(19) United States
`(12) Patent Application Publication (io) Pub. No.: US 2004/0165683 Al
`(43) Pub. Date:
`Aug. 26,2004
`Gupta et al.
`
`US 20040165683A1
`
`(54) CHANNEL ESTIMATION FOR
`COMMUNICATION SYSTEMS
`
`(76) Inventors: Alok Kumar Gupta, Carlsbad, CA
`(US); Rajiv Vijayan, San Diego, CA
`(US)
`
`Correspondence Address:
`Qualcomm Incorporated
`Patents Department
`5775 Morehouse Drive
`San Diego, CA 92121-1714 (US)
`
`(21) Appi. No.:
`
`10/651,625
`
`(22) Filed:
`
`Aug. 28, 2003
`
`Related U.S. Application Data
`
`(60) Provisional application No. 60/408,968, filed on Sep.
`4, 2002.
`
`Publication Classification
`
`Int. Cl.7 ................................................... H04L 27/06
`(51)
`(52) U.S. Cl............................................................... 375/340
`
`ABSTRACT
`(57)
`An improved channel estimation is disclosed. In one
`embodiment, initial channel estimation is performed using
`known training data sequence. The data packet received is
`demodulated based on the initial channel estimates, de­
`interleaved and decoded. The decoded data is then is re­
`encoded, interleaved and modulated to generate additional
`training symbols for updating the channel estimates through­
`out the received data packet.
`
`RECOVERED
`DATA
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`1
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`DELL EX. 1008
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`Patent Application Publication Aug. 26,2004 Sheet 1 of 4
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`Patent Application Publication Aug. 26,2004 Sheet 2 of 4
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`FIG. 4
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`FIG. 3
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`FIG. 5
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`Patent Application Publication Aug. 26,2004 Sheet 3 of 4
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`FIG. 6
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`Patent Application Publication Aug. 26,2004 Sheet 4 of 4
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`Aug. 26, 2004
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`CHANNEL ESTIMATION FOR COMMUNICATION
`SYSTEMS
`
`CROSS-REFERENCE TO RELATED
`APPLICATIONS
`[0001] This application is also related to the following, all
`of which are assigned to the same assignee of this applica­
`tion.
`[0002] Co-pending U.S. application No. 60/408,968 filed
`Sep. 4, 2002 and entitled “Channel Estimation For Com­
`munication Systems.”
`
`BACKGROUND
`[0003] I. Field of Invention
`[0004] The invention generally relates to communication
`systems, and more particularly to channel estimation in
`communication systems with coherent receivers.
`[0005] II. Description of the Related Art
`[0006] In digital communication, information is translated
`into digital data referred to as bits. A transmitter modulates
`an input bit stream into a waveform for transmission over a
`communication channel and a receiver demodulates the
`received waveform back into bits, thereby recovering the
`information. In an ideal communication system, the data
`received would be identical to the data transmitted. How­
`ever, in reality, distortions or noise may be introduced during
`the transmission of data over a communication channel from
`the transmitter to the receiver. If the distortion is significant,
`the information may not be recoverable from the data
`received at the receiver.
`[0007] Channel estimation is one technique used to com­
`pensate for the distortion introduced in data during its
`transmission. Channel characteristics are obtained at the
`receiver and are used to compensate for the distortion during
`demodulation. More particularly, a channel response of the
`communication channel is estimated based on transmissions
`of a known pattern called training sequences. Training
`sequences having constant data are used. For example, the
`data contents of the training data sequence are stored in the
`receiver and is embedded in each data sequence transmitted
`by the transmitter. At the receiver, the channel response can
`then be estimated by processing the training data sequence
`received in a distorted manner and the training data
`sequence stored in undistorted form. This response is
`applied in the demodulation and decoding of the data.
`[0008] Accordingly, channel estimation is important in
`digital communication systems. When implemented, a lim­
`ited number of training data sequence is typically used.
`However, estimates based on a few training data sequences
`often fail to give satisfactory performance. Therefore, there
`is a need for a more reliable, satisfactory and/or efficient
`channel estimation.
