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Thomas A. Schonhoff

dblp:60/10572 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 1997
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 first-authorTheory of computation · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
2 papers
Physical-layer communications · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › modulation › continuous phase modulation
continuous phase frequency shift keying
0.021980
An investigation of continuous phase frequency shift keying as a modulation on additive-impulsive atmospheric noise channels (Ph.D. Thesis abstr.) · IEEE Trans. Inf. Theory 1980
Symbol Error Probabilities for M-ary CPFSK: Coherent and Noncoherent Detection · IEEE Trans. Commun. 1976
Physical-layer communications
modulation
0.011980
An investigation of continuous phase frequency shift keying as a modulation on additive-impulsive atmospheric noise channels (Ph.D. Thesis abstr.) · IEEE Trans. Inf. Theory 1980
Physical-layer communications › signal detection
coherent and noncoherent detection
0.011976
Symbol Error Probabilities for M-ary CPFSK: Coherent and Noncoherent Detection · IEEE Trans. Commun. 1976
Physical-layer communications
modulation and detection
0.011976
Symbol Error Probabilities for M-ary CPFSK: Coherent and Noncoherent Detection · IEEE Trans. Commun. 1976
Physical-layer communications › error probability analysis
symbol error probability
0.011976
Symbol Error Probabilities for M-ary CPFSK: Coherent and Noncoherent Detection · IEEE Trans. Commun. 1976
Physical-layer communications › signal analysis › noise analysis › noise modeling
atmospheric noise channel
0.011980
An investigation of continuous phase frequency shift keying as a modulation on additive-impulsive atmospheric noise channels (Ph.D. Thesis abstr.) · IEEE Trans. Inf. Theory 1980

Methods — techniques the papers use, named apart from their topics

monte carlo simulation · 0.0
YearPublicationVenuePosition
1997 Receiver structures and error rate performance for signals with unknown frequency
abstract
Receiver structures for an optimal noncoherent receiver when a transmitted signal experiences a random frequency shift are derived. Error rate performance, obtained by simulation, is then developed and compared with the standard noncoherent correlator. Results indicate that 1) ignoring the frequency shift by using a standard noncoherent correlator leads to severely degraded performance relative to the optimal noncoherent receiver and 2) even the optimal noncoherent receiver accommodating a random frequency shift exhibits degraded performance as the unknown frequency range grows.
Thomas A. Schonhoff, Arthur A. Giordano
PIMRC1
1980 An investigation of continuous phase frequency shift keying as a modulation on additive-impulsive atmospheric noise channels (Ph.D. Thesis abstr.)
Thomas A. Schonhoff
IEEE Trans. Inf. Theory1
1976 Symbol Error Probabilities for M-ary CPFSK: Coherent and Noncoherent Detection
abstract
Continuous-phase frequency shift keying (CPFSK) is discussed and theoretical predictions for symbol error probabilities are derived, where the memory inherent in the phase continuity is used to improve performance. Previously known results concluded that binary CPFSK can outperform coherently detected PSK at high SNR. New results presented here show thatM-ary CPFSK outperforms more tranditionally usedM-ary modulation systems. Specifically, coherently detected quaternary CPFSK with a five-symbol interval decision can outperform coherent QPSK by 3.5 dB, and octal coherent CPFSK with a three- symbol decision can outperform octal orthogonal signaling by 2.6 dB at high SNR. Results for coherently detected and noncoherently detected CPFSK are derived. These performance improvements are estimates derived from symbol error probability upper bounds. Monte Carlo simulation was performed which then verified the results.
Thomas A. Schonhoff
IEEE Trans. Commun.1