Non-data-aided ML SNR estimation for AWGN channels with deterministic interference View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Fangjiong Chen, Yabing Kang, Hua Yu, Fei Ji

ABSTRACT

Communication channels not only suffer from ambient noise but also from deterministic interference. In this paper, we consider signal-to-noise ratio (SNR) estimation in the presence of constant deterministic interference. A maximum likelihood (ML) non-data-aided algorithm is proposed for SNR estimation. We first consider a real-valued model and then extend this to a complex-valued model. The proposed algorithm applies an iterative approach initialized with approximate closed form estimates so as to guarantee stability and convergence. Furthermore, the Cramer-Rao bound (CRB) is also derived as the theoretical limit of the jitter variance. Computer simulations based on pulse-amplitude modulation (PAM) and quadrature amplitude modulation (QAM) sources show that the performance of the proposed algorithm is close to the CRB. More... »

PAGES

45

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1687-1499-2014-45

DOI

http://dx.doi.org/10.1186/1687-1499-2014-45

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008115258


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "South China University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.79703.3a", 
          "name": [
            "School of Electronic and Information Engineering, South China University of Technology, 510640, Guangzhou, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chen", 
        "givenName": "Fangjiong", 
        "id": "sg:person.013206530453.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013206530453.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "South China University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.79703.3a", 
          "name": [
            "School of Electronic and Information Engineering, South China University of Technology, 510640, Guangzhou, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kang", 
        "givenName": "Yabing", 
        "id": "sg:person.013222561633.03", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013222561633.03"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "South China University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.79703.3a", 
          "name": [
            "School of Electronic and Information Engineering, South China University of Technology, 510640, Guangzhou, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yu", 
        "givenName": "Hua", 
        "id": "sg:person.013612605701.34", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013612605701.34"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "South China University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.79703.3a", 
          "name": [
            "School of Electronic and Information Engineering, South China University of Technology, 510640, Guangzhou, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ji", 
        "givenName": "Fei", 
        "id": "sg:person.014732363541.60", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014732363541.60"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1109/18.243443", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061098954"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/lcomm.2005.1496583", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061347126"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tcomm.2008.060275", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061556953"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tcomm.2011.100411.100284", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061558267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tsp.2011.2180719", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061803090"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tvt.2009.2014240", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061819939"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tvt.2010.2062548", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061820526"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/twc.2009.080139", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061826645"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icpads.2011.155", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095217487"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-12", 
    "datePublishedReg": "2014-12-01", 
    "description": "Communication channels not only suffer from ambient noise but also from deterministic interference. In this paper, we consider signal-to-noise ratio (SNR) estimation in the presence of constant deterministic interference. A maximum likelihood (ML) non-data-aided algorithm is proposed for SNR estimation. We first consider a real-valued model and then extend this to a complex-valued model. The proposed algorithm applies an iterative approach initialized with approximate closed form estimates so as to guarantee stability and convergence. Furthermore, the Cramer-Rao bound (CRB) is also derived as the theoretical limit of the jitter variance. Computer simulations based on pulse-amplitude modulation (PAM) and quadrature amplitude modulation (QAM) sources show that the performance of the proposed algorithm is close to the CRB.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/1687-1499-2014-45", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.7203908", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.6988323", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1050477", 
        "issn": [
          "1687-1472", 
          "1687-1499"
        ], 
        "name": "EURASIP Journal on Wireless Communications and Networking", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "2014"
      }
    ], 
    "name": "Non-data-aided ML SNR estimation for AWGN channels with deterministic interference", 
    "pagination": "45", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "26a97f7f96a44720929cc39047bd800af280d25e4cd1f008e6d33f9a6debc4b0"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1687-1499-2014-45"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1008115258"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1687-1499-2014-45", 
      "https://app.dimensions.ai/details/publication/pub.1008115258"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T16:41", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8669_00000510.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2F1687-1499-2014-45"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1687-1499-2014-45'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1687-1499-2014-45'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1687-1499-2014-45'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1687-1499-2014-45'


 

This table displays all metadata directly associated to this object as RDF triples.

