US20100046660A1 - Interference cancellation under non-stationary conditions - Google Patents

Interference cancellation under non-stationary conditions Download PDF

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Publication number
US20100046660A1
US20100046660A1 US12/464,311 US46431109A US2010046660A1 US 20100046660 A1 US20100046660 A1 US 20100046660A1 US 46431109 A US46431109 A US 46431109A US 2010046660 A1 US2010046660 A1 US 2010046660A1
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Prior art keywords
symbols
burst
subset
midamble
timing
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English (en)
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Divaydeep Sikri
Farrokh Abrishamkar
Ming Yan
Nico De Laurentiis
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Qualcomm Inc
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Qualcomm Inc
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Priority to US12/464,311 priority Critical patent/US20100046660A1/en
Priority to KR1020127014772A priority patent/KR20120082942A/ko
Priority to EP12150520A priority patent/EP2472734A1/en
Priority to TW098115882A priority patent/TWI393396B/zh
Priority to CA2723730A priority patent/CA2723730A1/en
Priority to EP09747422A priority patent/EP2294716A2/en
Priority to KR1020107027900A priority patent/KR101247479B1/ko
Priority to TW101144327A priority patent/TW201320664A/zh
Priority to RU2010150761/08A priority patent/RU2481742C2/ru
Priority to JP2011509633A priority patent/JP2011524115A/ja
Priority to PCT/US2009/043718 priority patent/WO2009140338A2/en
Priority to CN2009801170948A priority patent/CN102027692A/zh
Assigned to QUALCOMM INCORPORATED reassignment QUALCOMM INCORPORATED ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: YAN, MING, ABRISHAMKAR, FARROKH, DE LAURENTIIS, NICO, SIKRI, DIVAYDEEP
Publication of US20100046660A1 publication Critical patent/US20100046660A1/en
Priority to US13/215,984 priority patent/US8675796B2/en
Priority to JP2012238170A priority patent/JP2013070384A/ja
Abandoned legal-status Critical Current

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W56/00—Synchronisation arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/01—Reducing phase shift
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas

Definitions

  • the present invention generally relates to wireless communication and, in particular, relates to interference cancellation under non-stationary conditions.
  • a receiver's ability to properly decode a received signal depends upon the receiver's ability to accurately estimate symbol timing and frequency.
  • increasing amounts of interference can negatively impact a receiver's ability to do so.
  • optimal timing and frequency are jointly obtained in a wireless communication system by parametrizing the subspace into possible timing and frequency hypotheses and searching through them.
  • Joint Max Likelihood of frequency and timing may be performed sequentially or in parallel.
  • an interference suppression filter is tuned to various parameters, and then optimal pairs (of time and frequency) are picked by minimizing the prediction error using a known sequence (midamble or quasi-midamble, e.g., data aided).
  • the algorithm boosts the received signal quality under strong interference whereas non-coherent estimation would degrade significantly.
  • a method for timing and frequency synchronization in a wireless system comprises the steps of receiving a burst of symbols, selecting a subset of the burst of symbols, iteratively adjusting the subset of the burst of symbols by a plurality of timing offsets and calculating, for each timing offset, a first performance metric corresponding to the adjusted subset.
  • the method further comprises the steps of determining one of the plurality of timing offsets to be a preferred timing offset based upon the first performance metric thereof, iteratively rotating the subset of the burst of symbols by a plurality of frequency offsets and calculating, for each frequency offset, a second performance metric corresponding to the rotated subset, and determining one of the plurality of frequency offsets to be a preferred frequency offset based upon the second performance metric thereof.
  • a method for timing and frequency synchronization in a wireless system comprises the steps of receiving a burst of symbols, selecting a subset of the burst of symbols, iteratively adjusting the subset of the burst of symbols by a plurality of timing offsets and a plurality of frequency offsets, calculating, for each combination of timing and frequency offsets, a performance metric corresponding to the adjusted subset, and determining one of the combination of timing and frequency offsets to be a preferred combination based upon the performance metric thereof.
  • a wireless apparatus comprises a receiver configured to receive a burst of symbols, and a processor.
  • the processor is configured to select a subset of the burst of symbols, iteratively adjust the subset of the burst of symbols by a plurality of timing offsets and calculate, for each timing offset, a first performance metric corresponding to the adjusted subset.
  • the processor is further configured to determine one of the plurality of timing offsets to be a preferred timing offset based upon the first performance metric thereof, iteratively rotate the subset of the burst of symbols by a plurality of frequency offsets and calculate, for each frequency offset, a second performance metric corresponding to the rotated subset, and determine one of the plurality of frequency offsets to be a preferred frequency offset based upon the second performance metric thereof.
