EP1925092A1 - Joint demodulation filter for co-channel interference reduction and related methods - Google Patents
Joint demodulation filter for co-channel interference reduction and related methodsInfo
- Publication number
- EP1925092A1 EP1925092A1 EP06790562A EP06790562A EP1925092A1 EP 1925092 A1 EP1925092 A1 EP 1925092A1 EP 06790562 A EP06790562 A EP 06790562A EP 06790562 A EP06790562 A EP 06790562A EP 1925092 A1 EP1925092 A1 EP 1925092A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- signal
- filter
- channel
- impulse response
- joint demodulation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
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Classifications
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- 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
- H04B1/06—Receivers
- H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
- H04B1/109—Means associated with receiver for limiting or suppressing noise or interference by improving strong signal performance of the receiver when strong unwanted signals are present at the receiver input
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03D—DEMODULATION OR TRANSFERENCE OF MODULATION FROM ONE CARRIER TO ANOTHER
- H03D1/00—Demodulation of amplitude-modulated oscillations
-
- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
- H03M13/37—Decoding methods or techniques, not specific to the particular type of coding provided for in groups H03M13/03 - H03M13/35
- H03M13/39—Sequence estimation, i.e. using statistical methods for the reconstruction of the original codes
- H03M13/41—Sequence estimation, i.e. using statistical methods for the reconstruction of the original codes using the Viterbi algorithm or Viterbi processors
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- 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
- H04B1/06—Receivers
- H04B1/16—Circuits
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0045—Arrangements at the receiver end
- H04L1/0047—Decoding adapted to other signal detection operation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0045—Arrangements at the receiver end
- H04L1/0054—Maximum-likelihood or sequential decoding, e.g. Viterbi, Fano, ZJ algorithms
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/20—Arrangements for detecting or preventing errors in the information received using signal quality detector
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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
- H04L25/0204—Channel estimation of multiple channels
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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
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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
- H04L25/03178—Arrangements involving sequence estimation techniques
- H04L25/03248—Arrangements for operating in conjunction with other apparatus
- H04L25/03292—Arrangements for operating in conjunction with other apparatus with channel estimation circuitry
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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
- H04L25/03178—Arrangements involving sequence estimation techniques
- H04L25/03305—Joint sequence estimation and interference removal
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
- H04W88/02—Terminal devices
Definitions
- the present invention relates to wireless communications systems, such as cellular communications systems, and, more particularly, to filtering received wireless signals to reduce unwanted interference.
- Cellular communications systems continue to grow in popularity and have become an integral part of both personal and business communications.
- Cellular telephones allow users to place and receive voice calls most anywhere they travel.
- One such challenge is addressing interference caused between multiple cellular devices operating in a given geographical area.
- Cellular devices communicate with a cellular base station using common or shared wireless communications channels (i.e., frequencies).
- common or shared wireless communications channels i.e., frequencies.
- signals between other devices and a base station using the same channel may cause a desired signal from the base station to be significantly degraded or even dropped by the handheld device.
- Such interference is called co-channel interference.
- SAIC single-antenna interference cancellation
- SAIC Single Antenna Interference Cancellation
- 3GPP TR 45.903 Version 6.0.1, Release 6, European Telecommunications Standards Institute, 2004 This is the more limited case that requires one to assume that the base station synchronization data sequences (i.e., training sequences) of the desired-signal and dominant-interferer overlap, which in turn makes the estimation of the CIRs possible using previously known techniques. It also requires one to assume that the interferer will be dominant for the entire burst.
- FIG. 1 is a schematic block diagram of an exemplary Single Antenna Interference Cancellation (SAIC) enabled joint demodulation Global System for Mobile Communication (GSM) receiver in accordance with the present invention.
- SAIC Single Antenna Interference Cancellation
- GSM Global System for Mobile Communication
- FIG. 2 is a schematic block diagram of an exemplary embodiment of the joint demodulation receiver of FIG. 1 shown in greater detail.
