Differential Acquisition of m-Sequences using Recursive Soft Sequential Estimation
Differential Acquisition of m-Sequences using Recursive Soft Sequential Estimation
In this contribution a novel sequential estimation method is proposed for the acquisition of $m$-sequences. This sequential estimation method exploits the principle of iterative soft-in-soft-out (SISO) decoding for enhancing the acquisition performance, and that of differential pre-processing for the sake of achieving an enhanced acquisition performance, when communicating over various communication environments. Hence the advocated acquisition arrangement is referred to as the Differential Recursive Soft Sequential Estimation (DRSSE) acquisition scheme. The DRSSE acquisition scheme exhibits a low complexity, which is similar to that of an $m$-sequence generator, while achieving an acquisition time that is linearly dependent on the number of stages in the $m$-sequence generator. A low acquisition time is achieved with the advent of the property that the proposed DRSSE scheme is capable of determining the real-time reliabilities associated with the decision concerning a set of, say $S$, consecutive chips. This set of consecutive chips constitutes the sufficient initial condition for enabling the local $m$-sequence generator to produce a synchronized local despreading $m$-sequence replica. Owing to these attractive characteristics, the DRSSE acquisition scheme constitutes a promising initial synchronization scheme for acquisition of long $m$-sequences, when communicating over various propagation environments.
Initial synchronization, differential detection, pseudonoise signals, $m$-sequence, acquisition, sequential estimation, SISO decoding, recursive decoding, spread-spectrum signals.
128-136
Yang, L-L.
ae425648-d9a3-4b7d-8abd-b3cfea375bc7
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
January 2005
Yang, L-L.
ae425648-d9a3-4b7d-8abd-b3cfea375bc7
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Yang, L-L. and Hanzo, L.
(2005)
Differential Acquisition of m-Sequences using Recursive Soft Sequential Estimation.
IEEE Transactions on Wireless Communications, 4 (1), .
Abstract
In this contribution a novel sequential estimation method is proposed for the acquisition of $m$-sequences. This sequential estimation method exploits the principle of iterative soft-in-soft-out (SISO) decoding for enhancing the acquisition performance, and that of differential pre-processing for the sake of achieving an enhanced acquisition performance, when communicating over various communication environments. Hence the advocated acquisition arrangement is referred to as the Differential Recursive Soft Sequential Estimation (DRSSE) acquisition scheme. The DRSSE acquisition scheme exhibits a low complexity, which is similar to that of an $m$-sequence generator, while achieving an acquisition time that is linearly dependent on the number of stages in the $m$-sequence generator. A low acquisition time is achieved with the advent of the property that the proposed DRSSE scheme is capable of determining the real-time reliabilities associated with the decision concerning a set of, say $S$, consecutive chips. This set of consecutive chips constitutes the sufficient initial condition for enabling the local $m$-sequence generator to produce a synchronized local despreading $m$-sequence replica. Owing to these attractive characteristics, the DRSSE acquisition scheme constitutes a promising initial synchronization scheme for acquisition of long $m$-sequences, when communicating over various propagation environments.
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Published date: January 2005
Keywords:
Initial synchronization, differential detection, pseudonoise signals, $m$-sequence, acquisition, sequential estimation, SISO decoding, recursive decoding, spread-spectrum signals.
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 261274
URI: http://eprints.soton.ac.uk/id/eprint/261274
PURE UUID: 5e079e36-9c63-4b73-8435-1e057e9ac9b6
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Date deposited: 29 Sep 2005
Last modified: 18 Mar 2024 02:49
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Contributors
Author:
L-L. Yang
Author:
L. Hanzo
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