`
`SUMMARY
`[0009] Embodiments described allow an improved chan­
`nel estimation. In one embodiment a decoder is configured
`to decode data based on a channel response; and a channel
`estimating module coupled to the decoder is configured to
`
`determine the channel response using at least one training
`symbol, and to update the channel response based on the
`decoded data.
`[0010] The channel estimating module may comprise a
`first channel estimator configured to determine the channel
`response using at least one training symbol; and a second
`channel estimator configured to generate at least one modu­
`lation symbol based on the decoded data and to update the
`channel estimation using the at least one modulation sym­
`bol. The second channel estimator may comprise an encoder
`configured to re-encode the decoded data, an interleaver
`coupled to the encoder and configured to interleave the
`re-encoded data; and a modulation mapping module coupled
`to the interleaver and configured to map the interleaved data
`into a modulation symbol.
`[0011] Alternatively, the channel estimating module may
`comprise a channel estimator configured to determine the
`channel response using at least one training symbol; and a
`symbol generator coupled to the channel estimator, the
`symbol generator configured to generate at least one modu­
`lation symbol based on the decoded data; and wherein the
`channel estimator is configured to update the channel
`response using the at least one modulation symbol. The
`symbol generator may comprise an encoder configured to
`re-encode the decoded data, an interleaver coupled to the
`encoder and configured to interleave the re-encoded data;
`and a modulation mapping module coupled to the interleaver
`and configured to map the interleaved data into a modulation
`symbol.
`[0012] In another aspect, apparatus and method comprises
`means for decoding data based on a channel response; and
`means for determining the channel response using at least
`one training symbol, and to update the channel response
`based on the decoded data. The means for determining the
`channel response may comprise means for estimating the
`channel response using at least one training symbol; means
`for generating at least one modulation symbol based on the
`decoded data; and means for updating the channel estimate
`using the at least one modulation symbol. Also, the means
`for generating the at least one modulation symbol may
`comprise means for re-encoding the decoded data; means for
`interleaving the re-encoded data; and means for mapping the
`interleaved data into a modulation symbol.
`[0013] In a further aspect, apparatus for channel estima­
`tion comprises means for decoding data based on a channel
`response; and a machine readable medium comprising a
`code segment for determining the channel response using at
`least one training symbol, and for updating the channel
`response based on the decoded data. The code segment for
`determining the channel response may comprise code seg­
`ment for estimating the channel response using at least one
`training symbol; code segment for generating at least one
`modulation symbol based on the decoded data; and code
`segment for updating the channel response using the at least
`one modulation symbol. The code segment for generating
`the at least one modulation symbol may comprise code
`segment for re-encoding the decoded data; code segment for
`interleaving the re-encoded data; and code segment for
`mapping the interleaved data into a modulation symbol.
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`BRIEF DESCRIPTION OF THE DRAWINGS
`[0014] Various embodiments will be described in detail
`with reference to the following drawings in which like
`reference numerals refer to like elements, wherein:
`[0015] FIG. 1 shows a transmitter in a communication
`system;
`[0016] FIG. 2 shows a receiver in a communication sys­
`tem;
`[0017] FIG. 3 shows a channel estimating module;
`[0018] FIG. 4 shows another channel estimating module;
`[0019] FIG. 5 shows a training symbol generator that can
`be implemented in a channel estimating module;
`[0020] FIG. 6 shows a method for generating a training
`symbol for channel estimation; and
`[0021] FIG. 7 shows a method for channel estimation.
`
`DETAILED DESCRIPTION
`[0022] Multicarrier communication systems compensate
`for distortions in data transmitted through a multi-path or
`non-ideal communication channel. To counteract or com­
`pensate for distortions that may have been introduced in the
`signal, channel estimates are used in receivers to adjust the
`received signal.
`[0023] Accordingly, the embodiments described provide
`an improved channel estimation in such communication
`systems, by generating training symbols for channel esti­
`mation at a receiver. Generally, data that is decoded at the
`receiver is re-encoded and mapped to modulation symbols.