- FIG. 3 is a graph of simulated performance results for an SAIC joint demodulation receiver in accordance with the present invention and a typical GMSK receiver in accordance with the prior art.
- FIG. 4 is a flow diagram of an exemplary joint demodulation filtering method for reducing co-channel interference between a desired signal and a co-channel interfering signal in accordance with the invention.
- FIG. 5 is a schematic block diagram of an exemplary wireless communication device in which the joint demodulation receiver of FIG. 1 may be used.
- a joint demodulation filter for reducing co- channel interference between a desired signal and a co-channel interfering signal.
- the filter may include an input receiving samples of the desired signal and the co-channel interfering signal, a Viterbi decoder, and a first signal path between the input and the Viterbi decoder comprising a first filter.
- the joint demodulation filter may further include a second signal path between the input and the Viterbi decoder and comprising a linear finite impulse response (FIR) modeler for generating a channel impulse response estimate for the co-channel interfering signal.
- a third signal path may be between the input and the Viterbi decoder and include a whitened matched filter for generating a channel impulse response estimate for the desired signal.
- the desired signal and the co-channel interfering signal may each include a training sequence
- the joint demodulation filter may further include a training- sequence locator upstream of the second and third paths and downstream from the input.
- the third signal path may include a desired-signal channel impulse response (CIR) estimator upstream of the whitened matched filter for generating a desired- signal CIR estimate.
- the first filter may be a first finite impulse response (FIR) filter.
- the second signal path may include a first summer and a second summer connected downstream therefrom. Moreover, the second signal path may further include a remodulator between the desired-signal CIR estimator and the first summer and cooperating therewith for subtracting a remodulated desired-signal training sequence from samples of the desired signal and the co-channel interfering signal to thereby generate an interference signal estimate.
- the linear FIR modeler may include a blind interference and CIR estimator, and a second FIR filter downstream from the blind interference and CIR estimator.
- the Viterbi decoder may also iteratively build a tree of interferer bit sequence hypotheses.
- a joint demodulation filtering method for reducing co-channel interference between a desired signal and a co-channel interfering signal may include filtering receiving samples of the desired signal and the co-channel interfering signal using a first signal path comprising a first filter. The method may further include generating a channel impulse response estimate for the co-channel interfering signal using a second signal path comprising a linear finite impulse response (FIR) modeler, and generating a channel impulse response estimate for the desired signal using a third signal path comprising a whitened matched filter.
- FIR linear finite impulse response
- a decoding operation may be performed based upon the filtered received samples of the desired signal and the co-channel interfering signal, the channel impulse response estimate for the co-channel interfering signal, and the channel impulse response estimate for the desired signal using a Viterbi decoder.
- a joint demodulation filter 10 in accordance with an exemplary embodiment illustratively includes an input 11 receiving samples of a desired signal and a co-channel interfering signal, e.g., from the antenna of a wireless communications device (e.g., a mobile cellular device). That is, the joint demodulation filter 10 may advantageously be implemented in a wireless receiver of a mobile wireless communications device.
- the various components of the joint demodulation filter 10 may be implemented using software modules and a processing circuitry, such as a digital signal processor (DSP), for example, although other implementations are also possible, as will be appreciated by those skilled in the art. Exemplary components of a mobile cellular device in which the joint demodulation filter 10 may be used will be discussed further below with reference to FIG. 5.
- DSP digital signal processor
- the joint demodulation filter 10 further illustratively includes a Viterbi decoder 30, and a first signal path 12 between the input 11 and the Viterbi decoder comprising a first filter 46.
- the first filter 46 may be a finite infinite response (FIR) filter, such as a matched filter, for example.
- FIR finite infinite response
- a second signal path 13 is included between the input 11 and the Viterbi decoder 30.
- the second signal path 13 illustratively includes a linear FIR modeler 15 for generating a channel impulse response estimate for the co-channel interfering signal.
- a third signal path 14 is illustratively connected between the input 11 and the Viterbi decoder 30.