113 TRIPLES      21 PREDICATES      36 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1687-1499-2014-45 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Nc72a5be5b01d42eeb26654888080d3ea
4 schema:citation https://doi.org/10.1109/18.243443
5 https://doi.org/10.1109/icpads.2011.155
6 https://doi.org/10.1109/lcomm.2005.1496583
7 https://doi.org/10.1109/tcomm.2008.060275
8 https://doi.org/10.1109/tcomm.2011.100411.100284
9 https://doi.org/10.1109/tsp.2011.2180719
10 https://doi.org/10.1109/tvt.2009.2014240
11 https://doi.org/10.1109/tvt.2010.2062548
12 https://doi.org/10.1109/twc.2009.080139
13 schema:datePublished 2014-12
14 schema:datePublishedReg 2014-12-01
15 schema:description Communication channels not only suffer from ambient noise but also from deterministic interference. In this paper, we consider signal-to-noise ratio (SNR) estimation in the presence of constant deterministic interference. A maximum likelihood (ML) non-data-aided algorithm is proposed for SNR estimation. We first consider a real-valued model and then extend this to a complex-valued model. The proposed algorithm applies an iterative approach initialized with approximate closed form estimates so as to guarantee stability and convergence. Furthermore, the Cramer-Rao bound (CRB) is also derived as the theoretical limit of the jitter variance. Computer simulations based on pulse-amplitude modulation (PAM) and quadrature amplitude modulation (QAM) sources show that the performance of the proposed algorithm is close to the CRB.
16 schema:genre research_article
17 schema:inLanguage en
18 schema:isAccessibleForFree true
19 schema:isPartOf N0500f193686640139fe2347fffb7be5d
20 Nd54509be59924c97acf59d9a6aaa40e6
21 sg:journal.1050477
22 schema:name Non-data-aided ML SNR estimation for AWGN channels with deterministic interference
23 schema:pagination 45
24 schema:productId Nce4563ea97fd4cc38be7cfd6f8b0270d
25 Neec960f3699a42aa97313553a6361e0d
26 Nf259d257413e422dbc1d9067ded766a6
27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008115258
28 https://doi.org/10.1186/1687-1499-2014-45
29 schema:sdDatePublished 2019-04-10T16:41
30 schema:sdLicense https://scigraph.springernature.com/explorer/license/
31 schema:sdPublisher N31a42b77da0a4676966abade6d226bc9
32 schema:url http://link.springer.com/10.1186%2F1687-1499-2014-45
33 sgo:license sg:explorer/license/
34 sgo:sdDataset articles
35 rdf:type schema:ScholarlyArticle
36 N0500f193686640139fe2347fffb7be5d schema:volumeNumber 2014
37 rdf:type schema:PublicationVolume
38 N31a42b77da0a4676966abade6d226bc9 schema:name Springer Nature - SN SciGraph project
39 rdf:type schema:Organization
40 N5f5d345cbb324411ada7f1f5ee243fcd rdf:first sg:person.013612605701.34
41 rdf:rest N657dc82a3c6d45baa85b93fa2c0ac816
42 N657dc82a3c6d45baa85b93fa2c0ac816 rdf:first sg:person.014732363541.60
43 rdf:rest rdf:nil
44 Na7ef6e3f90444499920bba7835f8625c rdf:first sg:person.013222561633.03
45 rdf:rest N5f5d345cbb324411ada7f1f5ee243fcd
46 Nc72a5be5b01d42eeb26654888080d3ea rdf:first sg:person.013206530453.79
47 rdf:rest Na7ef6e3f90444499920bba7835f8625c
48 Nce4563ea97fd4cc38be7cfd6f8b0270d schema:name readcube_id
49 schema:value 26a97f7f96a44720929cc39047bd800af280d25e4cd1f008e6d33f9a6debc4b0
50 rdf:type schema:PropertyValue
51 Nd54509be59924c97acf59d9a6aaa40e6 schema:issueNumber 1
52 rdf:type schema:PublicationIssue
53 Neec960f3699a42aa97313553a6361e0d schema:name doi
54 schema:value 10.1186/1687-1499-2014-45
55 rdf:type schema:PropertyValue
56 Nf259d257413e422dbc1d9067ded766a6 schema:name dimensions_id
57 schema:value pub.1008115258
58 rdf:type schema:PropertyValue
59 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
60 schema:name Information and Computing Sciences
61 rdf:type schema:DefinedTerm
62 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
63 schema:name Artificial Intelligence and Image Processing
64 rdf:type schema:DefinedTerm
65 sg:grant.6988323 http://pending.schema.org/fundedItem sg:pub.10.1186/1687-1499-2014-45
66 rdf:type schema:MonetaryGrant
67 sg:grant.7203908 http://pending.schema.org/fundedItem sg:pub.10.1186/1687-1499-2014-45
68 rdf:type schema:MonetaryGrant
69 sg:journal.1050477 schema:issn 1687-1472
70 1687-1499
71 schema:name EURASIP Journal on Wireless Communications and Networking
72 rdf:type schema:Periodical
73 sg:person.013206530453.79 schema:affiliation https://www.grid.ac/institutes/grid.79703.3a
74 schema:familyName Chen
75 schema:givenName Fangjiong
76 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013206530453.79
77 rdf:type schema:Person
78 sg:person.013222561633.03 schema:affiliation https://www.grid.ac/institutes/grid.79703.3a
79 schema:familyName Kang
80 schema:givenName Yabing
81 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013222561633.03
82 rdf:type schema:Person
83 sg:person.013612605701.34 schema:affiliation https://www.grid.ac/institutes/grid.79703.3a
84 schema:familyName Yu
85 schema:givenName Hua
86 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013612605701.34
87 rdf:type schema:Person
88 sg:person.014732363541.60 schema:affiliation https://www.grid.ac/institutes/grid.79703.3a
89 schema:familyName Ji
90 schema:givenName Fei
91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014732363541.60
92 rdf:type schema:Person
93 https://doi.org/10.1109/18.243443 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061098954
94 rdf:type schema:CreativeWork
95 https://doi.org/10.1109/icpads.2011.155 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095217487
96 rdf:type schema:CreativeWork
97 https://doi.org/10.1109/lcomm.2005.1496583 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061347126
98 rdf:type schema:CreativeWork
99 https://doi.org/10.1109/tcomm.2008.060275 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061556953
100 rdf:type schema:CreativeWork
101 https://doi.org/10.1109/tcomm.2011.100411.100284 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061558267
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1109/tsp.2011.2180719 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061803090
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1109/tvt.2009.2014240 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061819939
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1109/tvt.2010.2062548 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061820526
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1109/twc.2009.080139 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061826645
110 rdf:type schema:CreativeWork
111 https://www.grid.ac/institutes/grid.79703.3a schema:alternateName South China University of Technology
112 schema:name School of Electronic and Information Engineering, South China University of Technology, 510640, Guangzhou, China
113 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...