Radar Waveform Design Under Communication Sum Capacity Constraint
This paper considers a joint radar and wireless communication systems where the radar transmit waveform is adaptively designed. To ensure acceptable performance of both radar and communication systems operating in the same frequency bands, the radar makes use of knowledge provided by the communicati...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on signal processing 2021, Vol.69, p.2795-2806 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 2806 |
---|---|
container_issue | |
container_start_page | 2795 |
container_title | IEEE transactions on signal processing |
container_volume | 69 |
creator | Kang, Bosung Rangaswamy, Muralidhar |
description | This paper considers a joint radar and wireless communication systems where the radar transmit waveform is adaptively designed. To ensure acceptable performance of both radar and communication systems operating in the same frequency bands, the radar makes use of knowledge provided by the communication systems and vice versa. Specifically, the radar transmit waveform is designed not only to maximize radar performance such as signal-to-interference-and-noise ratio (SINR) but also to guarantee acceptable communication systems performance by ensuring a prescribed total throughput or sum capacity of communication systems. We formulate an optimization problem that maximizes the radar performance subject to the radar power constraint and the communication sum capacity constraint. Since the sum capacity constraint is not a convex constraint, the resulting optimization problem is not convex. We provide a geometric analysis of the sum capacity constraint and the solution of the SINR maximization problem in two steps: 1) obtain the optimal solution with only radar power constraints, i.e., without the sum capacity constraint, and then 2) starting from the optimal solution of the first step, find a solution satisfying the sum capacity constraint. In this process, a closed form solution to find the locally optimal point at each search is derived, which reduces computational complexity of the proposed algorithm. Numerical results are provided to verify performance of the proposed method. |
doi_str_mv | 10.1109/TSP.2021.3077300 |
format | Article |
fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_ieee_primary_9424438</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9424438</ieee_id><sourcerecordid>2532301622</sourcerecordid><originalsourceid>FETCH-LOGICAL-c291t-1d54e2e96f2d3c84f3fd5d7e1c93463bc0a03d8007d602245d453543f03ae46c3</originalsourceid><addsrcrecordid>eNo9kE1Lw0AQhhdRsFbvgpeA59TZnd0keyzxEwTFtuhtWfdDUsym7iZC_70pLZ7mhXneGXgIuaQwoxTkzXLxOmPA6AyhLBHgiEyo5DQHXhbHYwaBuajKj1NyltIagHIuiwmZv2mrY_auf53vYpvdutR8hWwVrItZ3bXtEBqj-6YL2WJos1pvtGn67bgKqY-6Cf05OfH6O7mLw5yS1f3dsn7Mn18enur5c26YpH1OreCOOVl4ZtFU3KO3wpaOGom8wE8DGtBWAKUtgDEuLBcoOHpA7XhhcEqu93c3sfsZXOrVuhtiGF8qJpAh0IKxkYI9ZWKXUnRebWLT6rhVFNROlBpFqZ0odRA1Vq72lcY5949LzjjHCv8ABQ1i5Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2532301622</pqid></control><display><type>article</type><title>Radar Waveform Design Under Communication Sum Capacity Constraint</title><source>IEEE Electronic Library (IEL)</source><creator>Kang, Bosung ; Rangaswamy, Muralidhar</creator><creatorcontrib>Kang, Bosung ; Rangaswamy, Muralidhar</creatorcontrib><description>This paper considers a joint radar and wireless communication systems where the radar transmit waveform is adaptively designed. To ensure acceptable performance of both radar and communication systems operating in the same frequency bands, the radar makes use of knowledge provided by the communication systems and vice versa. Specifically, the radar transmit waveform is designed not only to maximize radar performance such as signal-to-interference-and-noise ratio (SINR) but also to guarantee acceptable communication systems performance by ensuring a prescribed total throughput or sum capacity of communication systems. We formulate an optimization problem that maximizes the radar performance subject to the radar power constraint and the communication sum capacity constraint. Since the sum capacity constraint is not a convex constraint, the resulting optimization problem is not convex. We provide a geometric analysis of the sum capacity constraint and the solution of the SINR maximization problem in two steps: 1) obtain the optimal solution with only radar power constraints, i.e., without the sum capacity constraint, and then 2) starting from the optimal solution of the first step, find a solution satisfying the sum capacity constraint. In this process, a closed form solution to find the locally optimal point at each search is derived, which reduces computational complexity of the proposed algorithm. Numerical results are provided to verify performance of the proposed method.