Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
  • H04B1/69—Spread spectrum techniques
  • H04B1/707—Spread spectrum techniques using direct sequence modulation
  • H04B1/7097—Interference-related aspects
  • H04B1/711—Interference-related aspects the interference being multi-path interference
  • H04B1/7115—Constructive combining of multi-path signals, i.e. RAKE receivers
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
  • H04B1/69—Spread spectrum techniques
  • H04B1/707—Spread spectrum techniques using direct sequence modulation
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
  • H04B1/69—Spread spectrum techniques
  • H04B1/707—Spread spectrum techniques using direct sequence modulation
  • H04B1/7073—Synchronisation aspects
• • 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
  • H04L25/024—Channel estimation channel estimation algorithms
  • H04L25/025—Channel estimation channel estimation algorithms using least-mean-square [LMS] method
• • 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
  • H04L25/03012—Arrangements for removing intersymbol interference operating in the time domain
• • 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
  • H04L25/03178—Arrangements involving sequence estimation techniques
  • H04L25/03248—Arrangements for operating in conjunction with other apparatus
  • H04L25/0328—Arrangements for operating in conjunction with other apparatus with interference cancellation circuitry
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
  • H04B1/69—Spread spectrum techniques
  • H04B1/707—Spread spectrum techniques using direct sequence modulation
  • H04B1/7097—Interference-related aspects
  • H04B1/711—Interference-related aspects the interference being multi-path interference
  • H04B1/7115—Constructive combining of multi-path signals, i.e. RAKE receivers
  • H04B1/712—Weighting of fingers for combining, e.g. amplitude control or phase rotation using an inner loop
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B2201/00—Indexing scheme relating to details of transmission systems not covered by a single group of H04B3/00 - H04B13/00
  • H04B2201/69—Orthogonal indexing scheme relating to spread spectrum techniques in general
  • H04B2201/707—Orthogonal indexing scheme relating to spread spectrum techniques in general relating to direct sequence modulation
  • H04B2201/7097—Direct sequence modulation interference
  • H04B2201/709727—GRAKE type RAKE receivers
• • 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
  • H04L2025/0335—Arrangements for removing intersymbol interference characterised by the type of transmission
  • H04L2025/03375—Passband transmission
  • H04L2025/03401—PSK

Definitions

• bits information is translated into a digital or binary form, referred to as bits, for communications purposes.
• the transmitter maps this bit stream into a modulated symbol stream, which is detected at the digital receiver and mapped back into bits and information.
• the radio environment presents many difficulties that impede successful communications.
• One difficulty is that the signal level can fade, because the signal may travel in multiple paths. As a result, signal images arrive at the receiver antenna out of phase. This type of fading is commonly referred to as Rayleigh fading or fast fading.
• Rayleigh fading When the signal fades, the signal-to-noise ratio becomes lower, causing a degradation in the commumcation link quality.
• ISI intersymbol interference
• Raleigh fading can be mitigated by using diversity, such as antenna diversity, at the receiver.
• the signal is received on a plurality of antennas. Because the antennas have slightly different locations and/or antenna patterns, the fading levels on the antennas are different.
• these multiple antenna signals are combined either before or after signal detection using such techniques as maximal-ratio-combining, equal-gain-combining, and selective combining. These techniques are well known to those skilled in the art and can be found in standard textbooks, such as W.C.Y. Lee, Mobile Communications Engineering, New York: McGraw-Hill, 1982.
• the time dispersion can be mitigated by using an equalizer.
• equalizers Common forms of equalization are provided by linear equalizers, decision-feedback equalizers, and maximum-likelihood sequence-estimation (MLSE) equalizers.
• a linear equalizer tries to undo the effects of the channel by filtering the received signal.
• a decision- feedback equalizer exploits previous symbol detections to cancel out the intersymbol interference from echoes of these previous symbols.
• an MLSE equalizer hypothesizes various transmitted symbol sequences and, with a model of the dispersive channel, determines which hypothesis best fits the received data.
• MLSE equalization has been considered preferable from a performance point of view.
• all possible transmitted symbol sequences are considered.
• the received signal samples are predicted using a model of the multipath channel.
• the difference between the predicted received signal samples and the actual received signal samples, referred to as the prediction error gives an indication of how good a particular hypothesis is.
