR algorithm, that is to say, moving recursively through the corresponding trellis diagram of the trellis from states at symbol samples n-1 to states at symbol samples n. The forward recursion may be represented by equation (8):
an (m) _ ~ an _ 1 (m') ~ yn _ 1 (m', m) ( 8 ) all statesm' The function given by equation (4) is calculated in a backward recursion procedure of the BCJR-algorithm, that is to say, moving recursively through the corresponding trellis diagram of the trellis from states at samples n to states at samples n+1. The backward recursion may be represented by equation ( 9 ) .
~n(m~)= ~~n+1(m)~yn+1(m~'m) all statesm To effect calculation of the functions according to equations (8) and (9), it remains to define the function yn(m',m) which is the conditional probability of state m at sample n and the received symbol z(n), under the condition that the predecessor state is m~. This is calculated from equation (10) .
Yn(m',m)= ~ P{X(n)=blSn =m;Sn-1 =m'}~P{Sn =mlSn-1 =m'~~P{z(n)l x(n)=bj allx(n) (10) In equation (10) the factor Ptx(n)=blSn=m;Sn-1=m'~ will be either 0 or 1, in dependence utpon whether or not a branch transition in the trellis diagram is present or not. If the modulation scheme is binary (b E (-l, +1}) , with the effect that the modulating symbols are binary (such as Binary Phase Shift Keying or Gaussian Minimum Phase Shift Keying) then there will only be two values per state Sn = m which are non zero.
The factor PjSn =mlSn-1 =m'~ is determined in accordance with a priory infotrmation of the transmitted data sequence.
If a part of the data sequence is known, then this can be used to determine P(Sn =mlSn-1 =m'~ . For example, P{Sn=mlSn-1=m'~=P{x(n)=-1} for a transition from state m' to m where a known data symbol is -1, and P{Sn =mlSn-1 =m'~=P{x(n)=+1} for a transition from state m' to m where a known data symbol is +1. Thus, if a modulating data symbol is known to be x(n) - -1 or +1, then Pfx(n)) will be 1. Otherwise these probabilities are set to 1/B where B =
2 for a binary modulation scheme. Finally the factor P{z(n) l x(n) = b} is a factor which depends on the channel .
As an approximation the error signal em(n) is used as an approximation for the latest detected symbol, formed by a comparison between the received signal sample per symbol z(n) and the reference signal y(n), which is expressed by equation (11) (z(n) -Yb,m~ ) P{z(n) l x(n) = b} _ ( 11 ) (z(n) -.Yb~m~) all m' where as before (b E {-1, +1}) for a binary symbol sequence.
The function yn(m',m) can be split into two parts, where each part is associated with the latest symbol being one of two 5 values (-1, +1) for the binary case. This is given in equation (12):
yn(m~.m) =Yn~-1(m~~m~X(n) _ -1)+Yn~+1(m~~m~x(n) _ +1) ( 12 ) 10 Finally soft decision detection is effected using the BCJR
algorithm by equation (13), where the top part of the function is generated by summing the probabilities of transitions associated with the symbol x(n) being -1, and the bottom part of the function is generated by summing the 15 probabilities of transitions associated with the symbol x(n) being +1.
(-1 ~ transitions~.n (m)) SD(n) = log m ( 13 ) (+1 ~ transitions~.n (m)) m Hard division output from the BCJR algorithm is determined 20 with reference to a threshold at zero, so that the hard decision output is estimated in accordance with equation (14) _ -1 if SD(n))0 x(n) + 1 if SD(n)(0 ( 14 ) It is however the soft decision outputs which makes the BCJR
algorithm particularly useful for turbo decoding used in a subsequent error detection stage, such as that shown in figures 1 and 3 as decoder 18.
As will be appreciated from the above discussions, symbol-by-symbol detectors such as the BCJR algorithm are characterised in that there are no decisions made as to which of the plurality of transitions leading to a subsequent state is selected for further processing of the algorithm because the symbol estimated at the latest step through the trellis diagram is determined from a combination of predecessor states. Thus, unlike the Viterbi algorithm no unique survivor path is selected, so that the new metric is formed as a combination of rather than a selection from two candidates.
