US 20080212657 A1 Abstract Techniques to iteratively detect and decode data transmitted in a wireless (e.g., MIMO-OFDM) communication system. The iterative detection and decoding is performed by iteratively passing soft (multi-bit) “a priori” information between a detector and a decoder. The detector receives modulation symbols, performs a detection function that is complementary to the symbol mapping performed at the transmitter, and provides soft-decision symbols for transmitted coded bits. “Extrinsic information” in the soft-decision symbols is then decoded by the decoder to provide its extrinsic information, which comprises the a priori information used by the detector in the detection process. The detection and decoding may be iterated a number of times. The soft-decision symbols and the a priori information may be represented using log-likelihood ratios (LLRs). Techniques are provided to reduce the computational complexity associated with deriving the LLRs, including interference nulling to isolate each transmitted signal and “dual-maxima” approximation.
Claims(22) 1. A method for transmitting data in a wireless communication system, comprising:
receiving channel state information (CSI) indicative of one or more characteristics of a communication channel used for data transmission, wherein the CSI is derived at one or more receivers based on iterative detection and decoding of a plurality of modulated signals as received at the one or more receivers, iterative detection and decoding comprises: deriving first a priori information for the coded data based on the received modulation signals and second a priori information for the coded data; and decoding the first a priori information to derive the second a priori information, the second a priori information comprises decoded information for the coded data subtracted by the first a priori information. 2. The method of interleaving the coded data based on one or more interleaving schemes, and wherein the interleaved data is modulated. 3. A transmitter in a wireless communication system, comprising:
a TX data processor that processes data based on one or more coding schemes to provide coded data, wherein the coding scheme is selected based on channel state information (CSI) derived at a receiver via iterative detection and decoding of a plurality of received modulated signals, iterative detection and decoding comprising: deriving first a priori information for the coded data based on the received modulation signals and second a priori information for the coded data; and decoding the first a priori information to derive the second a priori information, the second a priori information comprises decoded information for the coded data subtracted by the first a priori information. 4. The transmitter of 5. The transmitter of 6. The transmitter of 7. The transmitter of 8. The transmitter of 11. The transmitter of a controller that receives the CSI and selects the coding and modulation schemes based on the received CSI. 10. The transmitter of a controller receives the CSI and selects the coding, interleaving, and modulation schemes based on the received CSI. 11. The transmitter of 12. The transmitter of 13. The transmitter of 14. The transmitter of 15. The transmitter of 16. The transmitter of 17. The transmitter of 18. The transmitter of 19. The transmitter of 20. The transmitter of 21. A transmitter apparatus in a wireless communication system, comprising:
means for processing data based on one or more coding schemes to provide coded data; means for selecting the coding scheme based on channel state information (CSI) derived at a receiver via iterative detection and decoding of a plurality of received modulated signals, iterative detection and decoding comprising: means for deriving first a priori information for the coded data based on the received modulation signals and second a priori information for the coded data; and means for decoding the first a priori information to derive the second a priori information, the second a priori information comprises decoded information for the coded data subtracted by the first a priori information. 22. The transmitter apparatus of means for interleaving the coded data based on one or more interleaving schemes to provide a plurality of coded and interleaved data streams, and wherein the interleaved data is modulated. Description The present application for patent claims priority to Provisional application Ser. No. 10/005,104 entitled “ITERATIVE DETECTION AND DECODING FOR A MIMO-OFDM SYSTEM” filed Dec. 3, 2001, and assigned to the assignee hereof and hereby expressly incorporated by reference herein. 1. Field The present invention relates generally to data communication, and more specifically to techniques for performing iterative detection and decoding for a MIMO-OFDM communication system. 