</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/TSP.2021.3077300</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Acceptable noise levels ; adaptive radar ; Algorithms ; closed form solution ; Communication ; Communication systems ; Frequencies ; Interference ; MI maximization ; Optimization ; Radar ; Radar detection ; Signal processing algorithms ; Signal to noise ratio ; SINR maximization ; Spectral co-existence ; sum capacity ; waveform design ; Waveforms ; Wireless communication systems</subject><ispartof>IEEE transactions on signal processing, 2021, Vol.69, p.2795-2806</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-1d54e2e96f2d3c84f3fd5d7e1c93463bc0a03d8007d602245d453543f03ae46c3</citedby><cites>FETCH-LOGICAL-c291t-1d54e2e96f2d3c84f3fd5d7e1c93463bc0a03d8007d602245d453543f03ae46c3</cites><orcidid>0000-0001-9429-4537 ; 0000-0003-4830-7637</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9424438$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,4010,27900,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9424438$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Kang, Bosung</creatorcontrib><creatorcontrib>Rangaswamy, Muralidhar</creatorcontrib><title>Radar Waveform Design Under Communication Sum Capacity Constraint</title><title>IEEE transactions on signal processing</title><addtitle>TSP</addtitle><description>This paper considers a joint radar and wireless communication systems where the radar transmit waveform is adaptively designed. To ensure acceptable performance of both radar and communication systems operating in the same frequency bands, the radar makes use of knowledge provided by the communication systems and vice versa. Specifically, the radar transmit waveform is designed not only to maximize radar performance such as signal-to-interference-and-noise ratio (SINR) but also to guarantee acceptable communication systems performance by ensuring a prescribed total throughput or sum capacity of communication systems. We formulate an optimization problem that maximizes the radar performance subject to the radar power constraint and the communication sum capacity constraint. Since the sum capacity constraint is not a convex constraint, the resulting optimization problem is not convex. We provide a geometric analysis of the sum capacity constraint and the solution of the SINR maximization problem in two steps: 1) obtain the optimal solution with only radar power constraints, i.e., without the sum capacity constraint, and then 2) starting from the optimal solution of the first step, find a solution satisfying the sum capacity constraint. In this process, a closed form solution to find the locally optimal point at each search is derived, which reduces computational complexity of the proposed algorithm. Numerical results are provided to verify performance of the proposed method.</description><subject>Acceptable noise levels</subject><subject>adaptive radar</subject><subject>Algorithms</subject><subject>closed form solution</subject><subject>Communication</subject><subject>Communication systems</subject><subject>Frequencies</subject><subject>Interference</subject><subject>MI maximization</subject><subject>Optimization</subject><subject>Radar</subject><subject>Radar detection</subject><subject>Signal processing algorithms</subject><subject>Signal to noise ratio</subject><subject>SINR maximization</subject><subject>Spectral co-existence</subject><subject>sum capacity</subject><subject>waveform design</subject><subject>Waveforms</subject><subject>Wireless communication systems</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1Lw0AQhhdRsFbvgpeA59TZnd0keyzxEwTFtuhtWfdDUsym7iZC_70pLZ7mhXneGXgIuaQwoxTkzXLxOmPA6AyhLBHgiEyo5DQHXhbHYwaBuajKj1NyltIagHIuiwmZv2mrY_auf53vYpvdutR8hWwVrItZ3bXtEBqj-6YL2WJos1pvtGn67bgKqY-6Cf05OfH6O7mLw5yS1f3dsn7Mn18enur5c26YpH1OreCOOVl4ZtFU3KO3wpaOGom8wE8DGtBWAKUtgDEuLBcoOHpA7XhhcEqu93c3sfsZXOrVuhtiGF8qJpAh0IKxkYI9ZWKXUnRebWLT6rhVFNROlBpFqZ0odRA1Vq72lcY5949LzjjHCv8ABQ1i5Q</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Kang, Bosung</creator><creator>Rangaswamy, Muralidhar</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-9429-4537</orcidid><orcidid>https://orcid.org/0000-0003-4830-7637</orcidid></search><sort><creationdate>2021</creationdate><title>Radar