  • a wireless apparatus comprises a receiver configured to receive a burst of symbols, and a processor.
  • the processor is configured to receive a burst of symbols, select a subset of the burst of symbols, iteratively adjust the subset of the burst of symbols by a plurality of timing offsets and a plurality of frequency offsets, calculate, for each combination of timing and frequency offsets, a performance metric corresponding to the adjusted subset, and determine one of the combination of timing and frequency offsets to be a preferred combination based upon the performance metric thereof.
  • a wireless apparatus comprises means for receiving a burst of symbols, means for selecting a subset of the burst of symbols, means for iteratively adjusting the subset of the burst of symbols by a plurality of timing offsets and for calculating, for each timing offset, a first performance metric corresponding to the adjusted subset, means for determining one of the plurality of timing offsets to be a preferred timing offset based upon the first performance metric thereof, means for iteratively rotating the subset of the burst of symbols by a plurality of frequency offsets and calculating, for each frequency offset, a second performance metric corresponding to the rotated subset, and means for determining one of the plurality of frequency offsets to be a preferred frequency offset based upon the second performance metric thereof.
  • a wireless apparatus comprises means for receiving a burst of symbols, means for selecting a subset of the burst of symbols, means for iteratively adjusting the subset of the burst of symbols by a plurality of timing offsets and a plurality of frequency offsets, means for calculating, for each combination of timing and frequency offsets, a performance metric corresponding to the adjusted subset, and means for determining one of the combination of timing and frequency offsets to be a preferred combination based upon the performance metric thereof.
  • a computer-program product for use in a wireless communication system comprises a computer readable medium having a set of instructions stored thereon, the set of instructions being executable by one or more processors and the set of instructions comprising instructions for receiving a burst of symbols, instructions for selecting a subset of the burst of symbols, instructions for iteratively adjusting the subset of the burst of symbols by a plurality of timing offsets and for calculating, for each timing offset, a first performance metric corresponding to the adjusted subset, instructions for determining one of the plurality of timing offsets to be a preferred timing offset based upon the first performance metric thereof, instructions for iteratively rotating the subset of the burst of symbols by a plurality of frequency offsets and for calculating, for each frequency offset, a second performance metric corresponding to the rotated subset, and instructions for determining one of the plurality of frequency offsets to be a preferred frequency offset based upon the second performance metric thereof.
  • a computer-program product for use in a wireless communication system comprises a computer readable medium having a set of instructions stored thereon, the set of instructions being executable by one or more processors and the set of instructions comprising instructions for receiving a burst of symbols, instructions for selecting a subset of the burst of symbols, instructions for iteratively adjusting the subset of the burst of symbols by a plurality of timing offsets and a plurality of frequency offsets, instructions for calculating, for each combination of timing and frequency offsets, a performance metric corresponding to the adjusted subset, and instructions for determining one of the combination of timing and frequency offsets to be a preferred combination based upon the performance metric thereof.
  • FIG. 1 illustrates exemplary frame and burst formats in GSM in accordance with one aspect of the subject technology
  • FIG. 2 is a flow chart illustrating a method for suppressing interference in accordance with one aspect of the subject technology
  • FIG. 3 is a flow chart illustrating a method for suppressing interference in accordance with one aspect of the subject technology
  • FIG. 4 illustrates a receiver for use in a wireless communication system in accordance with one aspect of the subject technology
  • FIG. 5 illustrates a subset of symbols, including the first midamble symbol, that a receiver selects in accordance with one aspect of the subject technology
  • FIG. 6 illustrates a method for suppressing interference in accordance with one aspect of the subject technology
  • FIG. 7 illustrates a receiver for use in a wireless communication system in accordance with one aspect of the subject technology
  • FIG. 8 illustrates a method for suppressing interference in accordance with one aspect of the subject technology
  • FIG. 9 illustrates a receiver for use in a wireless communication system in accordance with one aspect of the subject technology
  • FIG. 10 illustrates a receiver for use in a wireless communication system in accordance with one aspect of the subject technology.
  • FIG. 11 is a block diagram illustrating a computer system with which certain aspects of the subject technology may be implemented.
  • FIG. 1 shows exemplary frame and burst formats in GSM.
  • the timeline for downlink transmission is divided into multiframes.
  • each multiframe such as exemplary multiframe 101
  • each multiframe includes 26 TDMA frames, which are labeled as TDMA frames 0 through 25 .
  • the traffic channels are sent in TDMA frames 0 through 11 and TDMA frames 13 through 24 of each multiframe, as identified by the letter “T” in FIG. 1 .
  • a control channel, identified by the letter “C,” is sent in TDMA frame 12 .
  • No data is sent in the idle TDMA frame 25 (identified by the letter “I”), which is used by the wireless devices to make measurements for neighbor base stations.