• the squared magnitude of the prediction error is used as a metric to evaluate a particular hypothesis. This metric is accumulated for different hypotheses for use in determining which hypotheses are better.
• This process is efficiently realized using the Viterbi algorithm, which is a form of dynamic programming. Ideally, the diversity combining process and the equalization process should be combined in some optimal way.
• the use of antenna arrays at base stations in a mobile communication systems has also been proposed as a technique for increasing capacity and performance.
• the most common approach for processing the information gathered by each antenna associated with a particular signal is based on direction of arrival (DOA) estimation followed by beamfomiing, i.e. combining the vector signal from the array to a scalar signal (spatial filtering), before detection.
• DOA direction of arrival
• beamfomiing i.e. combining the vector signal from the array to a scalar signal (spatial filtering)
• This approach does not fully exploit the spatial structure of the channel.
• a better way is to use an algorithm that is adaptive in the spatial domain and which also takes the quality that the transmitted signal has a finite alphabet (e.g. , 0's and l's) into account. Examples of such algorithms are the recently proposed iterative least squares with projections (ILSP) algorithm and the decoupled weighted least squares with projections (DWILSP)
• ILSP and DWILSP are, in their original formulation, limited to use on frequency-flat (i.e., non time-dispersive) channels.
• frequency-flat i.e., non time-dispersive
• the channel cannot be modelled as frequency-flat.
• extensions to the iterative least squares approaches have also been presented. These algorithms are unfortunately quite complex, both regarding computational aspects and detection procedures involved.
• these and other drawbacks and problems associated with the conventional DWILSP algorithm, and similar techniques for processing received radio signals are overcome by providing self-synchronizing techniques which provide improved performance for nonsynchronous ly sampled signals.
• nonsynchronously sampled signals create additional intersymbol interference (ISI) which should be compensated for in order to improve detection performance.
• ISI intersymbol interference
• This additional ISI is different than that described above in that it is parameterizable (and therefore readily determinable) based upon timing error and modulation type.
• exemplary embodiments of the present invention teach the provision of compensation schemes which, for example, modify the conventional DWILSP technique to compensate for the ISI introduced by nonsynchronous sampling.
• a specific example is given for MSK modulation, although the present invention can be applied to any type of modulation with adaptations which will be apparent to those skilled in the art.
• exemplary embodiments of the present invention also provide for robust diversity combining which outperforms conventional techniques, e.g. , RAKE diversity combining.
• RAKE diversity combining By using the DWILSP technique to provide temporal combining of spatio-temporal signal estimates created using an adapted version of the RAKE algorithm, exemplary embodiments of the present invention are able to significantly improve upon prior diversity combining techniques.
• FIG. 1 is a block diagram of an exemplary cellular radio telephone system in which the present invention may be applied;
• FIG. 2 illustrates an exemplary antenna array and processing structures associated therewith
• FIG. 3 is a flowchart depicting an exemplary self-synchronizing technique according to the present invention
• FIG. 4 is a graph illustrating simulation results in terms of bit error rate for BPSK modulated signals processed according to both the conventional DWILSP technique and self-synchronizing techniques according to the present invention
• FIG. 5 is a graph illustrating simulation results in terms of root mean square delay for BPSK modulated signals processed according to self- synchronizing techniques according to the present invention
• FIG. 6 is a graph illustrating simulation results for MSK modulated signals processed according to both the conventional DWILSP technique and a self-synchronizing technique according to the present invention
• FIG. 7 is a graph illustrating simulation results for GMSK modulated signals processed according to both the conventional DWILSP technique and a self-synchronizing technique according to the present invention
• FIG. 8 is a block diagram of a conventional RAKE combiner
• FIG. 9 is a block diagram of another known RAKE combiner using the DWILSP technique to provide signal estimates
• FIG. 10 is a block diagram of a RAKE combiner according to an exemplary embodiment of the present invention
• FIG. 11 is a block diagram of a RAKE combiner according to an another exemplary embodiment of the present invention.
• FIG. 12 is a flowchart illustrating steps associated with an exemplary diversity combining technique according to the present invention.
• FIG. 13 is a graph illustrating the results of a first simulation used to demonstrate the performance of an exemplary diversity combining technique associated with the present invention.
• FIG. 14 is a graph illustrating the results of a second simulation used to demonstrate the performance of an exemplary diversity combining technique associated with the present invention.
• FIG. 1 is a block diagram of an exemplary cellular radiocommunication system, including an exemplary base station 110 and mobile station 120.
• the base station includes a control and processing unit 130 which is connected to the mobile switching center (MSC) 140 which in turn is connected to the PSTN (not shown).
• MSC mobile switching center
• General aspects of such cellular radiocommunication systems are known in the art, as described by the above-cited U.S. patent applications and by U.S. Patent No. 5,175,867 to Wejke et al., entitled “Neighbor- Assisted Handoff in a Cellular Communication System, " and U.S. Patent Application No. 07/967,027 entitled “Multi-Mode Signal Processing,” which was filed on October 27, 1992, both of which are incorporated in this application by reference.
• the base station 110 handles a plurality of traffic channels through a traffic channel transceiver 150, which is controlled by the control and processing unit 130.
• each base station includes a control channel transceiver 160, which may be capable of handling more than one control channel.
• the control channel transceiver 160 is controlled by the control and processing unit 130.
• the control channel transceiver 160 broadcasts control information over the control channel of the base station or cell to mobiles locked to that control channel. It will be understood that the transceivers 150 and 160 can be implemented as a single device, like the traffic and control transceiver 170 in the mobile station, for use with control channels and traffic channels that share the same radio carrier frequency.
• the traffic channels can be used in a dedicated, connection-oriented manner to transmit information, e.g., for a voice connection, where each channel is used continuously for a period of time to support transmission of a single stream of information or in a packet-oriented manner where each channel can be used to send independent units of information associated with different information streams.
• Transceivers 150 and 160 may have dedicated antennas 170 and 180 which, using a duplex filter, transmit and receive signals for processing therein.
• base station 110 may be provided with an antenna array as depicted in FIG. 2.
• Each signal creates a response on each antenna element 200, which response is processed (e.g., filtered, downconverted, etc) in receive processing blocks 210.
• the processed signal responses are used to generate a channel estimate h_ and a signal estimate s k (t) for each sampling time instance i as shown in blocks 220.
• the manner in which these estimates are created and combined are described below with respect to exemplary embodiments of the present invention.
• the output of an -element array can be expressed as:
• d is the number of signals impinging on the array
• s k is the signal from the &:th user (with symbols belonging to a finite alphabet)
• u and ⁇ a is the attenuation and time-delay for each of the q k subpaths.
• Equation (1) can thus be rewritten as: (
• a block formulation is obtained by taking N snapshots, yielding:
• equation (4) can be rewritten in the following way:
• Equation (6) can thus be reformulated as follows:
• equation (9) is a temporally matched filter to the current signal estimate, whereas (8) represents a spatially matched filter. The process is repeated until s converges, after which the algorithm continues with the next signal.
• the present invention modifies the aforedescribed technique to handle intersymbol interference caused either by non bit-synchronized sampling or by the modulation technique used to process the original signal for transmission over the air interface.
• These modified techniques according to the present invention are referred to herein as "self-synchronized" techniques.
• ISI intersymbol interference
• This form of ISI is quite different from the ISI caused by a time dispersive propagation channel.
• the reason for this is that ISI caused by unsynchronized sampling has an underlying structure, i.e. , the ISI can be parameterized by the timing error.
• the parameterization of this structured kind of ISI differs between modulation formats. Therefore, the modifications made to the DWILSP technique according to exemplary embodiments of the present invention will also depend on the modulation format.
• the effects of ISI due to nonsynchronous sampling are reflected in the data model by a modification of the source signal description as:
• the ISI is parameterized in the scalar signal s ISI i (n), and the characterization of this ISI depends on the modulation format. In some cases, there is no ISI at all, for example MPSK modulation with a rectangular pulse shape, sampled directly at the symbol rate without a preceding matched filter. Nevertheless, in most cases, sampling nonsynchronously leads to ISI, as for example when a signal modulated by minimum shift keying (MSK) is nonsynchronously sampled.
• MSK minimum shift keying
• MSK signal is most often received by direct sampling at the symbol rate, without any matched filter, as in the European GSM system and systems operating in accordance with the GSM standard.
• received signal nonsynchronously sampled, can be expressed as:
• Pre-whitening is achieved by computing the following new quantities.
• the estimated array covariance matrix is defined by (with "H” denoting the Hermitean transpose operator):
• the self-synchronizing technique according to the present invention for detecting/estimating ISI in a single diversity path can now be outlined as follows.