`The modulation symbols are then used as training symbols
`in the estimation of the channel response. Here, data at the
`receiver may be decoded using an initial channel response
`that is estimated based on training symbol(s) received at the
`receiver from a transmitter. The receiver then generates
`modulation symbols from the decoded data and the modu­
`lation symbols are used as additional training symbols to
`update the initial channel response.
`[0024] In the description below, the embodiments may be
`described as a process which is depicted as a flowchart, a
`flow diagram, a structure diagram, or a block diagram.
`Although a flowchart may describe the operations as a
`sequential process, many of the operations can be performed
`in parallel or concurrently. In addition, the order of the
`operations may be re-arranged. Aprocess is terminated when
`its operations are completed. Aprocess may correspond to a
`method, a function, a procedure, a subroutine, a subprogram,
`etc. When a process corresponds to a function, its termina­
`tion corresponds to a return of the function to a calling
`function or a main function.
`[0025] As disclosed herein, the term “communication
`channel” refers to both wireless and wireline communication
`channels. Examples of wireless communication channels are
`radio, satellite and acoustic communication channel.
`Examples of wireline communication channels include, but
`is not limited to optical, copper, or other conductive wire(s)
`or medium. The term “look-up table” refers to data within a
`database or various storage medium. Storage medium may
`represent one or more devices for storing data, including
`read only memory (ROM), random access memory (RAM),
`
`magnetic disk storage mediums, optical storage mediums,
`flash memory devices and/or other machine readable medi­
`ums for storing information. The term “machine readable
`medium” includes, but is not limited to portable or fixed
`storage devices, optical storage devices, wireless channels
`and various other mediums capable of storing, containing or
`carrying instruction(s) and/or data. Also, for purposes of
`explanation, the embodiments will be described with refer­
`ence to Orthogonal Frequency Division Multiplexing
`(OFDM) systems. However, it will be well understood that
`the invention can be applied to other types of systems that
`require channel estimation.
`[0026] OFDM is an example of a multicarrier communi­
`cation technique that is well known. Generally, OFDM is a
`digital modulation technique that splits a signal into multiple
`sub-signals which are transmitted simultaneously at differ­
`ent frequencies. OFDM uses overlapped orthogonal signals
`to divide a channel into many sub-channels that are trans­
`mitted in parallel. Because OFDM allows high data rate
`transmission over degraded channels, OFDM has been suc­
`cessful in numerous wireless applications, such as in high
`speed local area networks (LANs).
`[0027] Therefore, in OFDM systems, the entire frequency
`bandwidth used for the transmission of signals is subdivided
`into a plurality of frequency subcarriers. By appropriately
`designing modulation symbol periods, adjacent frequency
`subcarriers are respectively orthogonal to each other.
`Orthogonality is a property of a set of functions such that the
`integral of the product of any two members of the set taken
`over the appropriate interval is zero. More specifically,
`orthogonal channels or frequencies are statistically indepen­
`dent and do not interfere with each other. As a result,
`orthogonality allows a receiver to demodulate a selected
`sub-carrier without demodulating other subcarriers that are
`transmitted in parallel through multiplexed communication
`channels. As a result, there is no cross-talk among subcar­
`riers and inter-symbol-interference (ISI) is significantly
`reduced.
`[0028] If there is an accurate estimate of the channel
`characteristics that can be used to adjust the received signal,
`the OFDM system performance can be improved by allow­
`ing for coherent demodulation. Accordingly, training
`sequences known as pilot symbol patterns or training sym­
`bols are transmitted by the transmitter. The training symbols
`are known to the receiver such that the receiver is able to
`perform channel estimation.
`[0029] FIG. 1 shows one embodiment of a transmitter 100
`for use in OFDM systems. Transmitter 100 comprises a
`scrambler 110, an encoder 120, an interleaver 130, a modu­
`lation mapping module 140, an inverse fast fourier trans­
`form (IFFT) module 150, a pulse shaping module 160 and
`an up-converter 170. Transmitter 100 receives a data packet
`and the data rate at which the packet is to be transmitted.
`Scrambler 110 scrambles and encoder 120 encodes the
`received packet. Encoder 120 may be a convolutional
`encoder or some other known encoder that allows error
`correction encoding.