2. Background A multiple-input multiple-output (MIMO) communication system employs multiple (N A wideband MIMO system typically experiences frequency selective fading, i.e., different amounts of attenuation across the system bandwidth. This frequency selective fading causes inter-symbol interference (ISI), which is a phenomenon whereby each symbol in a received signal acts as distortion to subsequent symbols in the received signal. This distortion degrades performance by impacting the ability to correctly detect the received symbols. As such, ISI is a non-negligible noise component that may have a large impact on the overall signal-to-noise-and-interference ratio (SNR) for systems designed to operate at high SNR levels, such as MIMO systems. In such systems, equalization may be used at the receivers to combat ISI. However, the computational complexity required to perform equalization is typically significant or prohibitive for most applications. Orthogonal frequency division multiplexing (OFDM) may be used to combat ISI, and achieves this without the use of computationally intensive equalization. An OFDM system effectively partitions the system bandwidth into a number of (N A MIMO system may thus advantageously employ OFDM to combat ISI. The frequency subchannels of the MIMO-OFDM system may experience different channel conditions (e.g., different fading and multipath effects) and may achieve different SNRs. Moreover, the channel conditions may vary over time. Consequently, the supported data rates may vary from frequency subchannel to frequency subchannel and from spatial subchannel to spatial subchannel, and may further vary with time. To achieve high performance, it is necessary to properly code and modulate the data at the transmitter (e.g., based on the determined channel conditions) and to properly detect and decode the received signals at the receiver. There is therefore a need in the art for techniques to detect and decode signals that may have been (flexibly) coded and modulated based on one or more coding and modulation schemes, e.g., as determined by the channel conditions. Aspects of the invention provide techniques to iteratively detect and decode data transmitted in a wireless (e.g., MIMO-OFDM) communication system. The iterative detection and decoding exploits the error correction capabilities of the channel code to provide improved performance. This is achieved by iteratively passing soft (multi-bit) “a priori” information between a soft-input soft-output detector and a soft-input soft-output decoder. The detector receives modulation symbols previously generated at a transmitter system based on one or more coding and modulation schemes, performs a detection function that is complementary to the symbol mapping performed at the transmitter system, and provides soft-decision symbols for transmitted coded bits. Extrinsic information in the soft-decision symbols (which comprises the a priori information for the decoder, as described below) is then decoded by the decoder based on one or more decoding schemes complementary to the one or more coding schemes used at the transmitter system. The decoder further provides its extrinsic information (which comprises the a priori information for the detector) that is then used by the detector in the detection process. The detection and decoding may be iterated a number of times. During the iterative detection and decoding process, the reliability of the bit decisions is improved with each iteration. The iterative detection and decoding process described herein may be used to combat frequency selective fading as well as flat fading. Moreover, the iterative detection and decoding process may be flexibly used with various types of coding schemes (e.g., serial and parallel concatenated convolutional codes) and with various modulation schemes (e.g., M-PSK and M-QAM). The a priori information passed between the detector and decoder and the soft-decision symbols may be represented using log-likelihood ratios (LLRs). Techniques are provided herein to reduce the computational complexity associated with deriving the LLRs. Such techniques include the use of interference nulling to isolate each transmitted signal by removing the other interferers and the use of a “dual-maxima” or some other approximation to compute the LLRs, which are described below. Various aspects and embodiments of the invention are described in further detail below. The invention further provides methods, receiver units, transmitter units, receiver systems, transmitter systems, systems, and other apparatuses and elements that implement various aspects, embodiments, and features of the invention, as described in further detail below. The features, nature, and advantages of the present invention will become more apparent from the detailed description set forth below when taken in conjunction with the drawings in which like reference characters identify correspondingly throughout and wherein: The iterative detection and decoding techniques described herein may be used for various wireless communication systems. For clarity, various aspects and embodiments of the invention are described specifically for multiple-input multiple output communication system that implements orthogonal frequency division multiplexing (i.e., a MIMO-OFDM system). As noted above, a MIMO system employs N At transmitter system The coded data is then provided to a modulator In a specific embodiment, the processing by modulator Each transmitter At receiver system A detector/decoder Controllers In the specific embodiment shown in Channel interleaver Demultiplexer In the specific embodiment shown in Within each OFDM modulator, symbol mapping element If conventional non-iterative symbol de-mapping and decoding are performed at the receiver system, then Gray mapping may be preferably used for the symbol mapping since it may provide better performance in terms of bit error rate (BER). With Gray mapping, the neighboring points in the signal constellation (in both the horizontal and vertical directions) differ by only one out of the q bit positions. Gray mapping reduces the number of bit errors for more likely error events, which correspond to a received modulation symbol being mapped to a location near the correct location, in which case only one coded bit would be received in error. However, if iterative detection and decoding are performed as described below, it can be shown that non-Gray mapping outperforms Gray mapping. This is true due to the fact that independence between the coded bits enhances independence between the detection and decoding processes, which then provides improved performance when iterative detection and decoding are performed. Thus, each symbol mapping element IFFT Transmitter unit In the specific embodiment shown in Each encoder In the specific embodiment shown in Other designs for the transmitter unit may also be implemented and are within the scope of the invention. For example, the coding and modulation may be separately performed for each subset of transmit antennas, each transmission channel, or each group of transmission channels. The implementation of encoders The coding and modulation for MIMO systems with and without OFDM arc described in further detail in U.S. patent application Ser. Nos. 09/826,481 and 09/956,449, both entitled “Method and Apparatus for Utilizing Channel State Information in a Wireless Communication System,” respectively filed Mar. 23, 2001 and Sep. 18, 2001; U.S. patent application Ser. No. 09/854,235, entitled “Method and Apparatus for Processing Data in a Multiple-Input Multiple-Output (MIMO) Communication System Utilizing Channel State Information,” filed May 11, 2001; U.S. patent application Ser. No. 09/776,075, entitled “Coding Scheme for a Wireless Communication System,” filed Feb. 1, 2001; and U.S. patent application Ser. No. 09/993,087, entitled “Multiple-Access Multiple-Input Multiple-Output (MIMO) Communication System,” filed Nov. 6, 2001. These applications are all assigned to the assignee of the present application and incorporated herein by reference. Still other coding and modulation schemes may also be used, and this is within the scope of the invention. An example OFDM system is described in U.S. patent application Ser. No. 09/532,492, entitled “High Efficiency, High Performance Communication System Employing Multi-Carrier Modulation,” filed Mar. 30, 2000, assigned to the assignee of the present invention and incorporated herein by reference. OFDM is also described by John A. C. Bingham in a paper entitled “Multicarrier Modulation for Data Transmission: An Idea Whose Time Has Come,” IEEE Communications Magazine, May 1990, which is incorporated herein by reference. Various types of encoder may be used to code data prior to transmission. For example, the encoder may implement any one of the following (1) a serial concatenated convolutional code (SCCC), (2) a parallel concatenated convolutional code (PCCC), (3) a simple convolutional code, (4) a concatenated code comprised of a block code and a convolutional code, and so on. Concatenated convolutional codes are also referred to as Turbo codes. Code interleaver The LCS code interleaving scheme is described in further detail in commonly assigned U.S. patent application Ser. No. 09/205,511, entitled “Turbo Code Interleaver Using Linear Congruential Sequences,” filed Dec. 4, 1998, and in a cdma2000 document entitled “C.S0002-A-1 Physical Layer Standard for cdma2000 Spread Spectrum Systems,” both of which are incorporated herein by reference. Other code interleavers may also be used and are within the scope of the invention. For example, a random interleaver or a symmetrical-random (S-random) interleaver may also be used instead of the LCS interleaver described above. Inner convolutional encoder As shown in The parity bits b The information bits (which are also referred to as the systematic bits), and the punctured parity bits from convolutional encoders In the embodiment shown in
Encoder Encoder After all N It can be shown analytically and via computer simulations that SCCCs provide better performance than PCCCs in additive white Gaussian noise (AWGN) channels at medium to high SNR levels, which is typically the desired operating region for MIMO systems. While the BER for PCCCs asymptotically reaches an error floor, this floor is absent or much lower for SCCCs. PCCCs outperform SCCCs in the high BER region, and may be more suitably used when the system loads approach the capacity limits of the channel at low SNRs. Both PCCCs and SCCCs may be implemented using relatively simple constituent codes (e.g., having constraint lengths of 3 to 16), such as the one shown in Referring back to Various interleaving schemes may be used for the channel interleaver. In one interleaving scheme, the coded bits for each packet are written (linearly) to rows of an array. The bits in each row may then be permutated (i.e., rearranged) based on (1) a bit-reversal rule, (2) a linear congruential sequence (such as the one described above for the code interleaver), (3) a randomly generated pattern, or (4) a permutation pattern generated in some other manner. The rows are also permutated in accordance with a particular row permutation pattern. The permutated coded bits are then retrieved from each column of the array and provided to the next processing element. Other channel interleaving schemes may also be used and this is within the scope of the invention. In an embodiment, the channel