• the flowchart of FIG. 3 provides a visual guide to the below described steps according to the present invention.
• create a corresponding signal r ISI (t) using a known training/reference sequence r(t) (which is contained as a part of the original finite alphabet signal, s(t), transmitted from a mobile station).
• r(t) which is contained as a part of the original finite alphabet signal, s(t)
• s(t) which is contained as a part of the original finite alphabet signal, s(t)
• different systems provide different known reference sequences in their transmission bursts.
• the GSM system provides a training sequence having 26 bits.
• this construction will depend on the actual length of the particular training sequence considered.
• Use this construction, together with the well-known Least-Squares (LS) method for parameter estimation, to find an initial estimate, g, of the channel response vector at block 310 using the below data model (with t t 1 ...t 2 ):
• the process continues iteratively begiirning with an estimation of the sampled ISI signal, s IS[ (t), employing the LS-method using the received pre-whitened data, z(t), and the estimated channel response vector, g, as indicated at block 320.
• the model for the estimated received data can be rewritten as:
• s(t) is the originally transmitted finite alphabet signal by a mobile station.
• the variables a x , 2 and s(t) can then be solved for using the conventional DWILSP technique.
• the relative sampling instance, r can be estimated from and as.
• an updated channel response vector, g can be computed, block 330, using the LS-method on the data model:
• a simulation was conducted that compares the present invention with the conventional DWILSP algorithm for signals using BPSK or Gaussian MSK modulation.
• the test simulated a 5-element antenna array that receives two signals from nominal DOA:s of [-15°, 20°] .
• the signals are transmitted in bursts corresponding to the normal GSM burst, i.e., 148 bits, including a 26 bit training sequence in the central part, and three known tail bits at each end.
• the channel was modelled as flat-fading and the scattering cluster width ⁇ was 3°. To simulate Rayleigh fading, independent channel vectors were used for each transmitted burst.
• the average E b /N 0 at each antenna-element was set to 5dB.
• the performance of the original DWILSP algorithm was compared to the self synchronizing technique according to the present invention.
• the self-synchronizing technique was tested twice, once using the LS-approach, and a second time using Viterbi equalization to facilitate a performance comparison.
• the timing error introduced by nonsynchronous sampling was varied, giving the results shown in FIG. 4. In this figure, bit error rate is plotted against timing error. Throughout these simulations the following conventions are used.
• the dashed line represents the results for the conventional DWILSP technique
• the results for the self- synchronizing technique (LS-approach) is shown as a dotted line
• the results for the self-synchronizing technique (Viterbi approach) is shown using a solid line.
• FIG. 4 it can be seen that either implementation of the present invention provides improved performance as compared with the conventional DWILSP technique due to its assumption of synchronized bit sampling.
• Using the Viterbi algorithm also leads to a performance degradation for ⁇ 0 and ⁇ l, but this is a consequence of the signal power loss involved, and not the Viterbi algorithm itself.
• the timing error r is of more importance than the BER.
• FIG. 5 shows the root mean square (RMS) error of the delay estimate for the LS and Viterbi implementations of the present invention.
• RMS root mean square
• exemplary techniques according to the present invention provides improved performance across the spectrum of timing errors and, accordingly, permit the signal of interest to be sampled nonsynchronously. For some modulation formats, some performance degradation is introduced, whereas for others, there is no performance degradation involved.
• the self-synchronizing techniques according to the present invention also provide an estimate of the timing error, either explicitly, or as a function value thereof. For example, Equation (13) can be rewritten to provide an estimate of the timing error r as the following function value:
• T s is here a known quantity
• ⁇ x has been estimated by the conventional DWILSP algorithm.
• the self-synchronizing version of the DWILSP algorithm can be used for other applications than communications, for example radar and positioning.
• Cancelling the effect of the channel dispersion is, as described above, a classical problem known as equalization.
• Conventional techniques include different filtering approaches, such as the linear equalizer (a filter approximating the inverse of the channel) and the decision feedback equalizer (DFE). These can be extended to the array signal case.
• Another often employed algorithm is the maximum likelihood sequence estimator (MLSE). The latter is often regarded as being optimal, as it is derived from the maximum likelihood principle.
• the conventional DWILSP algorithm acts as a spatial diversity combiner, collecting the spatially spread energy in an efficient way.