  • Each TDMA frame such as exemplary TDMA frame 102 , is further partitioned into eight time slots, which are labeled as time slots 0 through 7 .
  • Each active wireless device/user is assigned one time slot index for the duration of a call.
  • User-specific data for each wireless device is sent in the time slot assigned to that wireless device and in TDMA frames used for the traffic channels.
  • Each burst such as exemplary burst 103 , includes two tail fields, two data fields, a training sequence (or midamble) field, and a guard period (GP). The number of bits in each field is shown inside the parentheses.
  • GSM defines eight different training sequences that may be sent in the training sequence field.
  • Each training sequence, such as midamble 104 contains 26 bits and is defined such that the first five bits are repeated and the second five bits are also repeated.
  • Each training sequence is also defined such that the correlation of that sequence with a 16-bit truncated version of that sequence is equal to (a) sixteen for a time shift of zero, (b) zero for time shifts of ⁇ 1, ⁇ 2, ⁇ 3, ⁇ 4, and ⁇ 5, and (3) a zero or non-zero value for all other time shifts.
  • One approach to locating a midamble in a burst of symbols serially compares hypotheses regarding the midamble position to determine which hypothesis provides the highest correlation energy between the known midamble sequence and the hypothesized position in the burst of symbols. This method is very sensitive to interference from multi-paths of the same midamble sequence, which can cause the correlation energy of inaccurate hypotheses to be affected by time-delayed copies thereof.
  • Non-Coherent Frequency and Timing estimation suffers from performance degradation under presence of strong interference. According to one aspect of the subject technology, by semi-coherently estimating the optimal timing and frequency, performance in the presence of interference can be greatly improved.
  • optimal timing and frequency are jointly obtained by parametrizing the subspace into possible hypotheses and searching through them.
  • Joint Max Likelihood of frequency and timing may be further simplified to a sequential search to provide optimal performance.
  • an interference suppression filter is tuned to various parameters, and then optimal pairs (of time and frequency) are picked by minimizing the prediction error using a known sequence (midamble or quasi-midamble, e.g., data aided).
  • the algorithm boosts the received signal quality under strong interference whereas non-coherent estimation would degrade significantly.
  • x _ k [ x k ⁇ ( 1 ) x k ⁇ ( 2 ) ⁇ x k ⁇ ( M ) ]
  • s _ k [ s k s k - 1 ⁇ s k - ⁇ ]
  • s k is the midamble/quasi-midamble signal at time k
  • s k is a ( ⁇ +1) ⁇ 1 midamble/quasi-midamble vector
  • x k is a M ⁇ 1 received midamble/quasi-midamble vector
  • X k [ x _ k x _ k - 1 ⁇ x _ k - L ] ,
  • X k is a M ⁇ (L+1) ⁇ 1 vector of spatial temporal samples with a spatial length of M and a temporal length of L+1. Accordingly, a spatial/temporal structured matrix can be constructed, such that
  • [ X] [X k X k+1 . . . X k+p ⁇ ],
  • [X] is a M (L+1) ⁇ p ⁇ matrix
  • p is the length of the midamble or quasi-midamble (data aided).
  • a suppression filter W SAIC can be computed according to one aspect of the subject disclosure by estimating a reference sequence of symbols at the channel input:
  • W SAIC arg min ⁇ W[X] ⁇ tilde over (Z) ⁇ 2
  • W SAIC ⁇ tilde over (Z) ⁇ [X] ⁇ ,( ⁇ +1) ⁇ M(L+1)
  • W SAIC ⁇ tilde over (s) ⁇ k [X] T ⁇ [X][X] T ⁇ ⁇ 1 .
  • the interference suppression filter can be serially tuned to each of a plurality of timing hypotheses, and the hypothesis corresponding to the lowest prediction error (using any known sequence, such as the midamble or a data aided quasi-midamble) is selected. Then the filter is serially tuned to each of a plurality of frequency hypotheses to determine which frequency hypothesis corresponds to a lowest prediction error.
  • This serial approach is illustrated in accordance with one aspect of the subject disclosure in FIG. 2 .
  • the method begins by initializing a number of variables in block 201 , including k (the frequency hypothesis number), ⁇ (the timing hypothesis number), ⁇ min (the lowest measured error), ⁇ (n) (the optimal timing hypothesis number) and f(n) (the optimal frequency hypothesis number).
  • the method proceeds to the timing loop 202 (as k is initialized to a zero value).
  • k is initialized to a zero value.
  • Filter weights for a filter W ⁇ are calculated based upon the timing hypothesis, as set forth in greater detail above, and the filter is applied to the symbols to estimate a midamble ⁇ ⁇ .