`[0030] The encoded bits are grouped into a block, and
`each block is then interleaved by interleaver 130 and
`mapped to a sequence of modulation symbols by modulation
`mapping module 140. The encoded and interleaved bit
`stream of a selected length is grouped into various numbers
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`of bits depending upon the modulation. Typically, the bit
`stream is grouped into one of 1,2,4 or 6 bit(s) and converted
`into a sequence of complex numbers representing a modu­
`lation symbol in Bi-phase shift keying (BPSK) modulation,
`Quadrature phase shift keying (QPSK) modulation, 16
`Quadrature amplitude modulation (QAM) or 64-QAM
`respectively. BPSK, QPSK and QAM are modulation tech­
`niques well known in the art and will not be discussed in
`detail.
`[0031] Each modulation symbol is then assigned to a
`sub-carrier and inverse fast fourier transformed. This results
`in time-domain samples of a single OFDM symbol. Here, a
`cyclic prefix can be added to each symbol. Pulse shaping is
`then performed by pulse shaping module 160 and the
`symbols are up-converted by up-converter 170 for transmis­
`sion through a communication channel. Here, a program­
`mable pulse shaping may be used.
`[0032] In addition to the modulation symbols, the data
`packet may comprise other information. For example, head­
`ers, leadings and/or preambles may be appended as neces­
`sary to the packet before the scrambling. The header infor­
`mation may comprise the data rate and packet length
`information. The contents of the header are typically not
`scrambled. Also, short and long preambles may be generated
`and added to the data packet. The short preamble comprises
`a repetitive number of short training sequences used for
`synchronization such as timing acquisitions and coarse
`frequency acquisitions. The long preamble comprises a
`repetitive number of long training sequences used for fine
`frequency acquisitions. The long training sequences are also
`the training symbols that may be used for channel estima­
`tion.
`[0033] Various number and choice of training symbols
`may be added to the data packet. In many systems, modu­
`lation symbols are used as the training symbols. Accord­
`ingly, they may be pre-computed and stored such that
`transmission can begin without interleaving and IFFT delay.
`Also, for a more accurate measurement of channel charac­
`teristics, a larger number of training symbols are generally
`required. However, due to a limited bandwidth and more
`particularly to a delay involved in the channel estimation
`process, a lesser number of training symbols are used. In
`LANs, for example, two training symbols are typically
`transmitted and used to estimate the channel response.
`[0034] Existing channel estimation techniques use this
`limited number of training symbols to obtain an estimate of
`the channel response. Therefore, the channel response may
`often be inaccurate and/or unreliable, thereby failing to give
`satisfactory performance. In the described embodiments,
`new training symbols are generated at the receiver, thereby
`allowing a more accurate measurement of the channel
`characteristics.
`[0035] FIG. 2 shows one embodiment of a receiver 200
`that is capable of generating training symbol(s) for use in
`OFDM systems. The receiver 200 comprises a radio fre-
`quency/intermediate frequency (RF/IF) front-end 210, a
`synchronizing module 280, a fast fourier transform (FFT)
`module 220, a de-modulation module 230, a de-interleaver
`240, a decoder 250, a descrambler 260 and a channel
`estimating module 270. It should be noted here that FIG. 2
`shows a simplified block diagram of a receiver. A more
`typical commercial receiver may comprise additional ele­
`
`ments such as a storage medium (not shown) and a processor
`(not shown) to control one or more RF/IF front-end 210,
`synchronizing module 280, FFT module 220, de-modulation
`module 230, de-interleaver 240, decoder 250, descrambler
`260 and channel estimating module 270.
`[0036] RF/IF front end 230 receives data through a com­
`munication channel. The synchronizing module 280 looks
`for or detects a new packet, and tries to acquire time
`synchronization and frequency synchronization. One of sev­
`eral known techniques for detecting a new packet can be
`used. For example, synchronizing module 280 may com­
`prise a time synchronizer to synchronize the signal to the
`beginning of the block and a frequency offset corrector to
`correct the signal for any offset errors that occur between the
`transmitter oscillator and the receiver oscillator. The signal
`is then input to FFT module 220 and converted from time
`domain to frequency domain. FFT is performed after remov­
`ing the cyclic prefix as necessary. Channel estimating mod­
`ule 270 receives the frequency domain signal and provides
`a channel estimate based on the training symbols. The
`frequency domain signal also may be input to a phase locked
`loop (PEL) that provides phase error correction in adjusting
`the received signal. The demodulated signal is de-inter-
`leaved by de-interleaver 240 and decoded by decoder 250.