- the third signal branch illustratively includes a whitened matched filter 44 for generating a channel impulse response estimate for the desired signal, as will be discussed further below.
- the joint demodulation filter 10 illustratively includes a training-sequence locator 20 for the desired signal upstream of the second and third paths 13, 14 and downstream from the input 11.
- the third signal path 14 illustratively includes a desired-signal CIR estimator 22 upstream of the whitened matched filter 44 for generating a desired-signal CIR estimate.
- the second signal path 13 also illustratively includes a first summer 26, a second summer 34 connected downstream from the first summer, and a remodulator 24 between the desired-signal CIR estimator 22 and the first summer and cooperating therewith for subtracting a remodulated desired-signal training sequence from samples of the desired signal and the co-channel interfering signal to thereby generate an interference signal estimate.
- the linear FIR modeler 15 illustratively includes a blind interference and CIR estimator 28, coupled to the summer 26, and a second FIR filter 42 downstream from the blind interference and CIR estimator 28, which also receives an input from the whitened matched filter 44.
- the second summer 34 also receives an output of the blind interference and CIR estimator 28, as shown.
- the second signal path 13 further illustratively includes a residual noise power (Pn) sample offset block 32 between the first and second summers 26, 34, a significant interferer component (Pif) sample offset block downstream from the second summer, and a Pif/Pn decision block 38 downstream from the Pif sample offset block, as will be discussed further below.
- a mixer 40 is downstream from the Pif sample offset block 38 and also receives an output of the second FIR filter 42 as shown.
- the output of the mixer 40 and the output of the whitened matched filter 44 are provided to the Viterbi decoder 30, as is the output of the first FIR 46.
- joint demodulation uses estimates for a channel impulse response (CIR) for a desired signal and a dominant interferer associated therewith.
- CIR channel impulse response
- the dominant interferer is a GMSK modulated signal conforming to the GSM specification.
- the joint demodulation approach set forth herein may be applicable to both synchronized and unsynchronized networks, in that this technique uses "blind" interferer data and channel estimation techniques rather than making the above-noted assumptions.
- a two-dimensional (joint) adaptive Viterbi state structure may be used in the equalizer to estimate the data for both the desired signal and the interferer.
- Simulations of the present joint demodulation technique have demonstrated greater than 10 dB carrier-to-interference(C/I) improvement at about 0 dB C/I in the raw symbol error rate and frame error rate for 12.2-rate AMR FS speech.
- C/I carrier-to-interference
- a new joint-least-squares based technique was used for channel-offset positioning and desired and interferer CIR estimation. As noted above, this approach is coupled with blind estimation of the interferer data (i.e., with no a-priori knowledge of the interferer's data).
- the present joint demodulation approach may be particularly advantageous in its ability to provide relatively high gains (i.e., in its ability to receive at very low signal-to- noise ratios (SNRs)) when limited a-priori knowledge about the interferer is available, as will be discussed further below.
- SNRs signal-to- noise ratios
- VA Viterbi algorithm
- BLER Block Error Rate
- the joint demodulation approach assumes that the dominant interference component may be modeled as the noisy output of a finite-impulse-response (FIR) (unknown) filter with unknown, binary, random input (interferer) data.
- FIR finite-impulse-response
- this assumption holds even if there are additional, weaker interference signals present, which are treated as residual noise.
- this approach may be applied to other interferer modulation types using the above modeling assumption.
- a base station training sequence (TS) for the desired signal is found (Block 20)
- the CIR for the desired signal is estimated (Block 22)
- the re- modulated desired training sequence is removed from the input samples to form the interferer-signal estimate (Block 24).
- the "blind" estimation of the interferer CIR and data is performed based upon the interferer-signal estimate, at Blocks 26, 28.
- a joint least-squares desired/interferer channel estimation using the desired training sequence and estimated interferer data is performed at Block 30, as will be discussed further below.
- the foregoing steps may be repeated (or performed in a vectorized form) at multiple input sample offsets (as the timing offset varies).