  • the error ⁇ ( ⁇ ) in the estimated midamble is determined based upon the previously known values for the midamble S.
  • the error is smoothed, and is compared to ⁇ min , the lowest calculated error thus far.
  • ⁇ min is initially set to ⁇
  • the first iteration will necessarily involve redefining ⁇ min to the first calculated error value.
  • ⁇ (n) the optimal timing hypothesis yet calculated, will be set to ⁇ . Then, as long as ⁇ is less than ⁇ max (the total number of hypotheses in the parameterized space), the hypothesis ⁇ is indexed by one, and timing loop 202 repeats.
  • timing loop 202 has iteratively calculated errors for each timing hypothesis ⁇ , an optimal hypothesis ⁇ (n) will have been selected, and the method proceeds to frequency loop 203 .
  • frequency loop 203 iteratively calculates midamble estimation errors for each frequency hypothesis (at the optimal timing delay), and determines the optimal frequency hypothesis.
  • an optimal timing/frequency pair are serially determined from the parameterized timing/frequency subspace, and are used in the processing of the symbols to minimize errors arising from interference.
  • one drawback of using this algorithm for frequency synchronization is that the training sequence may be too short to reliably estimate small frequency offsets (e.g., on the order of few hundred Hz), as the curvature over midamble is essentially flat.
  • the need for an error smoothening filter which makes the implementation more complicated in the field where the frequency offset between interferer and the desired signal can change from burst to burst.
  • the signal to noise ratio may be used over the entire burst instead of the midamble estimation error, in accordance with one aspect of the subject disclosure.
  • the burst is equalized (post MLSE) and the signal to noise ratio is determined using the hard decisions.
  • This approach is illustrated in accordance with one aspect of the subject disclosure in FIG. 3 .
  • the timing loop includes an estimation of the signal to noise ratio (E b /N 0 ), which estimation is used to
  • the method illustrated in FIG. 3 includes a timing loop 301 and a frequency loop 302 .
  • a set of spatial temporal samples are selected corresponding to timing hypothesis number ⁇ .
  • Filter weights for a filter W ⁇ are calculated based upon the timing hypothesis, as set forth in greater detail above, and the filter is applied to the symbols to estimate a midamble ⁇ ⁇ .
  • the error ⁇ ⁇ in the estimated midamble is determined based upon the previously known values for the midamble S.
  • the error is smoothed, and is compared to ⁇ min , the lowest calculated error thus far.
  • ⁇ min is initially set to ⁇
  • the first iteration will necessarily involve redefining ⁇ min to the first calculated error value.
  • ⁇ t ML (n) the optimal timing hypothesis yet calculated, will be set to ⁇ .
  • N the total number of hypotheses in the parameterized space
  • the hypothesis ⁇ is indexed by one, and timing loop 301 repeats.
  • an optimal hypothesis ⁇ t ML (n) will have been selected, and the method proceeds to frequency loop 302 .
  • Frequency loop 302 iteratively calculates a signal to noise ratio for each frequency hypothesis (at the optimal timing delay), and determines the optimal frequency hypothesis. In this manner, an optimal timing/frequency pair are serially determined from the parameterized timing/frequency subspace, and are used in the processing of the symbols to minimize errors arising from interference.
  • the signal to noise ratio E b /N 0 determined in frequency loop 302 is based upon hard decisions.
  • the SNR may be equal to ⁇ H ⁇ F / ⁇ WX ⁇ 2 , where ⁇ is a Toeplitz matrix of estimated symbols after the equalization of the entire burst, which also includes the known training sequence S.
  • FIG. 4 illustrates a receiver for use in a wireless communication system in accordance with one aspect of the subject technology.
  • Receiver 400 includes an antenna 410 configured to receive a wireless signal. While receiver 400 may be used in various communication systems, for clarity, receiver 400 is specifically described herein with respect to a GSM system.
  • the received signal is provided to a pre-processor 420 which demodulates the signal to generate received samples.
  • Pre-processor 420 may include a GMSK-to-BPSK rotator that performs phase rotation on the received samples.
  • Timing estimator 430 receives the samples from pre-processor 420 and generates a plurality of timing hypotheses regarding where a training sequence of symbols (i.e., midamble) begins in the burst of data.
  • Interference suppressor 440 iteratively performs single antenna interference cancellation on the symbols for each timing hypothesis, calculating different filter weights for each timing hypothesis, and midamble estimator 450 generates a midamble estimation error for each hypothesis, as described in greater detail above.
  • Timing decision circuit 460 compares the midamble estimation errors for each hypothesis and selects the hypothesis with the lowest midamble estimation error. The selection of a hypothesis by timing decision circuit 460 represents the position in the burst of symbols where the midamble is estimated to begin.