`Decoder 250 may be a Viterbi decoder. The decoded data is
`then descrambled by descrambler 260 to recover the original
`data information. An additional buffer may also be imple­
`mented to hold the samples while the signal field is being
`decoded.
`[0037] More particularly, when processing a new packet,
`the short preambles are obtained and discarded from the data
`packet before FFT processing. The obtained short preamble
`is used to perform time synchronization. After FFT process­
`ing, the long preambles are obtained and used to perform
`channel estimation for each subcarrier. Initial channel esti-
`mate(s) can be obtained based on the transmitted training
`symbols. Thereafter, training symbols are generated by the
`channel estimating module 270 and can be used in obtaining
`subsequent channel estimates. Abuffer may be implemented
`to store the packet during timing synchronization before
`FFT processing.
`[0038] Channel estimating module 270 performs channel
`estimation based on training symbol(s) and the frequency
`domain signal. For example, after FFT processing, a signal
`for a sub-carrier can be represented in Equation [1] as
`follows,
`Y„=HJC„+N„
`[1]
`[0039] where n denotes the time index (n=0,1,2, . . . ), Xn
`is the transmitted modulation symbol or the training symbol,
`Hn is the channel coefficient and Nn is the noise. Here, if the
`channel is static or varies very slowly, Hn=H for all n where
`H is a constant. The following iterative algorithm in Equa­
`tion [2] is one of many techniques that can be used in the
`channel estimation of each sub-carrier, where Hn is the
`estimated channel response.
`
`[0040] In Equation [2], n=0, 1, 2, 3, . . . and H ^O. The
`channel response is initially estimated using the trans­
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`mitted training symbols and additional training symbols are
`generated to improve the initial channel estimates. For
`example, if two training symbols were transmitted, the
`training symbols Xo and X2 corresponding to n=0 and n=l
`are known for estimating the initial channel estimates Ho and
`Hj. Thereafter, subsequent training symbols are obtained
`and the channel estimates can be updated iteratively using
`Equation [2] to improve the initial channel estimates.
`[0041] Channel estimating module 270 may stop the itera­
`tion after a finite number of iterations, at some appropriate
`n, for example n=16 or 32. In such a case, the value of
`l/(n+l) can be obtained from a database, storage medium or
`look-up table. Also, different iterative algorithms can be
`used. For example, iterative algorithms that are better suited
`for tracking, such as a first order Infinite Impulse Response
`(IIR) filter type or Least mean square (LMS) type algorithm,
`can be used. The recursive equation for the IIR filter type can
`be expressed as follows in Equation [3],
`
`,
`-
`Hn = (1
`
`-
`
`+
`
`(L1
`A J
`
`Pl
`
`[0042] where n=0,1, 2, 3, ... a is the filter coefficient and
`II_, =0. Based on Equation [3], the channel response may
`initially be estimated using the transmitted training symbols
`and additional training symbols may be generated to
`improve the initial channel estimates. For example, if two
`training symbols were transmitted, the training symbols Xo
`and X2 corresponding to n=0 and n=l are known for esti­
`mating the initial channel estimates Ho and Hj.
`[0043] Alternatively, one algorithm can be used for esti­
`mating the initial channel estimates based on the known
`training symbols while another algorithm is used for sub­
`sequent channel estimates. Furthermore, complex division
`can be converted to a simple complex multiplication and two
`real multiplications by using a database, storage medium or
`look-up table for calculating the value of 1/X. Accordingly,
`channel estimating module 300 determines a channel
`response using one or more training symbols.