Returning to the description of the example embodiment of the present invention, adaptation of the channel impulse response estimate so as to substantially mitigate effects associated with Doppler frequency shift causing changes in the channel impulse response with time, will now be described. As already explained, the new state metric during the forward and also the backward recursions in the BCJR algorithm is the sum of contributions from several candidates (two for binary symbols). Adaptation of the channel impulse response, for a symbol-by-symbol detector is effected by calculating the new tap coefficients using contributions from transitions from all possible first states (m') and the probability of these candidate first states as a weighting factor. As such, the adaptation principle is expressed by equations (14), (15), and ( 16 ) wm -1 = Lwm, _1 +Om, -1 ( 14 ) > > >
wm +1 = Lwm, ,+1 + ~m'~+1 ( 15 ) 3 0 wm = Wn,-1 ~ wm~_1 +Wn~+1 ~ wm,+1 ( 16 ) Where weighting factors Wn-1 and m +1 are given by > >
equations (17) and (18):
an,-1 (m).Yn~_1 (m. ~ m) a (m), y (m~ , m) + a (m). y (m' ~ m) ( 17 ) n,-1 n,-1 n,+1 n,+1 an~+1 (m)' Yn,+1 (m~' m) m,+ 1 a (m). Y (m' , m) + a (m). y (m' ~ m) ( 18 ) n,-1 n,-1 n,+1 n,+1 In equations ( 14 ) and ( 15 ) wm,-1 and H'm,+1 are intermediate up-dated versions of the channel impulse response estimate, generated by up-dating the versions of the channel impulse response estimate wm, -1' wm',+1' associated with the first states m', in accordance with adaptation factors Om~-1' ~m~ +1 calculated according to equations ( 19 ) and ( 20 ) . The adaptation factors ~m~ -1' Vim',+1' are calculated by the data processor 41, of the channel impulse response adapter 42, in dependence upon the data symbol (-1, +1) associated with transitions from the first states m' to the subsequent state m. The intermediate up-dated versions of the channel impulse response estimate u'm,-1' Wm,+1' are formed by adding adaptation factors Om~,_1' Vim',+1' to the versions of the channel impulse response estimate associated with the first states m', in some way. For example, one such way is given as an example in equations (14) and (15). The equations (14) and (15), correspond to the well-known leaky Least Mean Sequences equation, with a leakage factor L, for example with L = (1 - lleast significant bit) being used for improved stability. However, as will be appreciated, other adaptation algorithms may be used. The adaptation factors Om~,_1' Vim',+1' in equations ( 14 ) and ( 15) correspond to changes to the channel impulse response coefficients associated with the adaptation step size ~, for a corresponding error signal, in accordance with the least mean squares algorithm, as expressed by equations (19) and (20):
_ (19) Vim',-1 Vim' ~ xm',-1 Vim',+1 Vim' ~ xm',+1 ( 2 0 ) Where a is the error signal' xm'-1 is a symbol vector associated with the first state m' where the new symbol is -1, and xm',+1 is a symbol vector associated with the first state m', where the new symbol is +1. The adapted version of the channel impulse response estimate wm is formed in accordance with equation (16), by scaling the intermediate up-dated versions of the channel impulse response estimates 'vm,-1' wm,+1' by the weighting factors m-1' Wn,+1' and summing the result.
As will be appreciated by those skilled in the art other symbol-by-symbol detectors may also be used with the present invention. A further example of a symbol-by-symbol detector is a detector which operates in accordance with the Maximum A-Posteriors (MAP) algorithm. Symbol-by-symbol detectors are characterised in that transitions in a trellis diagram modelling the state of the channel are retained, in that all possible paths into a subsequent state contribute to the subsequent state metric. Adaptation of the channel impulse response used in the detection of the data with a symbol-by-symbol detector in accordance with the example embodiment of the present invention can be interpreted as calculating an average coefficient vector that results from averaging over all candidate old states. The probability ratio (equations (17) and (18)) is proposed as a weighting factor for adaptation, as this provides an average value calculated from the probability of occurrence. The two extreme cases are the following: If one candidate is much more likely than the other' the influence of the other is suppressed and the result is equivalent to the case for an adaptive Viterbi equaliser as herein before described. If both candidates (differing in the latest impulse response tap) are equally likely no effective update is performed for the latest detected symbol, and the new coefficient vector just becomes the (unweighted) average of both contributions Wn,-1 and Wn~+1.