interleaving is performed separately for each independently coded data stream. For the PCCCs, the information bits and the tail and parity bits for each packet may also be channel interleaved separately. For example, the information bits b The interleaving interval may be selected to provide the desired temporal, frequency, and/or spatial diversity, or any combination thereof. For example, the coded bits for a particular time period (e.g., 10 msec, 20 msec, and so on) and for a particular combination of transmission channels may be interleaved. The channel interleaving may be performed for each transmit antenna, or across each group of transmit antennas or across all transmit antennas to provide spatial diversity. The channel interleaving may also be performed for each frequency subchannel, or across each group of frequency subchannels or across all frequency subchannels to provide frequency diversity. The channel interleaving may also be performed across each group of one or more frequency subchannels of each group of one or more transmit antennas such that the coded bits from one data stream may be distributed over one or more frequency subchannels of one or more transmit antennas to provide a combination of temporal, frequency, and spatial diversity. The channel interleaving may also be performed across all frequency subchannels of all transmit antennas. The signals transmitted from the N In the specific embodiment shown in In the embodiment shown in Detector For each transmission symbol period, detector Decoder To briefly summarize, the output of the detection process may be expressed as: where -
- L(b
_{k}) represents the soft-decision symbol for the k-th coded bit b_{k}; - L
_{a}(b_{k}) represents the detector a priori information for the k-th coded bit, which is provided by the decoder; and - L
_{e}(b_{k}) represents the extrinsic information for the k-th coded bit provided by the detector to the decoder. The output of the decoding process may similarly be expressed as:
- L(b
where -
- L
^{D}(b_{k}) represents the a posteriori information for the k-th coded bit provided by the decoder; - L
_{a}^{D}(b_{k}) represents the decoder a priori information for the k-th coded bit provided by the detector; and - L
_{e}^{D}(b_{k}) represents the extrinsic information for the k-th coded bit provided by the decoder to the detector.
- L
As shown in The detection and decoding process may be iterated a number of times. During the iterative detection and decoding process, the reliability of the bit decisions is improved with each iteration. The iterative detection and decoding process described herein may be used to combat frequency selective fading (e.g., by using OFDM with cyclic prefix) as well as flat fading (without any modifications). Moreover, the iterative detection and decoding process may be flexibly used with various types of coding and modulation schemes, including the serial and parallel concatenated convolutional codes as described above. In In an embodiment, only the channel information and extrinsic information are passed from the detector to the decoder where, after parallel-to-serial conversion and channel deinterleaving, they are used as a priori information in the decoding process. For simplicity, the channel information and extrinsic information are collectively referred to as simply the extrinsic information. Ideally, the decoder a priori information should be provided by an independent source. However, since such a source is not available, an independent source may be mimicked by minimizing the correlation between the decoder a priori information (i.e., the detector output) and previous decisions made by the decoder (i.e., the detector a priori information). This is achieved by subtracting the detector a priori information from the soft-decision symbols derived by the detector, using summers The modulation symbol received from the output of the OFDM demodulator coupled to the m-th receive antenna for the l-th frequency subchannel at time index j (i.e., transmission symbol period j) may be expressed as:
where -
- h
_{n,m,l}(j) is the channel response between the n-th transmit antenna and the m-th receive antenna for the l-th frequency subchannel at time index i; - c
_{n,l}(j) is the modulation symbol transmitted on the l-th frequency subchannel of the n-th transmit antenna; and - n
_{m,l}(j) is a sample function of a zero-mean, temporally and spatially white Gaussian noise process. To simplify notation, the time index j is dropped in the following derivations.
- h
Equation (3) may be expressed in matrix form, as follows: _{l} = H _{l} c _{l} + n _{l}, for l=0, 1, 2, . . . , N_{F}−1, Eq (4)where -
- r
_{l}=[r_{1,l}r_{2,l }. . . r_{N}_{ R }_{,l}]^{T }is a vector of N_{R }modulation symbols received from the N_{R }receive antennas for the l-th frequency subchannel; - H
_{l }is the N_{R}×N_{T }matrix of channel gains {h_{n,m,l}} for the l-th frequency subchannel, where h_{n,m,l }denotes the complex channel gain between the n-th transmit antenna and the m-th receive antenna for the l-th frequency subchannel; - c
_{l}=[C_{1,l}, c_{2,l }. . . c_{N}_{ T }_{,l}]^{T }is a vector of N_{T }modulation symbols transmitted from the N_{T }transmit antennas for the l-th frequency subchannel; - n
_{l}=[n_{1,l }n_{2,l }. . . n_{N}_{ R }_{,l}]^{T }is a vector of N_{R }noise samples for the N_{R }receive antennas for the l-th frequency subchannel; and - “
^{T}” denotes the transposition.