  • Frequency estimator 470 receives the samples from timing decision circuit 460 and generates a plurality of frequency hypotheses regarding a frequency on which symbols are transmitted.
  • Interference suppressor 440 iteratively performs single antenna interference cancellation on the symbols for each frequency hypothesis, calculating different filter weights for each frequency hypothesis, and midamble estimator 450 generates a midamble estimation error for each hypothesis, as described in greater detail above.
  • Frequency decision circuit 480 compares the midamble estimation errors for each hypothesis and selects the hypothesis with the lowest midamble estimation error. The selection of a hypothesis by frequency decision circuit 480 represents the optimal frequency at which to receive the burst of symbols.
  • the signal is then provided to data processor 490 , which processes the received symbols based upon the selected timing and frequency hypotheses, and outputs the data corresponding to the received symbols.
  • timing estimator may generate a plurality of timing hypotheses by opening a “window” around the estimated beginning of the midamble sequence.
  • the position of the first symbol of the midamble sequence can be estimated for a given burst, based upon the known structure of each burst. For example, as illustrated in FIG. 1 , the beginning of midamble 104 in burst 103 begins in the 62nd bit of the burst.
  • timing estimator 430 selects a window 105 of bits representing a series of hypotheses regarding where the first midamble symbol may be located. Exemplary window 105 is illustrated in greater detail in FIG. 5 .
  • Each ⁇ value represents the position of the symbol in the window.
  • Each of these channel estimates is then processed by interference suppressor 440 and midamble estimator 450 to determine estimated midamble symbols corresponding thereto, in order to determine a midamble estimation error therefor.
  • window 105 has been illustrated as consisting of exactly 11 symbols, the scope of the present invention is not limited to such an arrangement. Rather, as will be readily apparent to one of skill in the art, any window size (up to the size of the entire data burst) may be selected.
  • the size of the search window may be chosen to be twice the size of the expected minimum propagation delay.
  • the search window size may be parameterized based on any other metric known to those of skill in the art.
  • a channel estimate ⁇ may be generated by timing estimator 430 by correlating the received samples (corresponding to the hypothesized delay) with the reference samples (i.e., the known midamble sequence) for each hypothesis. Based on the correlation R ys ( ⁇ ) between received signal y and midamble sequence s for a hypothesized delay ⁇ , the channel estimate may be calculated as follows:
  • interference suppressor 440 performs SAIC on each estimated channel.
  • SAIC is a method by which oversampled and/or real/imaginary decomposition of a signal is used to provide virtual antennas with separate sample sequences, such that weights may be applied to the virtual antennas to form a beam in the direction of a desired transmitter and a beam null in the direction of an undesired interference source.
  • SAIC may be achieved with one or multiple actual antennas at the receiver by using space-time processing, where “space” may be virtually achieved with inphase and quadrature components, and “time” may be achieved using late and early samples.
  • x _ k [ x k ⁇ ( 1 ) x k ⁇ ( 2 ) ⁇ x k ⁇ ( M ) ]
  • s _ k [ s k s k - 1 ⁇ s k - ⁇ ]
  • s k is the midamble/quasi-midamble signal at time k
  • s k is a ( ⁇ +1) ⁇ 1 midamble/quasi-midamble vector
  • x k is a M ⁇ 1 received midamble/quasi-midamble vector
  • X k [ x _ k x _ k - 1 ⁇ x _ k - L ] ,
  • X k is a M ⁇ (L+1) ⁇ 1 vector of spatial temporal samples with a spatial length of M and a temporal length of L+1. Accordingly, a spatial/temporal structured matrix can be constructed, such that
  • [ X] [X k X k+1 . . . X k+p ⁇ ],
  • [X] is a M(L+1) ⁇ p ⁇ matrix
  • p is the length of the midamble or quasi-midamble (data aided).
  • a suppression filter W SAIC can be computed according to one aspect of the subject disclosure by estimating a reference sequence of symbols at the channel input:
  • W SAIC arg min ⁇ W[X] ⁇ tilde over (Z) ⁇ 2 (4)
  • W SAIC ⁇ tilde over (Z) ⁇ [X] ⁇ ,( ⁇ +1) ⁇ M(L+1) (5)
  • W SAIC ⁇ tilde over (s) ⁇ k [X] T ⁇ [X][X] T ⁇ ⁇ 1 (6)
  • the output of interference suppressor 440 is in the form ⁇ , where ⁇ represents an estimate of the midamble sequence.
  • ⁇ represents an estimate of the midamble sequence.
  • Each time t i is equal to the hypothesized position ⁇ i plus an offset T s from the beginning of the burst:
  • timing decision block 460 determines which hypothesis corresponds to the lowest estimation error e m , and the other hypothesized timing values are discarded.