`[0044] FIG. 3 shows an embodiment of a channel esti­
`mating module 300 comprising a channel estimator 310, a
`symbol generator 320 and a delay buffer 330. Channel
`estimator 310 performs initial channel estimation to obtain
`initial channel estimates based on the transmitted training
`symbol(s). The initial channel estimates are forwarded to
`demodulation module 230. New training symbols are gen­
`erated by symbol generator 320 and forwarded to channel
`estimator 310. The operations of symbol generator 320 will
`be described more in detail later with reference to FIGS. 5
`and 7. Channel estimator 310 then performs subsequent
`channel estimation based on the new and/or additional
`training symbols to update the initial channel estimates.
`Here, channel estimator 310 may use an iterative algorithm,
`such as for example Equation [2] or [3], to update the
`channel estimates. Also, channel estimator 310 may stop the
`update at a finite number of iterations. Delay buffer 330
`temporarily stores the frequency domain signal from FFT
`220 while the new training symbol is being generated.
`[0045] FIG. 4 shows another embodiment of a channel
`estimating module 400 comprising a first channel estimator
`
`410, a second channel estimator 420 and a delay buffer 430.
`First channel estimator 410 performs initial channel estima­
`tion to obtain initial channel estimates based on the trans­
`mitted training symbols. The initial channel estimates are
`forwarded to demodulation module 430. In this embodi­
`ment, second channel estimator 420 generates new training
`symbols and performs subsequent channel estimation based
`on the new and/or additional training symbols to update the
`initial channel estimates. Here, second channel estimator
`420 may also use an iterative algorithm, such as for example
`Equation [2] or [3], to update the channel estimates. Second
`channel estimator 420 may be implemented with a symbol
`generator that is analogous to symbol generator 320 for
`generating new training symbols. Moreover, second channel
`estimator 420 may stop the update at a finite number of
`iterations and delay buffer 430 temporarily stores the fre­
`quency domain signal from FFT 220 while the additional
`training symbol is being generated.
`[0046] In channel estimating modules 300 and 400, the
`training symbol can be generated in a process that is
`analogous to the process of generating the modulation
`symbols at the transmitter. Accordingly, the output from
`decoder 250 is processed into modulation symbols and used
`as new training symbols. FIG. 5 shows one embodiment of
`a symbol generator 500 that can be implemented in symbol
`generator 320 and/or second channel estimator 420 of chan­
`nel estimating modules 300 and 400, respectively. Symbol
`generator 500 comprises an encoder 510, an interleaver 520
`and modulation mapping module 530. The operation will be
`described with reference to a method 600 for generating a
`training symbol.
`[0047] After the received data packet is demodulated,
`de-interleaved and decoded, the decoded data is re-encoded
`by the encoder 510 (610), interleaved by interleaver 520
`(620) and modulated into modulation symbols by modula­
`tion mapping module 530 (630). The modulated symbols
`can then be used as training symbols. Here, due to the delay
`through the de-interleaving, decoding, re-encoding and
`interleaving process, Yn may be stored in delay buffers 330
`and 430 as shown in FIGS. 3 and 4. Therefore, new training
`symbols can be generated at a receiver for use in systems
`such as OFDM systems that need channel estimation.
`[0048] More particularly, FIG. 7 shows a decoding
`method 700 for use in OFDM systems. When a new packet
`is received (710), a determination is made if training sym­
`bols are available (720). If available, the training symbols
`are obtained (730) and a channel response is initially esti­
`mated using the obtained training symbols (740). The data is
`decoded using the channel response (750). If there are no
`more training symbols available (720), additional training
`symbols are generated by re-encoding, interleaving and
`mapping the decoded data to modulation symbols (760­
`780). The channel response is then updated using the modu­
`lation symbol as new training symbols (790) and the data is
`decoded using the updated channel response (750). Here, the
`channel response may be updated using an iterative algo­
`rithm and the updates may be stopped at a finite number of
`iterations.
`[0049] As described, the channel estimates can be
`improved continuously in an iterative manner throughout the
`received data packet using the decoder output. A robust
`channel estimator can significantly improve the performance
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`of a multicarrier system such as OFDM based modulation
`system. Using the decoder output, more reliable estimates of
`the transmitted symbols can be generated and used as
`additional training symbols for the channel estimation in a
`recursive manner. As the decoding progresses through the
`packet, the channel estimates continue to improve with the
`help of already decoded symbols, thereby improving the
`chance of subsequent symbols and the whole packet being
`correctly decoded.