- the offset yielding the minimal residual noise power (Pn) may be selected, and a determination may be made as to whether the model applies (i.e., was a significant interferer component (Pif) detected or not), at Blocks 32, 34, 36, and 38. If so, demodulation is performed using a joint-demodulation (multi-dimensional state) Viterbi algorithm that estimates and removes the interference jointly with the estimation of the desired-signal data (Block 30).
- the desired channel impulse response was estimated using a conventional training-sequence correlation (i.e., "channel-sounding") method, as will be appreciated by those skilled in the art.
- channel-sounding i.e., "channel-sounding”
- the least-squares method provides the initial desired channel impulse response estimate by multiplying the input samples by a constant (pre-computed) matrix (A H A) " ' A H , where A is the training-sequence convolution matrix of the desired signal.
- the above-noted SAIC Feasibility Study assumes a synchronous network model. More particularly, this model assumes that the training sequence of the interfering signal is aligned with the desired signal's training sequence within a -1 to +4 symbol offset.
- the interferer channel impulse response can be estimated using the training-sequence correlation technique (or least squares, since the training-sequence data is known) after removing the desired signal's (re-modulated) training sequence from the received samples.
- This approach uses an algorithm which combines concepts of vector quantization and sequential decoding of convolutional codes.
- the algorithm is based on two assumptions: (1) the interferer signal may be modeled with a linear Finite Impulse Response (FIR) source (Block 28); and (2) the interferer signal is corrupted by residual additive white (i.e., uncorrelated) Gaussian noise (after removing the estimated desired signal) (FIG. 1, 26).
- FIR Finite Impulse Response
- the algorithm iteratively builds a tree of interferer bit sequence hypotheses. For each new bit added to a bit sequence hypothesis, it computes the new FIR state (or codebook index, as will be apparent to those skilled in the art of vector quantization) and averages all input samples corresponding to the same state in a particular sequence to estimate the FIR output (codebook value) for that state.
- the distortion of a bit sequence is what remains after removing the sequence's FIR outputs from the input samples (FIG. 2, 36).
- each sequence is extended by another 0/1 bit to yield two new sequences (2W total), and the process of re-estimating FIR outputs of each sequence is repeated followed by keeping the W sequences with minimum distortion (e.g., one-half the sequences).
- W search width parameter
- This above-described algorithm provides the initial interferer data and channel impulse response estimates for subsequent joint least-squares desired-signal and interferer- channel estimation.
- the CIR position (offset), and CIR value estimation for the desired and interferer is affected by the cross-correlation of the desired and interferer data sequences.
- a joint least-squares channel estimation is possible that removes (i.e., accounts for) this cross-correlation as follows:
- a (NxLh) and B (NxLg) are the desired-signal and interferer data-sequence convolution matrices (A is known and constant, B is an estimate for the interferer), and h and g are the desired-signal and interferer CIRs respectively that result from solving the above equations with Lh (5 in this embodiment) the length of h, and Lg (3 chosen for this embodiment) the length of g.
- a two-dimensional state Viterbi algorithm may be applied. For a Euclidean distance metric, the whitened discrete time model filter (WMF) is computed from the estimated desired CIR (Block 44). The computation is also applied to the interferer CIR, and the three (Lg) largest resulting taps are used to form the interferer codebook (i.e., a set of possible interferer channel FIR outputs). Of course, other numbers of taps Lh and Lg may also be used in some embodiments.
- WMF whitened discrete time model filter
- the resulting desired-signal and interferer codebooks are passed to the joint- demodulation Viterbi algorithm.
- the returned soft-decision metrics include the forward and backward recursion using the difference of the odd/even state minimum metrics at each stage (not path) as the soft decision value and sign.
- FIG. 3 simulated results for TCH-AFS 12.2 rate speech for a typical urban fading profile at 50km vehicle speeds (TU-50) at the 1950MHz band without the use of frequency hopping and using interferer model DTSl are shown, as will be appreciated by those skilled in the art.
- C/I is the average carrier-to-interference ratio.