As will be appreciated by those skilled in the art, various modifications may be made to the aforementioned embodiment without departing from the scope of the present invention.
For example, although the example embodiment has been described with a separate channel impulse response estimate per state modelled by the data detector, it will be appreciated that a single channel impulse response estimate could be adapted in accordance with the principles of the invention, and used by the data detector to estimate the symbols. Furthermore, the present invention finds application for detecting data received from a variety of communications channels, where a limitation in the bandwidth of the channel or other effects cause inter-symbol interference.
Claims (26)
1. A communications receiver for detecting data symbols from signals representative of said data symbols received from a communications channel, said communications receiver comprising an equaliser (19, 46) which operates to detect said data symbols by calculating a plurality of transition probability estimates associated with transitions from first states (m') of the communications channel to at least one subsequent state of the communications channel from an estimate of an impulse response of said communications channel and said received signals, wherein said communications receiver further includes a channel impulse response adapter (42) coupled to said equaliser (19, 46) which operates to adapt said channel impulse response estimate in dependence upon said plurality of transition probability estimates, whereby a likelihood of correctly detecting said data symbols is substantially improved.
2. A communications receiver as claimed in Claim 1, wherein said channel estimate adapter (42) has a data store (43) in which said channel impulse response estimate is stored, and a data processor (41) which operates to adapt said channel impulse response estimate in accordance with an adaptation algorithm in combination with said transition probability estimates.
3. A communications receiver as claimed in Claims 2, wherein said channel estimate adapter (42) further comprises a plurality of data stores (43), each of which data stores (43) is associated with a state (m) of the communications channel and serves to store a version of said channel impulse response estimate, and said data processor (41) operates to adapt each version of said channel impulse response estimate, in accordance with an adaptation algorithm in combination with a corresponding plurality of said transition probability estimates for transitions from a plurality of said first states (m') to the subsequent state (m) with which the channel impulse response estimate is associated.
4. A communications receiver as claimed in Claim 3, wherein said adaptation algorithm operates to generate at least one adaptation factor (~m1,-1 ~m1,+1) with which coefficients of each version of the channel impulse response estimate (~m) are adapted.
5. A communications receiver as claimed in Claim 4, wherein said data processor (41) adapts each version of said channel impulse response estimate (~m) in accordance with said adaptation factor (~m1,-1 ~m1,+1), weighted by a combination of said corresponding plurality of said transition probability estimates.
6. A communications receiver as claimed in Claim 5, wherein the data processor (41) operates to adapt each version of the channel impulse response estimate ~m by generating an intermediate up-dated version of the channel impulse response estimate (~m,-1 ~m,+1) for each of the transitions from the first states (m') to the subsequent state (m) and combining the intermediate up-dated versions of said channel impulse response estimate weighted by said corresponding plurality of transition probability estimates.
7. A communications receiver as claimed in Claim 6, wherein said data processor (41) further operates to generate said intermediate up-dated versions of said channel impulse response estimate (~m,-1 ~m,+1) from the versions of the channel impulse response estimate (~m1,-1 ~m1,+1) associated with the first states (m') in combination with said at least one adaptation factor (~m1,-1 ~m1,+1)
8. A communications receiver as claimed in Claim 7, wherein said at least one adaptation factor (~m',_1' ~m',+1) is generated by said adaptation algorithm in dependence upon detected symbols associated with the transitions from the first states (m') to the subsequent state (m).
9. A communications receiver as claimed in Claim 8, wherein said channel impulse response adapter (42) operates to calculate said adaptation factor in dependence upon error signals calculated from a comparison of the detected symbols combined with a corresponding version of the channel impulse response estimate and said received signals, said adaptation factor (~m'-1' ~m' +1) being determined to the effect that said error signal is substantially minimised.
10. A communications receiver as claimed in Claim 9, wherein said adaptation algorithm which generates said adaptation factor (~m',-1, ~m', +1) forms part of a least mean squares adaptation algorithm, or the like, which operates to generate said intermediate up-dated versions of said channel impulse response estimate (~m,1' ~m,+1) to the effect that said error signal is minimised.
11. A communications receiver as claimed in any preceding Claim, wherein said equaliser (19, 46) further operates to substantially maximise a probability of correctly detected data symbols in dependence upon a plurality of state probability estimates, each of said state probability estimates being associated with one of the plurality of states of said communications channel and is calculated from said received signals in combination with the adapted version of said channel impulse response estimate associated with the state.
