A Novel Pseudoerror Monitor

Abstract

<p/> <p>The error rate (ER) is a crucial criterion in evaluating the performance of a digital communication system. Many ER estimation methods have been described in the literature. Among them, the pseudoerror monitoring solution has attracted special attention due to its consistent performance in different environments and distinctive blind estimation capability, that is, estimating the ER without needing any prior knowledge of the transmitted information. In this paper, a novel pseudoerror monitor (PEM) design, the kernel PEM, is developed. Incorporating the strength of the probability density function (pdf) approximation technique, the proposed design has remarkable advantage of being able to produce statistically consistent ER estimate within a much shorter observation time. Simulation results are given in support of this claim.</p

Comparative Study of Kernel Pseudo-Error Monitor

“…Figure 1 clarifies this In KPEM, the SER is purposely amplified to release the demand on the length of the observation sequence, and Eq. (3) is used to calculate a set of pseudo-error rates, which are then extrapolated to approach the SER (refer to [7] for the details of KPEM).…”

“…However, the observation cost is still unbearable for practical applications. In pursuit of maximum utilization of the observations and thus least observation cost, the strengths of kernel density estimation have been incorporated into SER estimation, and leads to the so-called kernel real-and pseudo-error monitoring [4]- [7].…”

Kernel-based error rate estimation for M-ary modulation

“…In kernel pseudo-error monitoring, the ER is amplified in a controlled manner, so as to reduce the high demand on the size of the observations [5]. Usually, the ER amplification can be achieved by modifying the detection thresholds or degrading the received signal [8].…”

“…However, in this solution, the transmitted signal must be known a priori, so as to meet the requirement for statistical reliability. Wang and Ser propose the so-called kernel pseudo-error monitoring approach to overcome this problem, where the density estimate is used to calculate a set of pseudo-error rates, which are then extrapolated to give the ER estimate [5].…”