- the dotted lines 50 and 51 represent the SER (symbol error rate) and FER (frame error rates) of the conventional GMSK receiver.
- the dashed lines 53 and 54 represent the performance of the above-described SAIC-JD receiver.
- the solid lines 55 and 56 represent the performance of a higher-complexity SAIC-JD receiver in accordance with an exemplary embodiment of the invention in which the blind vector quantization of the interferer is performed using recursive least squares (RLS) updates while the interferer symbol sequence hypotheses are formed and evaluated.
- RLS recursive least squares
- the amount of residual "noise” power remaining in the desired signal's training- sequence window after removing the desired (i.e., estimated) samples may be used as a test of model "fit” in some embodiments. If removing the subsequently estimated interferer does not reduce the residual power significantly, a non-interference signal model may be selected, and vice-versa.
- a joint demodulation filtering method for reducing co-channel interference between a desired signal and a co-channel interfering signal will now be described with reference to FIG. 4.
- receiving samples of the desired signal and the co-channel interfering signal are filtered using a first signal path 12 comprising a first filter 46, at Block 61.
- the method may further include generating a channel impulse response estimate for the co-channel interfering signal using a second signal path 13 comprising a linear finite impulse response (FIR) modeler 15, at Block 62, and generating a channel impulse response estimate for the desired signal using a third signal path 14 comprising a whitened matched filter 44, at Block 63.
- FIR linear finite impulse response
- a decoding operation may be performed based upon the filtered received samples of the desired signal and the co-channel interfering signal, the channel impulse response estimate for the co-channel interfering signal, and the channel impulse response estimate for the desired signal using a Viterbi decoder 30, at Block 64, thus concluding the illustrated method (Block 65).
- the device 1000 illustratively includes a housing 1200, a keypad 1400 and an output device 1600.
- the output device shown is a display 1600, which is preferably a full graphic LCD. Other types of output devices may alternatively be utilized.
- a processing device 1800 is contained within the housing 1200 and is coupled between the keypad 1400 and the display 1600. The processing device 1800 controls the operation of the display 1600, as well as the overall operation of the mobile device 1000, in response to actuation of keys on the keypad 1400 by the user.
- the housing 1200 may be elongated vertically, or may take on other sizes and shapes (including clamshell housing structures).
- the keypad may include a mode selection key, or other hardware or software for switching between text entry and telephony entry.
- other parts of the mobile device 1000 are shown schematically in FIG. 5. These include a communications subsystem 1001; a short- range communications subsystem 1020; the keypad 1400 and the display 1600, along with other input/output devices 1060, 1080, 1100 and 1120; as well as memory devices 1160, 1180 and various other device subsystems 1201.
- the mobile device 1000 is preferably a two-way RF communications device having voice and data communications capabilities.
- the mobile device 1000 preferably has the capability to communicate with other computer systems via the Internet.
- Operating system software executed by the processing device 1800 is preferably stored in a persistent store, such as the flash memory 1160, but may be stored in other types of memory devices, such as a read only memory (ROM) or similar storage element.
- system software, specific device applications, or parts thereof may be temporarily loaded into a volatile store, such as the random access memory (RAM) 1180. Communications signals received by the mobile device may also be stored in the RAM 1180.
- the processing device 1800 in addition to its operating system functions, enables execution of software applications 1300A-1300N on the device 1000.
- a predetermined set of applications that control basic device operations, such as data and voice communications 1300A and 1300B, may be installed on the device 1000 during manufacture.
- a personal information manager (PIM) application may be installed during manufacture.
- the PIM is preferably capable of organizing and managing data items, such as e-mail, calendar events, voice mails, appointments, and task items.
- the PIM application is also preferably capable of sending and receiving data items via a wireless network 1401.
- the PIM data items are seamlessly integrated, synchronized and updated via the wireless network 1401 with the device user's corresponding data items stored or associated with a host computer system.
- the communications subsystem 1001 includes a receiver 1500, a transmitter 1520, and one or more antennas 1540 and 1560.