12. A communications receiver as claimed in Claim 11, wherein each version of said channel impulse response estimate is adapted by weighting said intermediate up-dated versions of said channel impulse response estimate (~m,-1' ~m,+1) by a combination of said corresponding transition probability estimates and said state probability estimate.
13. A communications receiver as claimed in any of claims 6 to 12, wherein said data processor (41) operates to generate each of said adapted versions of said channel impulse response estimate (~m) in accordance with the equation;
where ~m,-1 and ~m,+1 are the intermediate up-dated versions of the channel impulse response estimate for transitions associated with detected symbols (-1,+1), and W m,-1 and W m,+1 are weighting factors given by;
and substantially as herein before described.
where ~m,-1 and ~m,+1 are the intermediate up-dated versions of the channel impulse response estimate for transitions associated with detected symbols (-1,+1), and W m,-1 and W m,+1 are weighting factors given by;
and substantially as herein before described.
14. A communications receiver as claimed in any preceding Claim, wherein said equaliser operates in accordance with a symbol by symbol detection algorithm such as the BCJR
algorithm, a Maximum A Posteriori algorithm, or the like.
algorithm, a Maximum A Posteriori algorithm, or the like.
15. A mobile radio telephone including a communications receiver as claimed in any preceding claim.
16. A base station forming part of a mobile radio telephone system including a communications receiver as claimed in any preceding claim.
17. A method of detecting data symbols from signals received from a communications channel, comprising the steps of;
- calculating a plurality of transition probability estimates associated with transitions from first states (m') of the communications channel to at least one subsequent state (m) of the communications channel, from an estimate of an impulse response of said communications channel in combination with said received signals;
- adapting said channel impulse response estimate in dependence upon said transition probability estimates; and - detecting said data symbols from said transition probability estimates in combination with said adapted channel impulse response estimate.
- calculating a plurality of transition probability estimates associated with transitions from first states (m') of the communications channel to at least one subsequent state (m) of the communications channel, from an estimate of an impulse response of said communications channel in combination with said received signals;
- adapting said channel impulse response estimate in dependence upon said transition probability estimates; and - detecting said data symbols from said transition probability estimates in combination with said adapted channel impulse response estimate.
18. A method of detecting data symbols as claimed in Claim 17, wherein the step of adapting said channel impulse response estimate further comprises the steps of;
- calculating an adaptation factor by which each of said channel impulse response estimates is adapted using an adaptation algorithm;
- adjusting said adaptation factor in dependence upon said transition probability estimates; and - adapting coefficients of said channel impulse response estimate in dependence upon said adjusted adaptation factor.
- calculating an adaptation factor by which each of said channel impulse response estimates is adapted using an adaptation algorithm;
- adjusting said adaptation factor in dependence upon said transition probability estimates; and - adapting coefficients of said channel impulse response estimate in dependence upon said adjusted adaptation factor.
19. A method of detecting data symbols as claimed in Claims 17 or 18, further including the steps of;
- generating a plurality of versions of said channel impulse response estimate, each of which plurality of versions is associated with a state (m) of said communications channels;
and - adapting each of said channel impulse response estimates in dependence upon a corresponding plurality of said transition probability estimates for transitions from a plurality of said first states to the subsequent state with which the channel impulse response is associated.
- generating a plurality of versions of said channel impulse response estimate, each of which plurality of versions is associated with a state (m) of said communications channels;
and - adapting each of said channel impulse response estimates in dependence upon a corresponding plurality of said transition probability estimates for transitions from a plurality of said first states to the subsequent state with which the channel impulse response is associated.
20. A method of detecting data symbols as claimed in Claim 19, wherein the step of adapting each of said plurality of versions of the channel impulse response estimate further comprises the steps of;
- for each transition from the plurality of first states (m') to the subsequent state (m) associated with the channel impulse response estimate generating an intermediate up-dated version of the channel impulse response estimate;
- weighting each of said intermediate versions with said transition probability estimates; and - combining said weighted intermediate up-dated versions to generate said adapted channel impulse response estimate.
- for each transition from the plurality of first states (m') to the subsequent state (m) associated with the channel impulse response estimate generating an intermediate up-dated version of the channel impulse response estimate;
- weighting each of said intermediate versions with said transition probability estimates; and - combining said weighted intermediate up-dated versions to generate said adapted channel impulse response estimate.