  • the foregoing method for interference suppression enjoys a number of benefits when compared to a method utilizing channel output beamforming.
  • the interference suppression filter weights are calculated by minimizing the cost function
  • the suppression filter weights (of Equation 6) have the dimensionality of ⁇ M (L+1), and the filtered output has the dimensionality of ⁇ (p ⁇ ). Accordingly, the size of the filter weights grows linearly with the number of antennas (whether real or virtual), and the size of the filtered output sample matrix remains constant even as the number of antennas (or virtual antennas) grows. This offers dramatic improvements in computational simplicity and storage requirements over a channel output setup, in which the interference suppression filter weights are calculated by minimizing the cost function
  • Such a channel output setup further involves greater storage and backend ISI equalization using non-linear equalizers (such as an MLSE, where the number of input streams must be set equal to M).
  • non-linear equalizers such as an MLSE, where the number of input streams must be set equal to M.
  • the number of input streams for the backend ISI equalization is only ⁇ , and the number of back-substitutions in the computation of the filter weights is reduced (not being proportional to the number of antennas, as in the channel output setup).
  • the performance of the system is at least as good as, if not better than, the channel output setup.
  • the channel input setup provides good robustness against channel estimation error, which tends to dominate the performance of a GERAN receiver when interference is present.
  • data processor 490 comprises a soft output generator that receives the signal from frequency decision block 480 and generates soft decisions that indicate the confidence in the detected bits.
  • a soft output generator may implement an Ono algorithm, as is well known to those of skill in the art.
  • Data processor 490 may further comprise a de-interleaver that de-interleaves the soft decisions, and passes the soft decisions to a Viterbi decoder that decodes the deinterleaved soft decisions and outputs decoded data.
  • FIG. 6 illustrates a method for suppressing interference in accordance with one aspect of the subject technology.
  • the method begins in step 601 , in which a burst of symbols are received.
  • step 602 a subset of the burst of symbols is selected.
  • the subset of the burst of symbols includes a first midamble symbol.
  • step 603 the subset selected in step 602 is iteratively adjusted by a plurality of timing offsets.
  • a plurality of weights for an interference filter are calculated for each timing offset, based upon the burst of symbols.
  • step 605 the burst of symbols are filtered, for each timing offset, using the interference suppression filter with the corresponding plurality of weights to determine an estimated midamble sequence.
  • step 606 the estimated midamble sequence for each timing offset is compared to a previously known midamble sequence to determine a midamble estimation error for that timing offset.
  • One of the plurality of timing offsets is determined, in step 607 , to be a preferred timing offset, based upon the midamble estimation error thereof.
  • the preferred midamble timing offset is the timing offset corresponding to the lowest midamble estimation error.
  • step 608 the subset of the burst of symbols are iteratively rotated by a plurality of frequency offsets.
  • a plurality of weights for an interference filter are calculated for each frequency offset, based upon the burst of symbols.
  • the burst of symbols are filtered, for each frequency offset, using the interference suppression filter with the corresponding plurality of weights to determine an estimated midamble sequence.
  • the estimated midamble sequence for each frequency offset is compared to a previously known midamble sequence to determine a midamble estimation error for that frequency offset.
  • One of the plurality of frequency offsets is determined, in step 612 , to be a preferred frequency offset, based upon the midamble estimation error thereof.
  • a parallel approach to locating an optimal frequency/timing hypothesis pair may be utilized, with a corresponding increase in computational complexity over a serial approach (e.g., where there are 5 frequency hypotheses and 7 timing hypotheses, a serial approach may involve determining a prediction error 12 times, whereas a parallel approach will involve determining a prediction error 35 times). Nevertheless, a parallel approach may provide even more accurate estimation of timing and frequency for improved performance.
  • FIG. 7 illustrates a receiver for use in a wireless communication system in accordance with one aspect of the subject technology.
  • Receiver 700 includes an antenna 710 configured to receive a wireless signal.
  • the received signal is provided to a pre-processor 720 which demodulates the signal to generate received samples.
  • Pre-processor 720 may include a GMSK-to-BPSK rotator that performs phase rotation on the received samples.
  • Timing and frequency estimator 730 receives the samples from pre-processor 720 and generates a plurality of timing and frequency hypotheses regarding where a training sequence of symbols (i.e., midamble) begins in the burst of data (timing) and at which frequency the symbols can be optimally received (frequency).
  • a training sequence of symbols i.e., midamble
  • Interference suppressor 740 iteratively performs single antenna interference cancellation on the symbols for each timing and frequency hypothesis pair, calculating different filter weights for each hypothesis pair, and midamble estimator 750 generates a midamble estimation error for each hypothesis pair, as described in greater detail above.