`[0050] Moreover, it should noted here that the elements of
`receiver 200 as shown in FIG. 3 may be rearranged without
`affecting the operation of the receiver. Similarly, elements of
`channel estimating module 300 and/or 400 may also be
`rearranged without affecting the channel estimating opera­
`tion. Furthermore, one or more elements of channel esti­
`mating module 300 and/or 400 may be implemented by
`hardware, software, firmware, middleware, microcode, or
`any combination thereof.
`[0051] When implemented in software, firmware, middle­
`ware or microcode, the program code or code segments to
`perform the necessary tasks may be stored in a storage
`medium (not shown). A processor may perform the neces­
`sary tasks. A code segment may represent a procedure, a
`function, a subprogram, a program, a routine, a subroutine,
`a module, a software package, a class, or any combination
`of instructions, data structures, or program statements. A
`code segment may be coupled to another code segment or a
`hardware circuit by passing and/or receiving information,
`data, arguments, parameters, or memory contents. Informa­
`tion, arguments, parameters, data, etc. may be passed, for­
`warded, or transmitted via any suitable means including
`memory sharing, message passing, token passing, network
`transmission, etc.
`[0052] The foregoing embodiments are merely examples
`and are not to be construed as limiting the invention. The
`present teachings can be readily applied to other types of
`apparatuses, methods and systems. The description of the
`invention is intended to be illustrative, and not to limit the
`scope of the claims. Therefore, many alternatives, modifi­
`cations, and variations will be apparent to those skilled in the
`art without departure from the scope of the invention as set
`forth in the appended claims.
`
`What is claimed is:
`1. Apparatus in a communication system comprising:
`a decoder configured to decode data based on a channel
`response; and
`a channel estimating module coupled to the decoder, the
`channel estimating module configured to determine the
`channel response using at least one training symbol,
`and to update the channel response based on the
`decoded data.
`2. The apparatus of claim 1, wherein the channel estimat­
`ing module comprises:
`a first channel estimator configured to determine the
`channel response using at least one training symbol;
`and
`a second channel estimator configured to generate at least
`one modulation symbol based on the decoded data and
`to update the channel response using the at least one
`modulation symbol.
`
`3. The apparatus of claim 2, wherein the second channel
`estimator comprises:
`an encoder configured to re-encode the decoded data;
`an interleaver coupled to the encoder, the interleaver
`configured to interleave the re-encoded data; and
`a modulation mapping module coupled to the interleaver,
`the modulation mapping module configured to map the
`interleaved data into a modulation symbol.
`4. The apparatus of claim 1, wherein the channel estimat­
`ing module comprises:
`a channel estimator configured to determine the channel
`response using at least one training symbol; and
`a symbol generator coupled to the channel estimator, the
`symbol generator configured to generate at least one
`modulation symbol based on the decoded data; and
`wherein the channel estimator is configured to update
`the channel response using the at least one modulation
`symbol.
`5. The apparatus of claim 4, wherein the symbol generator
`comprises:
`an encoder configured to re-encode the decoded data;
`an interleaver coupled to the encoder, the interleaver
`configured to interleave the re-encoded data; and
`a modulation mapping module coupled to the interleaver,
`the modulation mapping module configured to map the
`interleaved data into a modulation symbol.
`6. The apparatus of claim 1, wherein the channel estimat­
`ing module updates the channel response using an iterative
`algorithm based on the decoded data.
`7. The apparatus of claim 6, wherein the channel estimat­
`ing module stops the update after a finite number of itera­
`tions.
`8. The apparatus of claim 6, further comprising a look-up
`table and wherein the channel estimating module updates the
`channel response using the look-up table.
`9. A method for channel estimation in a communication
`system comprising:
`estimating a channel response using at least one training
`symbol,
`decoding data based on the channel response; and
`updating the channel response based on the decoded data.
`10. The method of claim 9, wherein estimating the chan­
`nel response comprises:
`estimating the channel response using