21. A method of detecting data symbols as claimed in Claim 20, wherein the step of generating said intermediate up-dated versions of said channel impulse response estimate comprises the step of;
- adapting the version of the channel impulse response estimate associated with the first states (m') for the transition to the subsequent state (m) in dependence upon said adaptation factor and a detected symbol associated with the transition.
- adapting the version of the channel impulse response estimate associated with the first states (m') for the transition to the subsequent state (m) in dependence upon said adaptation factor and a detected symbol associated with the transition.
22. A method of detecting data symbols as claimed in any of Claims 17 to 21, further including the steps of;
- calculating a plurality of state probability estimates representative of a probability that the communications channel is in a given state from at least one of said plurality of versions of said channel impulse response estimate in combination with said received signals; and - detecting data symbols from said state probability estimates in combination with said plurality of transition probability estimates.
- calculating a plurality of state probability estimates representative of a probability that the communications channel is in a given state from at least one of said plurality of versions of said channel impulse response estimate in combination with said received signals; and - detecting data symbols from said state probability estimates in combination with said plurality of transition probability estimates.
23. A method of detecting data symbols as claimed in Claim 22, wherein the step of adapting each version of the channel impulse response estimate, further includes the step of;
- weighting said intermediate up-dated version of said channel impulse response estimate by a combination of said corresponding transition probability estimates and said state probability estimates.
- weighting said intermediate up-dated version of said channel impulse response estimate by a combination of said corresponding transition probability estimates and said state probability estimates.
24. A method of detecting data symbols as claimed in any of Claims 20 to 23, wherein the step of adapting said channel impulse response estimate (~m)is effected in accordance with the equation; where ~m,-1 and ~m,+1 are the intermediate up-dated versions of the channel impulse response estimate for transitions associated with detected symbols (-1,+1), and W m,-1 and W m,+1 are weighting factors given by;
and substantially as herein before described.
and substantially as herein before described.
25. A method of detecting data symbols as claimed in any of Claims 17, to 24, wherein the step of calculating said state probability estimates and said transition probability estimates is effected by a BCJR algorithm, a Maximum A
Posteriors algorithm, or the like.
Posteriors algorithm, or the like.
26. A communications receiver as herein before described with reference to the accompanying drawings.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB9804786A GB2335123B (en) | 1998-03-07 | 1998-03-07 | Communications receiver and method of detecting data from received signals |
| GB9804786.3 | 1998-03-07 |
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| CA2264414A1 true CA2264414A1 (en) | 1999-09-07 |
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| CA 2264414 Abandoned CA2264414A1 (en) | 1998-03-07 | 1999-03-05 | Communications receiver and method of detecting data from received signals |
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| GB (1) | GB2335123B (en) |
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| US6628706B1 (en) | 1999-12-06 | 2003-09-30 | Telefonaktiebolaget Lm Ericsson (Publ) | Method and apparatus for transforming a channel estimate |
| GB2371953A (en) * | 2001-01-31 | 2002-08-07 | Matsushita Comm Ind Uk Ltd | Viterbi equalizer which compares received data with predicted data based on the channel response estimate to generate path metrics |
| CN102801661B (en) * | 2011-05-25 | 2016-08-03 | 中兴通讯股份有限公司 | A kind of uplink receiving method and device |
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| SE464902B (en) * | 1989-10-24 | 1991-06-24 | Ericsson Telefon Ab L M | PROCEDURE TO ADAPT A VITERBIAL ALGORITHM TO A CHANNEL WITH VARIOUS TRANSFER PROPERTIES AND A DEVICE IMPLEMENTING PROCEDURE |
| EP0453814B1 (en) * | 1990-03-30 | 1997-01-29 | Nec Corporation | Adaptive channel impulse response estimation system using maximum likelihood sequence estimation |
| JP2621685B2 (en) * | 1991-05-29 | 1997-06-18 | 日本電気株式会社 | Adaptive maximum likelihood sequence estimator |
| JPH09294095A (en) * | 1996-04-26 | 1997-11-11 | Oki Electric Ind Co Ltd | Adaptive equalizer |
-
1998
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| GB9804786D0 (en) | 1998-04-29 |
| GB2335123B (en) | 2003-08-13 |
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