- r
The modulation symbols received from all N _{0} ^{T} r _{1} ^{T } . . . r _{N} _{ F } _{−1}]^{T} Eq (5)The N As noted above, each modulation symbol is formed by a respective group of q coded bits. The N where the coded bits transmitted from the n-th transmit antenna may be expressed as _{n} =[b _{n,0,1 } . . . b _{n,0,q } b _{n,1,1 } . . . b _{n,1,q } . . . b _{n,N} _{ F } _{−1,1 } . . . b _{n,N} _{ F } _{−1,q}]^{T}.The detector computes the LLRs for each transmitted coded bit b
As shown in equation (8), the LLR for a given coded bit, L(b The following equalities may be expressed:
where f(·) represents the symbol mapping from the coded bits
In the first iteration of the iterative detection and decoding process, it is assumed that all points in the signal constellation are equally likely. Hence, the term Pr{
where a change in notation of variables is made (i.e., p={n,l,i}) in the term to the right of the equality to simplify notation. The received modulation symbols r
where σ Substituting equations (11) and (12) into equation (10), the LLR for the k-th coded bit may then be expressed as:
where k={n,l,i}. Equation (13) may further be decomposed as follows:
As shown in equation (14), the LLR for the k-th coded bit, L(b
The term L
where C is a constant and
Hence, the detector extrinsic information, L
Since the detector a priori information, L It can be seen from equations (13) and (17) that the computational complexity to derive the LLRs for the coded bits grows exponentially with the number of frequency subchannels (N Without loss of generality, the signal from transmit antenna ^{(1)}=Θ _{1} ^{(1)} r _{l}=Θ _{l} ^{(1)} H _{l} c _{l} + Θ _{l} ^{(1)} n _{l} = {tilde over (H)} _{l} ^{(1)} c _{1,l} + ñ _{l} ^{(1)}, for l=0, 1, . . . , N_{F}−1. Eq (18)As shown in equation (18), the components from transmit antennas The nulling matrices, _{l} ^{(1)}=0 where 0 is the all-zero matrix, and where Derivation of the nulling matrices for a MIMO system is described in further detail by Vahid Tarokh et al in a paper entitled “Combined Array Processing and Space-Time Coding,” IEEE Transactions on Information Theory, Vol. 45, No. 4, May 1999, which is incorporated herein by reference. After nulling the interference on the desired signal due to the signals from the other (N
where After the interference nulling, the LLR computation is simplified since only the desired signal from one transmit antenna is considered at a time. Equation (19) may be expressed in a form similar to equation (14), as follows:
where k=1, 2, . . . , N As shown in equation (20), instead of calculating (N The product of the a priori probabilities, ΠPr{b
The detector extrinsic information, L
The detection with interference nulling described above may be repeated N The reduced computational complexity for deriving the LLRs for the coded bits is achieved with a corresponding decrease in diversity, since the desired signal is received with a diversity of order (N The dual-maxima approximation may also be used to reduce the computational complexity associated with deriving the LLRs for the coded bits. As shown in equations (20) and (22), the LLR for each coded bit is computed as the logarithm of the ratio of two summations. Each summation is performed over a number of elements, with each such element being composed of products of exponential terms, exp(β
For simplicity, the following may be defined:
Applying the approximation shown in equation (23) for the sum of exponents to equation (24), the following can be expressed:
The approximation shown in equation (25) is often referred to as the dual-maxima approximation. The dual-maxima approximation may be used to simplify the computation for the LLRs for the coded bits. Specifically, for equation (22), the logarithm of the ratio of two summations may first be decomposed as follows:
Next, instead of summing over the individual elements for all possible values of the coded bits for the modulation symbols By using approximations based on the dual-maxima approximation, the computational complexity can be made to increase linearly in the number of coded bits per modulation symbol, q, instead of exponentially. Simulation results have shown that the performance degradation due to the use of such approximations is negligible over the range of SNRs where the use of high-order modulations is justified. Other approximations and simplifications may also be used to reduce the number of complex additions and multiplications needed to compute the LLRs for the coded bits, and this is within the scope of the invention. Other