SNR Estimation for DVB-S2 System

Kim, Soo‐Young; Kim, Sooseong; Park, Eunwoo; Yeo, Sungmoon

doi:10.2514/6.2007-3302

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…Since this algorithm produced a number of problems in application to high order signaling schemes such as M-ary QAM and APSK schemes, a few modifications were made in our previous research [5] [6]. In this paper, we introduce a more efficient algorithm which can be applied to high order modulation schemes with very low computational complexity.…”

Section: Previous Researchesmentioning

confidence: 97%

“…Depending on the values of C1 and C2, the counter controller produces up or down command to make the content in the up-down counter be n c value. In this way, the estimate of the LUT address L â can be found by (6). Since the address is calculated by a simple linear combination of the predetermined constants, the total computational complexity to find the SNR is very low.…”

Section: Snr Estimation Using the Lutmentioning

confidence: 99%

“…In addition, the estimation error in low SNR range (less than 5 dB for BPSK or QPSK modulation schemes) is too high to get a desirable result. Our previous research presented SNR estimation techniques for high order M-ary PSK and QAM scheme [5], and a simpler algorithm was introduced in [6].…”

Section: Introductionmentioning

confidence: 99%

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A Simple Hardware Structure for SNR Estimation

Kim

Park

Yeo

et al. 2007

MILCOM 2007 - IEEE Military Communications Conference

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In this paper, we present an efficient hardware structure to estimate signal to noise ratio (SNR) for M-ary amplitude and phase modulation schemes at the receiver. The proposed hardware structure requires a counter and two comparators with a predetermined look up table (LUT). For an estimation error of less than 1 dB, it needs just about a few hundred samples. We can design the LUTs with theoretically derived values and tailor them for special purposes. We demonstrate a few simulation results of the estimation algorithm, and present hardware implementation results.

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Section: Previous Researchesmentioning

confidence: 97%

Section: Snr Estimation Using the Lutmentioning

confidence: 99%