Waveform Design Under Communication Sum Capacity Constraint</title><author>Kang, Bosung ; Rangaswamy, Muralidhar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-1d54e2e96f2d3c84f3fd5d7e1c93463bc0a03d8007d602245d453543f03ae46c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Acceptable noise levels</topic><topic>adaptive radar</topic><topic>Algorithms</topic><topic>closed form solution</topic><topic>Communication</topic><topic>Communication systems</topic><topic>Frequencies</topic><topic>Interference</topic><topic>MI maximization</topic><topic>Optimization</topic><topic>Radar</topic><topic>Radar detection</topic><topic>Signal processing algorithms</topic><topic>Signal to noise ratio</topic><topic>SINR maximization</topic><topic>Spectral co-existence</topic><topic>sum capacity</topic><topic>waveform design</topic><topic>Waveforms</topic><topic>Wireless communication systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kang, Bosung</creatorcontrib><creatorcontrib>Rangaswamy, Muralidhar</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kang, Bosung</au><au>Rangaswamy, Muralidhar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Radar Waveform Design Under Communication Sum Capacity Constraint</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>2021</date><risdate>2021</risdate><volume>69</volume><spage>2795</spage><epage>2806</epage><pages>2795-2806</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>This paper considers a joint radar and wireless communication systems where the radar transmit waveform is adaptively designed. To ensure acceptable performance of both radar and communication systems operating in the same frequency bands, the radar makes use of knowledge provided by the communication systems and vice versa. Specifically, the radar transmit waveform is designed not only to maximize radar performance such as signal-to-interference-and-noise ratio (SINR) but also to guarantee acceptable communication systems performance by ensuring a prescribed total throughput or sum capacity of communication systems. We formulate an optimization problem that maximizes the radar performance subject to the radar power constraint and the communication sum capacity constraint. Since the sum capacity constraint is not a convex constraint, the resulting optimization problem is not convex. We provide a geometric analysis of the sum capacity constraint and the solution of the SINR maximization problem in two steps: 1) obtain the optimal solution with only radar power constraints, i.e., without the sum capacity constraint, and then 2) starting from the optimal solution of the first step, find a solution satisfying the sum capacity constraint. In this process, a closed form solution to find the locally optimal point at each search is derived, which reduces computational complexity of the proposed algorithm. Numerical results are provided to verify performance of the proposed method.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TSP.2021.3077300</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-9429-4537</orcidid><orcidid>https://orcid.org/0000-0003-4830-7637</orcidid></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1053-587X |
ispartof | IEEE transactions on signal processing, 2021, Vol.69, p.2795-2806 |
issn | 1053-587X 1941-0476 |
language | eng |
recordid | cdi_ieee_primary_9424438 |
source | IEEE Electronic Library (IEL) |
subjects | Acceptable noise levels adaptive radar Algorithms closed form solution Communication Communication systems Frequencies Interference MI maximization Optimization Radar Radar detection Signal processing algorithms Signal to noise ratio SINR maximization Spectral co-existence sum capacity waveform design Waveforms Wireless communication systems |
title | Radar Waveform Design Under Communication Sum Capacity Constraint |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-18T23%3A16%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Radar%20Waveform%20Design%20Under%20Communication%20Sum%20Capacity%20Constraint&rft.jtitle=IEEE%20transactions%20on%20signal%20processing&rft.au=Kang,%20Bosung&rft.date=2021&rft.volume=69&rft.spage=2795&rft.epage=2806&rft.pages=2795-2806&rft.issn=1053-587X&rft.eissn=1941-0476&rft.coden=ITPRED&rft_id=info:doi/10.1109/TSP.2021.3077300&rft_dat=%3Cproquest_RIE%3E2532301622%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2532301622&rft_id=info:pmid/&rft_ieee_id=9424438&rfr_iscdi=true |