simplifications that may be used for computing LLRs are described by Andrew J. Viterbi in a paper entitled “An Intuitive Justification and a Simplified Implementation of the MAP Decoder for Convolutional Codes,” IEEE Journal on Selected Areas in Communications, Vol. 16, No. 2, February 1998, pp. 260-264, and by Patrick Robertson et al. in a paper entitled “A Comparison of Optimal and Sub-Optimal MAP Decoding Algorithms Operating in the Log Domain,” IEEE International Conference on Communication, 1995, pp. 1009-1012, both of which are incorporated herein by reference. These various simplification techniques typically perform computations in the log-domain, where division becomes subtraction and multiplication becomes addition. The signals transmitted from the N In the embodiment shown in Detector Decoder Similar to that described for The N Detector/decoder Within detector _{l} ^{(1)} = Θ _{l} ^{(1)} r _{l}=Θ _{l} ^{(1)} H _{l} c _{l}+Θ _{l} ^{(1)} n _{l}.Interference nuller The vectors The decoded bits from decoder block ^{(2)} = r ^{(1)} − î ^{(1)}. Eq (27)Each subsequent stage performs the detection and decoding in a similar manner as described above for the first stage to provide the decoded bits for the assigned transmit antenna. However, the input vectors, Pre-decoding interference estimation and cancellation may also be used, and this is within the scope of the invention. In this case, a hard decision may be made on the LLR outputs from the detector. The hard decision may then be re-modulated and multiplied with the estimated channel response to obtain pre-decoding interference estimates (which are typically not as reliable as post-decoding interference estimates). The pre-decoding interference estimates may then be canceled from the received modulation symbols. Decoders The coded bits (or more specifically, the a priori LLRs for the decoder, L MAP decoder The decoding by inner and outer MAP decoders MAP decoders The coded bits (or more specifically, the a priori LLRs for the decoder, L MAP decoder MAP decoder P/S converter The decoding by MAP decoders In general, the number of iterations in both the decoder and the iterative detector-decoder can be fixed or variable (i.e., adaptive). In the latter case, the stop criterion may be triggered when (1) the BER converges or reaches an acceptable level, (2) the worse or average LLR reaches a particular confidence level, or (3) some other criterion is met. For each frequency subchannel, channel simulator If the remodulated symbol corresponding to the n-th transmit antenna is expressed as {tilde over (c)}
The N The successive cancellation receiver processing technique is described in further detail in the aforementioned U.S. patent application Ser. Nos. 09/854,235 and [Attorney Docket No. 010254], and by P. W. Wolniansky et al. in a paper entitled “V-BLAST: An Architecture for Achieving Very High Data Rates over the Rich-Scattering Wireless Channel”, Proc. ISSSE-98, Pisa, Italy, which is incorporated herein by reference. In Controller At transmitter system The iterative detection and decoding techniques have been described specifically for serial and parallel concatenated convolutional codes. These techniques may also be used with other codes, such as convolutional codes, block codes, concatenated codes of different types (e.g., a convolutional code with a block code), and so on. Furthermore, the iterative detection and decoding techniques have been described specifically for a MIMO-OFDM system. These techniques may also be used for a MIMO system that does not implement OFDM, an OFDM system that does not utilize MIMO, or some other wireless communication systems (e.g., a wireless LAN system). The iterative detection and decoding techniques may be implemented in various units in a wireless communication system, such as in a terminal, a base station, an access point, and so on. The iterative detection and decoding techniques described herein may be implemented by various means. For example, these techniques may be implemented in hardware, software, or a combination thereof. For a hardware implementation, the elements used to perform the iterative detection and decoding (e.g., detector For a software implementation, the iterative detection and decoding may be performed with modules (e.g., procedures, functions, and so on) that perform the computations and functions described herein. The software codes may be stored in a memory unit (e.g., memory The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein. Referenced by
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