Bidirectional equalizer with improved equalization efficiency using viterbi decoder information and equalization method using the bidirectional equalizer

A bidirectional equalizer comprising:

• a first equalizer to eliminate inter-symbol interference present in a data sequence transmitted from a transmitter and to generate a first candidate data sequence;
• a first time reverse operator to reverse the order of the transmitted data sequence and to generate a reversed data sequence;
• a second equalizer to eliminate inter-symbol interference present in the reversed data sequence and to generate a second candidate data sequence;
• a first forward Viterbi decoder to receive the first candidate data sequence, and to output a first minimum path metric calculated by a maximum likelihood ML when the first candidate data sequence is decoded for every data symbol;
• a reverse Viterbi decoder to receive the second candidate data sequence, and to output a second minimum path metric calculated by the ML when the second candidate data sequence is decoded for every data symbol;
• a second time reverse operator to reverse the order of the second candidate data sequence and to output the reversed second candidate data sequence;
• and
• an arbitrator to compare the first minimum path metric with the second minimum path metric, and to select and output an output of the first equalizer or an output of the second time reverse operator according to the comparison result.

A bidirectional equalizer comprising:

• a first equalizer to eliminate inter-symbol interference present in a data sequence transmitted from a transmitter and to generate a first candidate data sequence;
• a first time reverse operator to reverse the order of the transmitted data sequence and to generate a reversed data sequence;
• a second equalizer to eliminate inter-symbol interference present in the reversed data sequence and to generate a second candidate data sequence;
• a first forward Viterbi decoder to receive the first candidate data sequence, and to decode and output the first candidate data sequence for every data symbol using a first branch metric calculated by a maximum likelihood ML;
• a reverse Viterbi decoder to receive the second candidate data sequence, and to decode and output the second candidate data sequence using a second branch metric calculated by the ML;
• a second time reverse operator to reverse the order of the second candidate data sequence and output the reversed second candidate data sequence;
• and
• an arbitrator to compare the first branch metric with the second branch metric, and to select and output an output of the first equalizer or an output of the second time reverse operator according to the comparison result.

An equalization method comprising:

• (a) eliminating inter-symbol interference present in a data sequence transmitted from a transmitter and outputting the data sequence;
• (b) reversing the order of the transmitted data sequence and generating a reversed data sequence;
• (c) eliminating interference present in the reversed data sequence and outputting the reversed data sequence;
• (d) decoding and outputting the data sequence output in operation (a) for every data symbol using a first minimum path metric calculated by a maximum likelihood (ML);
• (e) decoding and outputting the data sequence output in operation (c) for every data symbol using a second minimum path metric calculated by the ML;
• (f) reversing the order of the data sequence output in operation (e) and outputting the reversed data sequence;
• (g) comparing the first minimum path metric with the second minimum path metric;
• and
• (h) selecting and outputting a data symbol generated in operation (d) or a data symbol generated in operation (f) according to the comparison result.

An equalization method comprising:

• (a) eliminating inter-symbol interference present in a data sequence transmitted from a transmitter and outputting the data sequence;
• (b) reversing the order of the transmitted data sequence and generating a reversed data sequence;
• (c) eliminating inter-symbol interference present in the reversed data sequence and outputting the reversed data sequence;
• (d) outputting a first minimum path metric calculated by a maximum likelihood (ML) for every data symbol, when decoding the data sequence output in operation (a);
• (e) outputting a second minimum path metric calculated by the ML for every data symbol, when decoding the data sequence output in operation (c);
• (f) reversing the order of the data sequence output in operation (e) and outputting the reversed data sequence;
• (g) comparing the first minimum path metric with the second minimum path metric;
• and
• (h) selecting and outputting a data symbol generated in operation (a) or a data symbol generated in operation (f) according to the comparison result.

An equalization method comprising:

• (a) eliminating inter-symbol interference present in data sequence transmitted from a transmitter and outputting the data sequence;
• (b) reversing the order of the transmitted data sequence and generating a reversed data sequence;
• (c) eliminating inter-symbol interference present in the reversed data sequence and outputting the reversed data sequence;
• (d) outputting a first branch metric calculated by ML for every data symbol, when decoding the data sequence output in operation (a);
• (e) outputting a second branch metric calculated by ML for every data symbol, when decoding the data sequence output in operation (c);
• (f) reversing the order of the data sequence output in operation (e) and outputting the reversed data sequence;
• (g) comparing the first branch metric with the second branch metric;
• and
• (h) selecting and outputting a data symbol generated in operation (a) or a data symbol generated in operation (f) according to the comparison result.