
doi: 10.1002/dac.3377
SummaryLong code Direct Sequence Spread Spectrum is a good choice for applications where security and antispoofing ability of a spread spectrum connection is concerned. Due to long period of spreading code, acquisition is a challenge for these systems because a trade‐off between detection probability and acquisition time must be made. For confronting this challenge, various algorithms were proposed in the literature but almost all of them focus on expediting the coarse acquisition. In this paper, we consider the efficient dual folding algorithm for coarse acquisition level and propose 3 methods for enhancing the fine acquisition level leading to faster execution of overall acquisition algorithm. The methods are based on estimations from coarse acquisition level that are not used in conventional algorithms for fine acquisition, ie, zero padding. Theoretical expressions of 2 main comparison criteria in acquisition algorithms, ie, detection probability and mean acquisition time, are derived for conventional zero padding and each of the proposed method. Besides, a coarse estimate of resource consumption is provided by the number of floating point operations for each algorithm to make a useful comparison. Considering these 3 parameters, in comparison, the proposed methods surpass zero padding in 1, 2, or all of the 3 aspects. Simulation agrees well with analytical results.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