- the communications subsystem 1001 also includes a processing module, such as a digital signal processor (DSP) 1580, and local oscillators (LOs) 1601.
- DSP digital signal processor
- LOs local oscillators
- a mobile device 1000 may include a communications subsystem 1001 designed to operate with the MobitexTM, Data TACTM or General Packet Radio Service (GPRS) mobile data communications networks, and also designed to operate with any of a variety of voice communications networks, such as AMPS, TDMA, CDMA, WCDMA, PCS, GSM, EDGE, etc. Other types of data and voice networks, both separate and integrated, may also be utilized with the mobile device 1000.
- the mobile device 1000 may also be compliant with other communications standards such as 3GSM, 3GPP, UMTS, etc.
- Network access requirements vary depending upon the type of communication system. For example, in the Mobitex and DataTAC networks, mobile devices are registered on the network using a unique personal identification number or PIN associated with each device. In GPRS networks, however, network access is associated with a subscriber or user of a device. A GPRS device therefore requires a subscriber identity module, commonly referred to as a SIM card, in order to operate on a GPRS network.
- SIM card subscriber identity module
- the mobile device 1000 may send and receive communications signals over the communication network 1401.
- Signals received from the communications network 1401 by the antenna 1540 are routed to the receiver 1500, which provides for signal amplification, frequency down conversion, filtering, channel selection, etc., and may also provide analog to digital conversion. Analog-to-digital conversion of the received signal allows the DSP 1580 to perform more complex communications functions, such as demodulation and decoding.
- signals to be transmitted to the network 1401 are processed (e.g. modulated and encoded) by the DSP 1580 and are then provided to the transmitter 1520 for digital to analog conversion, frequency up conversion, filtering, amplification and transmission to the communication network 1401 (or networks) via the antenna 1560.
- the DSP 1580 provides for control of the receiver 1500 and the transmitter 1520. For example, gains applied to communications signals in the receiver 1500 and transmitter 1520 may be adaptively controlled through automatic gain control algorithms implemented in the DSP 1580.
- a received signal such as a text message or web page download
- the communications subsystem 1001 is input to the processing device 1800.
- the received signal is then further processed by the processing device 1800 for an output to the display 1600, or alternatively to some other auxiliary I/O device 1060.
- a device user may also compose data items, such as e-mail messages, using the keypad 1400 and/or some other auxiliary I/O device 1060, such as a touchpad, a rocker switch, a thumb-wheel, or some other type of input device.
- the composed data items may then be transmitted over the communications network 1401 via the communications subsystem 1001.
- a voice communications mode In a voice communications mode, overall operation of the device is substantially similar to the data communications mode, except that received signals are output to a speaker 1100, and signals for transmission are generated by a microphone 1120.
- Alternative voice or audio I/O subsystems such as a voice message recording subsystem, may also be implemented on the device 1000.
- the display 1600 may also be utilized in voice communications mode, for example to display the identity of a calling party, the duration of a voice call, or other voice call related information.
- the short-range communications subsystem enables communication between the mobile device 1000 and other proximate systems or devices, which need not necessarily be similar devices.
- the short-range communications subsystem may include an infrared device and associated circuits and components, or a BluetoothTM communications module to provide for communication with similarly-enabled systems and devices.
