Error detection/correction and fault detection/recovery – Pulse or data error handling – Digital data error correction
Reexamination Certificate
1999-10-26
2003-12-09
Decady, Albert (Department: 2133)
Error detection/correction and fault detection/recovery
Pulse or data error handling
Digital data error correction
C714S774000
Reexamination Certificate
active
06662337
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to a transmission of digital signals, e.g. in a digital radio communication system.
BACKGROUND OF THE INVENTION
Iterative decoding algorithms have become a vital field of research in digital communications. The first discovered and still most popular encoding scheme suited for iterative decoding is the parallel concatenation of two recursive systematic convolutional codes, also referred to as ‘Turbo Codes’. The underlying ‘Turbo Principle’ is applicable more generally to other algorithms used in modern digital communications, and in the past few years, other applications of the “Turbo Principle” have been found.
Channel coding is used to make the transmitted digital information signal more robust against noise. For this the information bit sequence is encoded at the transmitter by a channel encoder and decoded at the receiver by a channel decoder. In the encoder redundant information is added to the information bit sequence in order to facilitate error correction in the decoder. For example, in a systematic channel encoding scheme the redundant information is added to the information bit sequence as additional, inserted “coded” bits. In a non-systematic encoding scheme the outgoing bits are all coded bits, and there are no longer any “naked” information bits. The number of incoming bits (information bits) at the encoder is smaller than the number of outgoing bits (information bits plus inserted coded bits, or all coded bits). The ratio of incoming/outgoing bits is called the “code rate R” (typically R=1:2).
Recent improvements using the “Turbo Principle” have shown that, in digital communication systems involving a plurality of users in wireless communication with a receiver, an improvement in the quality of the decoded signal can be achieved by applying iterative decoding steps to the received data. In particular, “Iterative Equalization and Decoding in Mobile Communication Systems' by Baunch, Khorram and Hagenauer, EPMCC'97, pp 307-312, October 1997, Bonn, Germany, discusses the application of the Turbo principle to iterative decoding of coded data transmitted over a mobile radio channel.
In order to be suitable for iterative decoding, a transmitted signal must be encoded by at least two concatenated codes, either serially or parallelly concatenated.
FIG. 1
shows a serially concatenated coding scheme: the transmission is done on a block-by-block basis. The binary signal from the digital source is encoded firstly by an outer encoder and is then passed through an interleaver, which changes the order of the incoming bit symbols to make the signal appear more random to the following processing stages. After the interleaver, the signal is encoded a second time by an ‘inner encoder’. Correspondingly, at the receiver the signal is first decoded by the inner decoder in a first decoding step, deinterleaved, and decoded by the outer decoder in a second decoding step. From the outer decoder soft decision values are fed back as additional a priori input to the inner decoder. The soft decision values provide information on the reliability of the hard decision values. In a first iteration the decoding step is repeated and the soft decision values are used as input values for the first and second decoder.
The iterative decoding of a particular transmitted sequence is stopped with an arbitrary termination criterion, e.g. after a fixed number of iterations, or until a certain bit error rate is reached. It should be noted that the a priori soft value input to the inner decoder is set to zero for the very first decoding of the transmitted bit sequence (‘Oth iteration’).
The inner and outer binary codes can be of any type: systematic, or non-systematic, block or convolutional codes. Simple mapping (e.g. antipodal or binary phase shift keying) is performed in the transmitter (after the inner encoder) and simple demapping is performed in the receiver (after the inner decoder) although for clarity this is not shown in FIG.
1
. Likewise,
FIG. 1
illustrates a single user scenario, although application of appropriate multiplexing provides a suitable multi user system.
At the receiver the two decoders are soft-in/soft-out decoders (SISO-decoder). A soft value represents the reliability on the bit decision of the respective bit symbol (whether 0 or 1 was sent). A soft-in decoder accepts soft reliability values for the incoming bit symbols. A soft-out decoder provides soft reliability output values on the outgoing bit symbols. The soft-out reliability values are usually more accurate than the soft-in reliability values since they are improved during the decoding process, based on the redundant information added with each encoding step at the transmitter. The best performance is achieved by a SISO-decoder which provides the A Posteriori Probability calculator (APP), tailored to the respective channel code. Several faster, but sub-optimal algorithms exist, e.g. the SOVA (soft output Viterbi algorithm).
In multilevel modulation, M bits (bit symbols) are grouped together at the transmitter to form one ‘mapped symbol’ (also briefly referred to as ‘symbol’). This symbol can be mapped onto a real or a complex signal space (i.e. real axis, or complex plane). The mapping operation simply associates the unmapped symbol (M bits, value from 0, . . . , 2
m
−1) with a discrete amplitude level for Pulse Amplitude Modulation (PAM), a discrete phase level for Phase Shift Keying (PSK), any discrete signal point in the complex plane for quadrature Amplitude Modulation (QAM) or any combination of PAM, QAM, PSK. The mapping can be of any type.
At the receiver the incoming symbols are noise affected. The hard decision demapping operation associates the incoming symbol with the closest signal point in the signal space (signal point with minimum Euclidian distance in real or complex signal space) and takes for example the respective Gray-encoded codeword as the hard decision values (O,1) for the M bits per mapped symbol.
However, if multilevel modulation is used in conjunction with channel coding and soft channel decoding (i.e. a soft input decoder) the demapping operation preferably calculates soft reliability values as inputs to the channel decoder. For simplicity, the term “multilevel modulation” is used when referring to PAM, PSK or QAM modulation, meaning ‘multi-amplitude level’ for PAM, “multi phase level” for PSK, and “multi signal points” for QAM.
In one prior proposal, apparatus for iteratively decoding a signal has a demapper which has a first input for receiving the signal and an output for generating a demapped signal; and a decoder which has an input for receiving the demapped signal and an output for generating a decoded signal, the demapper having a second input for receiving the decoded signal.
Each user in a mobile communication system may have a different Quality of Service (QoS) requirement, i.e. different BER and latency constraints due to differing communication services. For example: voice communication has the lowest BER requirements (i.e. can tolerate many bit errors) with the highest latency constraints (i.e. cannot tolerate long delays in two way conversation); visual communication has a higher BER requirement and high latency constraints; data communication (e.g. wireless Internet web-browsing) has the highest BER requirements and the lowest latency constraints. Each user communicates with the base station with a different signal quality (i.e. SNR), multipath propagation and fading due to differing distance from the base station, propagation environment and, if mobile, speed.
The mapping operation itself does not add redundancy (in contrast to the inner encoder in classic serially concatenated encoding schemes) to the signal, but links bits together by grouping several bit symbols to form one mapped symbol.
The demapper is a soft demapping device that has been modified in order to accept a priori information obtained from the decoder. The decoder is a channel decoder and can be any SISO-decoder (optimal APP, or other sub-optima
Agere Systems Inc.
Torres Joseph D.
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