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Howard Ma

dblp:203/6345 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1984
—ORCID · none

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

Computer networks · 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.

Theoretical computer science
1 paper
Coding theory · 100%
Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › channel coding › adversarial channel
antijamming codes
0.011984
Error-Correcting Codes Against the Worst-Case Partial-Band Jammer · IEEE Trans. Commun. 1984
Coding theory
error-correcting codes
0.011984
Error-Correcting Codes Against the Worst-Case Partial-Band Jammer · IEEE Trans. Commun. 1984
Physical-layer communications › spread spectrum
frequency hopping
0.011984
Error-Correcting Codes Against the Worst-Case Partial-Band Jammer · IEEE Trans. Commun. 1984
Physical-layer communications
spread spectrum
0.011984
Error-Correcting Codes Against the Worst-Case Partial-Band Jammer · IEEE Trans. Commun. 1984
Coding theory › error-correcting codes
convolutional codes
0.011984
Error-Correcting Codes Against the Worst-Case Partial-Band Jammer · IEEE Trans. Commun. 1984

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

union bound · 0.0chernoff bound · 0.0
YearPublicationVenuePosition
1984 Error-Correcting Codes Against the Worst-Case Partial-Band Jammer
abstract
This paper provides performance analyses of a broad spectrum of error-correcting codes in an antijam communication system under worst-case partial-band noise jamming conditions. These analyses demonstrate the coding advantages available for systems operating with and without frequency diversity. Utilizing both the exact approach (where possible) and upper-bounding approaches (Chernoff and union bounds), the decoded bit error rates for typical error-correcting codes (binary andM-ary, block and convolutional) have been obtained, and these codes have been compared according to theE_{b}/N_{0}required to achieve a bit error rate of 10-5. The best performance is achieved with the use ofM-ary signaling and optimum diversity withM-ary codes, such as Reed-Solomon block codes, dual-kconvolutional codes, convolutional orthogonal codes, or concatenated codes.
Howard Ma, Margaret A. Poole
IEEE Trans. Commun.1