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- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Power Engineering (AREA)
- Physics & Mathematics (AREA)
- Probability & Statistics with Applications (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Artificial Intelligence (AREA)
- Noise Elimination (AREA)
- Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)
Abstract
Description
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Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
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CA002516910A CA2516910A1 (en) | 2005-08-23 | 2005-08-23 | Joint demodulation techniques for interference cancellation |
PCT/CA2006/001379 WO2007022627A1 (en) | 2005-08-23 | 2006-08-23 | Joint demodulation filter for co-channel interference reduction and related methods |
Publications (2)
Publication Number | Publication Date |
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EP1925092A1 true EP1925092A1 (en) | 2008-05-28 |
EP1925092A4 EP1925092A4 (en) | 2009-01-14 |
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EP06790561A Withdrawn EP1925091A4 (en) | 2005-08-23 | 2006-08-23 | Wireless communications device including a joint demodulation filter for co-channel interference reduction and related methods |
EP06790562A Withdrawn EP1925092A4 (en) | 2005-08-23 | 2006-08-23 | Joint demodulation filter for co-channel interference reduction and related methods |
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EP06790561A Withdrawn EP1925091A4 (en) | 2005-08-23 | 2006-08-23 | Wireless communications device including a joint demodulation filter for co-channel interference reduction and related methods |
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EP (2) | EP1925091A4 (en) |
JP (1) | JP4845965B2 (en) |
KR (1) | KR100979742B1 (en) |
CN (2) | CN101292433A (en) |
AU (1) | AU2006284391B2 (en) |
BR (1) | BRPI0614959A2 (en) |
CA (1) | CA2516910A1 (en) |
WO (2) | WO2007022626A1 (en) |
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US7460832B2 (en) | 2004-04-12 | 2008-12-02 | The Directv Group, Inc. | Methods and apparatuses for minimizing co-channel interference |
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US7161988B2 (en) | 2004-04-12 | 2007-01-09 | The Directv Group, Inc. | Method and apparatus for minimizing co-channel interference |
US7639763B2 (en) | 2005-08-23 | 2009-12-29 | Research In Motion Limited | Wireless communications device including a joint demodulation filter for co-channel interference reduction and related methods |
US7643590B2 (en) * | 2005-08-23 | 2010-01-05 | Research In Motion Limited | Joint demodulation filter for co-channel interference reduction and related methods |
KR101610305B1 (en) * | 2009-03-20 | 2016-04-20 | 삼성전자주식회사 | Apparatus and method for reducing inter-cell interference in multiple input multiple output system |
US8433015B2 (en) | 2009-12-03 | 2013-04-30 | Glowlink Communications Technology, Inc. | System for and method of removing unwanted inband signals from a received communication signal |
KR101363385B1 (en) * | 2009-12-18 | 2014-02-14 | 한국전자통신연구원 | Receiver of Real Time Locating System |
US8938038B2 (en) * | 2012-02-02 | 2015-01-20 | Telefonaktiebolaget L M Ericsson (Publ) | Extending the set of addressable interferers for interference mitigation |
CN103051573B (en) * | 2012-12-12 | 2016-07-06 | 锐迪科科技有限公司 | Gsm system disturbs signal cancellation module and its implementation |
US8938041B2 (en) | 2012-12-18 | 2015-01-20 | Intel Corporation | Techniques for managing interference in multiple channel communications system |
SG11201506441VA (en) * | 2013-02-26 | 2015-09-29 | Glowlink Communications Technology Inc | System for and method of removing unwanted inband signals from a received communication signal |
CN105703878B (en) * | 2014-11-28 | 2019-04-30 | 联芯科技有限公司 | A kind of sequence detecting method and device |
KR102449737B1 (en) * | 2015-06-25 | 2022-09-30 | 한국전자통신연구원 | Method and apparatus for tuning finite impulse response filter in in-band full duplex transceiver |
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CN101292433A (en) | 2008-10-22 |
AU2006284391B2 (en) | 2009-12-10 |
WO2007022626A1 (en) | 2007-03-01 |
KR20080036235A (en) | 2008-04-25 |
WO2007022627A1 (en) | 2007-03-01 |
EP1925091A1 (en) | 2008-05-28 |
CN101292432A (en) | 2008-10-22 |
EP1925091A4 (en) | 2009-01-14 |
KR100979742B1 (en) | 2010-09-09 |
JP4845965B2 (en) | 2011-12-28 |
BRPI0614959A2 (en) | 2011-04-26 |
AU2006284391A1 (en) | 2007-03-01 |
CA2516910A1 (en) | 2007-02-23 |
JP2009506595A (en) | 2009-02-12 |
EP1925092A4 (en) | 2009-01-14 |
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