  • Timing and frequency decision circuit 760 compares the midamble estimation errors for each hypothesis pair and selects the pair with the lowest midamble estimation error.
  • the selection of a hypothesis pair by timing and frequency decision circuit 760 represents the position in the burst of symbols where the midamble is estimated to begin, and the optimal frequency at which to receive the burst of symbols.
  • the signal is then provided to data processor 770 , which processes the received symbols based upon the selected timing and frequency hypotheses, and outputs the data corresponding to the received symbols.
  • FIG. 8 illustrates a method for suppressing interference in accordance with one aspect of the subject technology.
  • the method begins in step 801 , in which a burst of symbols are received.
  • step 802 a subset of the burst of symbols is selected.
  • the subset of the burst of symbols includes a first midamble symbol.
  • step 803 the subset selected in step 802 is iteratively adjusted by a plurality of timing and frequency offsets.
  • a plurality of weights for an interference filter are calculated for each timing and frequency offset pair, based upon the burst of symbols.
  • step 805 the burst of symbols are filtered, for each pair of offsets, using the interference suppression filter with the corresponding plurality of weights to determine an estimated midamble sequence.
  • step 806 the estimated midamble sequence for each offset pair is compared to a previously known midamble sequence to determine a midamble estimation error for that timing offset.
  • One of the plurality combination of timing and frequency offsets is determined, in step 807 , to be a preferred combination, based upon the midamble estimation error thereof.
  • the preferred combination is the combination corresponding to the lowest midamble estimation error.
  • FIG. 9 illustrates a receiver for use in a wireless communication system in accordance with one aspect of the subject technology.
  • Receiver 900 includes an antenna module 910 configured to receive a wireless signal. While receiver 900 may be used in various communication systems, for clarity, receiver 900 is specifically described herein with respect to a GSM system.
  • the received signal is provided to a pre-processor module 920 which demodulates the signal to generate received samples.
  • Pre-processor module 920 may include a GMSK-to-BPSK rotator that performs phase rotation on the received samples.
  • Timing estimator module 930 receives the samples from pre-processor module 920 and generates a plurality of timing hypotheses regarding where a training sequence of symbols (i.e., midamble) begins in the burst of data.
  • Interference suppressor module 940 iteratively performs single antenna interference cancellation on the symbols for each timing hypothesis, calculating different filter weights for each timing hypothesis, and midamble estimator module 950 generates a midamble estimation error for each hypothesis, as described in greater detail above.
  • Timing decision circuit 960 compares the midamble estimation errors for each hypothesis and selects the hypothesis with the lowest midamble estimation error. The selection of a hypothesis by timing decision module 960 represents the position in the burst of symbols where the midamble is estimated to begin.
  • Frequency estimator module 970 receives the samples from timing decision module 960 and generates a plurality of frequency hypotheses regarding a frequency on which symbols are transmitted. Interference suppressor module 940 iteratively performs single antenna interference cancellation on the symbols for each frequency hypothesis, calculating different filter weights for each frequency hypothesis, and midamble estimator module 950 generates a midamble estimation error for each hypothesis, as described in greater detail above. Frequency decision circuit 980 compares the midamble estimation errors for each hypothesis and selects the hypothesis with the lowest midamble estimation error. The selection of a hypothesis by frequency decision module 980 represents the optimal frequency at which to receive the burst of symbols. The signal is then provided to data processor module 990 , which processes the received symbols based upon the selected timing and frequency hypotheses, and outputs the data corresponding to the received symbols.
  • FIG. 10 illustrates a receiver for use in a wireless communication system in accordance with one aspect of the subject technology.
  • Receiver 1000 includes an antenna module 1010 configured to receive a wireless signal. The received signal is provided to a pre-processor module 1020 which demodulates the signal to generate received samples.
  • Pre-processor module 1020 may include a GMSK-to-BPSK rotator that performs phase rotation on the received samples.
  • Timing and frequency estimator module 1030 receives the samples from pre-processor module 1020 and generates a plurality of timing and frequency hypotheses regarding where a training sequence of symbols (i.e., midamble) begins in the burst of data (timing) and at which frequency the symbols can be optimally received (frequency).
  • a training sequence of symbols i.e., midamble
  • Interference suppressor module 1040 iteratively performs single antenna interference cancellation on the symbols for each timing and frequency hypothesis pair, calculating different filter weights for each hypothesis pair, and midamble estimator module 1050 generates a midamble estimation error for each hypothesis pair, as described in greater detail above.
  • Timing and frequency decision module 1060 compares the midamble estimation errors for each hypothesis pair and selects the pair with the lowest midamble estimation error.
  • the selection of a hypothesis pair by timing and frequency decision module 1060 represents the position in the burst of symbols where the midamble is estimated to begin, and the optimal frequency at which to receive the burst of symbols.