• Such algorithms have been proposed but are unfortunately quite complex, both with regard to computational aspects and detection procedures involved.
• these conventional approaches require an oversampling of the received signal.
• a space-time algorithm according to the present invention can be derived with the DWILSP algorithm as its elementary building block.
• the time dispersive case can be reformulated according to the frequency flat data model.
• the DWILSP algorithm can then be adopted to estimate different time-arrivals separately. This step thus performs spatial combing. Then, the different time-arrival estimates are combined temporally.
• This technique according to the present invention thus constitutes a RAKE-combiner, exploiting both the spatial and temporal structure of the measured array signal, as well as the finite alphabet property of the modulated source signal.
• this novel technique provides high performance at a low computational complexity, while at the same time lending itself to a simple and straightforward implementation.
• the approach taken here is based on estimation of different time arrivals of the desired user signal separately, instead of trying to invert or equalize the filter representing the channel.
• a final estimate is achieved by a combination of the estimates of the different time arrivals.
• the RAKE combiner was originally proposed for direct sequence spread spectrum (DSSS) systems operating on time-dispersive channels.
• DSSS direct sequence spread spectrum
• s is a DSSS signal.
• DSSS signals are wideband signals.
• the wideband property is achieved by spreading the original data sequence with a high rate spreading code, whose elements are called chips, each with a duration of T c seconds.
• chips whose elements are called chips
• Each original data symbol thus contains several chips, and the spreading code is designed to have an autocorrelation function resembling white noise, such that symbols shifted more than one chip length apart are approximately uncorrelated.
• This type of signal is commonly used, for example, in radiocommunication systems that operate in accordance with code division multiple access (CDMA) techniques.
• CDMA code division multiple access
• the DSSS RAKE combiner estimates each time-arrival s(n-kT c ) by exploiting the autocorrelation property of the spreading sequence.
• the L+l signal estimates are then temporally combined to yield a finite signal estimate.
• the total scheme is thus equivalent to an L+l order diversity combiner (if the channel taps h k are uncorrelated).
• the conventional RAKE combiner can be illustrated as in FIG. 8, where each block 800 provides a time delay T c and the multiplication by c(n) at each multiplier 810 represents the despreading operation.
• the temporal branches seen in FIG. 8 are often referred to as
• RAKE fingers but are referred to herein as "spatio-temporal signal estimates” when used to refer to branches of a modified RAKE combiner wherein the DWILSP algorithm is used to provide for spatial combination.
• the outputs of each RAKE finger are then temporally combined at block 820 by a diversity combining technique as will be described below.
• the RAKE approach can also be applied to the array (unspread) signal case.
• spread symbols as in the DSSS data model of equation (22), consider blocks of symbols. If the user signal is sufficiently temporally white, shifted versions, by an amount of T s seconds or more, become approximately uncorrelated. A block of symbols thus acts as the spreading sequence in the DSSS case, and different time-arrivals can be viewed as different user signals in the frequency flat case. Then the DWILSP type algorithm can be used to estimate the different time arrivals separately.
• the RAKE approach can be generalized to the multi-user case. Considering the different time arrivals as different signals, the double sum in the multi-user model can be rewritten according to equation (22), corresponding to the frequency flat case with d(L + l) users:
• the RAKE combiner for the array signal case is shown in FIG. 9, where delayed versions of the received symbols are provided by blocks 900.
• the despreading operation in FIG. 8 is replaced by the conventional DWILSP algorithm in blocks 910 which provide spatio-temporal signal estimates to the temporal combining block 920.
• the self-synchronizing techniques described in the above exemplary embodiments can be applied to provide the spatio-temporal signal estimates as shown in FIG. 10.
• the delay blocks 1000, spatio-temporal signal estimators 1010 and temporal combining logic 1020 operate as described above.
• MRC maximum ratio combining
• SNR signal-to-noise ratio
• the conventional MRC approach can be modified with the conventional DWILSP algorithm.
• _ . represents a small bias (usually negligible)
• ⁇ tlc (n) is a noise term due to scaled thermal noise v(n) plus cochannel and self interferences s ⁇ n), ⁇ ) OR (l ⁇ k).
• This noise term can, with good accuracy, be considered as temporally white Gaussian and the noise in different signal estimates are approximately uncorrelated, i.e. E ⁇ B ⁇ O, for (j ⁇ OR (l ⁇ k).