  • the signal is then provided to data processor module 1070 , which processes the received symbols based upon the selected timing and frequency hypotheses, and outputs the data corresponding to the received symbols.
  • FIG. 11 is a block diagram that illustrates a computer system 1100 upon which an aspect may be implemented.
  • Computer system 1100 includes a bus 1102 or other communication mechanism for communicating information, and a processor 1104 coupled with bus 1102 for processing information.
  • Computer system 1100 also includes a memory 1106 , such as a random access memory (“RAM”) or other dynamic storage device, coupled to bus 1102 for storing information and instructions to be executed by processor 1104 .
  • Memory 1106 may also be used for storing temporary variable or other intermediate information during execution of instructions to be executed by processor 1104 .
  • Computer system 1100 further includes a data storage device 1110 , such as a magnetic disk or optical disk, coupled to bus 1102 for storing information and instructions.
  • Computer system 1100 may be coupled via I/O module 1108 to a display device (not illustrated), such as a cathode ray tube (“CRT”) or liquid crystal display (“LCD”) for displaying information to a computer user.
  • a display device such as a cathode ray tube (“CRT”) or liquid crystal display (“LCD”) for displaying information to a computer user.
  • An input device such as, for example, a keyboard or a mouse may also be coupled to computer system 1100 via I/O module 1108 for communicating information and command selections to processor 1104 .
  • timing and frequency estimation is performed by a computer system 1100 in response to processor 1104 executing one or more sequences of one or more instructions contained in memory 1106 .
  • Such instructions may be read into memory 1106 from another machine-readable medium, such as data storage device 1110 .
  • Execution of the sequences of instructions contained in main memory 1106 causes processor 1104 to perform the process steps described herein.
  • processors in a multi-processing arrangement may also be employed to execute the sequences of instructions contained in memory 1106 .
  • hard-wired circuitry may be used in place of or in combination with software instructions to implement various aspects. Thus, aspects are not limited to any specific combination of hardware circuitry and software.
  • machine-readable medium refers to any medium that participates in providing instructions to processor 1104 for execution. Such a medium may take many forms, including, but not limited to, non-volatile media, volatile media, and transmission media.
  • Non-volatile media include, for example, optical or magnetic disks, such as data storage device 1110 .
  • Volatile media include dynamic memory, such as memory 1106 .
  • Transmission media include coaxial cables, copper wire, and fiber optics, including the wires that comprise bus 1102 . Transmission media can also take the form of acoustic or light waves, such as those generated during radio frequency and infrared data communications.
  • Machine-readable media include, for example, floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH EPROM, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Noise Elimination (AREA)
  • Radio Transmission System (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Time-Division Multiplex Systems (AREA)
  • Synchronisation In Digital Transmission Systems (AREA)
  • Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)
US12/464,311 2008-05-13 2009-05-12 Interference cancellation under non-stationary conditions Abandoned US20100046660A1 (en)

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US12/464,311 US20100046660A1 (en) 2008-05-13 2009-05-12 Interference cancellation under non-stationary conditions
TW101144327A TW201320664A (zh) 2008-05-13 2009-05-13 非平穩條件下的干擾消除
RU2010150761/08A RU2481742C2 (ru) 2008-05-13 2009-05-13 Подавление помех при нестационарных условиях
TW098115882A TWI393396B (zh) 2008-05-13 2009-05-13 非平穩條件下的干擾消除
CA2723730A CA2723730A1 (en) 2008-05-13 2009-05-13 Interference cancellation under non-stationary conditions
EP09747422A EP2294716A2 (en) 2008-05-13 2009-05-13 Interference cancellation under non-stationary conditions
KR1020107027900A KR101247479B1 (ko) 2008-05-13 2009-05-13 비정상 조건 하에서의 간섭 제거
KR1020127014772A KR20120082942A (ko) 2008-05-13 2009-05-13 비정상 조건 하에서의 간섭 제거
EP12150520A EP2472734A1 (en) 2008-05-13 2009-05-13 Interference cancellation under non-stationary conditions
JP2011509633A JP2011524115A (ja) 2008-05-13 2009-05-13 非定常状態下での干渉消去
PCT/US2009/043718 WO2009140338A2 (en) 2008-05-13 2009-05-13 Interference cancellation under non-stationary conditions
CN2009801170948A CN102027692A (zh) 2008-05-13 2009-05-13 非静止条件下的干扰消除
US13/215,984 US8675796B2 (en) 2008-05-13 2011-08-23 Interference cancellation under non-stationary conditions
JP2012238170A JP2013070384A (ja) 2008-05-13 2012-10-29 非定常状態下での干渉消去

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