• each signal estimate of s ; (n) is automatically normalized in amplitude (PSK:
• 1) by DWILSP.
• 1 by DWILSP.
• Equation (27) the operator (Proj) means projection onto the finite alphabet and cr 2 ⁇ is the variance of ⁇ lk (n), which can be estimated as Var(Proj(s ⁇ c )- ⁇ ;*).
• DWILSP projects symbols onto the alphabet of +/-1 and only the variance of the real part of the noise should be considered.
• FIG. 11 shows the DWILSP technique
• the column vector w can be interpreted as a temporal channel vector, representing the delay profile of the channel.
• the column vector w also has a direct correspondence to the combining
• equation (29) using DWILSP is essentially a search for the best diversity combining weights. Note that with the DWILSP algorithm employed for temporal combining, as well as to provide the spatio-temporal signal estimates, the finite alphabet property is used twice.
• DWILSP is very robust in cases where not all diversity channels contain the signal of interest.
• the known training sequence e.g. , the CDVCC in D-AMPS
• the self- synchronizing technique described above can be used to obtain a signal estimate S f r of time path k at block 1210.
• the signal estimates can be temporally combined at block 1220, by either (1) estimating the variance of ⁇ - x) and using modified MRC according to equation (28) or using the conventional DWILSP to perform temporal combining.
• the performance of RAKE receivers according to the present invention was evaluated numerically at two different settings of a 5-tap FIR channel.
• the local scatter model was used to model each filter tap.
• the filter taps were modelled as statistically independent, therefore and the standard version of the DWILSP algorithm was used to provide the spatio-temporal signal estimates.
• the receiving antenna was chosen to be a 10-element uniform linear array (ULA).
• UUA uniform linear array
• Three equally powered cochannel users were placed at nominal DOA:s [30°, 0°, -45°], relative to the array broadside.
• BPSK data was transmitted in bursts of 150 bits. Each burst included a 15-bit resequence, periodically extended to 19 bits, which was used as a training sequence for initialization of the receiver algorithm.
• the performance of the conventional MLSE technique was also evaluated.
• the MLSE was run twice: once with the exact channel and interference covariance matrix as a benchmark, and also using maximum likelihood estimates of these parameters obtained from the training sequence to provide a more realistic evaluation of MLSE performance.
• the MLSE was implemented with the Viterbi algorithm.
• the relative average power in each tap was the same. Assuming a larger angular spread for the late arrivals (but the same nominal DO A), the cluster width standard deviations for the different taps were [2°, 3°, 4°, 5°, 6°].
• the total signal power is here defined as the sum of die powers in each filter tap.
• the first curve shows the performance of the MLSE run with estimated channel parameters and interference co variance, and it is seen that this method has a performance that is limited by me cochannel interference. This characteristic is not seen in the other curves.
• the second curve shows the performance of the RAKE-combiner using standard MRC temporal combining.
• performance has been improved by about 2dB using modified MRC. Another 2dB is gained by employing DWILSP combining.
• the last curve shows the performance of the MLSE run with the exact parameters. Considering the fact that the MLSE is run with estimated parameters in a practical application, e.g.
• the channel setting was adjusted to simulate a hilly terrain environment.
• the mean filter tap powers were set as [0, 0, -20, -20, -6] dB and the cluster width standard deviations were [2°, 3°, 6°, 2°].
• Each tap corresponded to a direction of [0°, 1°, 0° , 0°, 10°] relative to the nominal DOA's, i.e., the late arrival impinging from a somewhat different direction compared to the early ones.
• the relative performance of the different algorithms resemble the results from FIG. 13.

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• 1997
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  • 1998-03-20 DE DE69835349T patent/DE69835349T2/de not_active Expired - Lifetime
  • 1998-03-20 CA CA002285431A patent/CA2285431C/en not_active Expired - Fee Related
  • 1998-03-20 EP EP98912849A patent/EP0970569B1/en not_active Expired - Lifetime
  • 1998-03-20 TW TW087104156A patent/TW386325B/zh not_active IP Right Cessation
  • 1998-03-20 JP JP54153798A patent/JP4409634B2/ja not_active Expired - Lifetime
• 1999
  • 1999-06-16 US US09/333,978 patent/US6148023A/en not_active Expired - Lifetime

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