{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/29794"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/29794","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Communication strategies for the MIMO interference channel","abstract":"Managing interference for wireless networks is crucial for meeting future demand for higher mobile data rates. Interference can be viewed through the interference channel (IC) in which pairs of transmitters and receivers interfere with each other, so an interesting way to manage interference is to develop communication strategies for the IC. We consider the problem of designing signals to transmit over the multiple input and multiple output (MIMO) interference channel by extending the Max SINR algorithm. The Max SINR algorithm starts with arbitrary beamformers and then designs optimal receivers to maximize the SINR at each receiver. The Max SINR algorithm then alternates the direction of communication and repeats this process. This algorithm is known to perform well, but there is no proof that it converges. We propose a modification to Max SINR using a power control step to make a metric similar to sum rate converge. With successive interference cancellation (SIC), then the new metric is exactly the sum rate. Finally, simulations show that the performance of the modified Max SINR algorithm, unlike other convergent alternatives, is nearly identical to that of the original Max SINR algorithm.","abstract_html":"Managing interference for wireless networks is crucial for meeting future demand for higher mobile data rates. Interference can be viewed through the interference channel (IC) in which pairs of transmitters and receivers interfere with each other, so an interesting way to manage interference is to develop communication strategies for the IC. We consider the problem of designing signals to transmit over the multiple input and multiple output (MIMO) interference channel by extending the Max SINR algorithm. The Max SINR algorithm starts with arbitrary beamformers and then designs optimal receivers to maximize the SINR at each receiver. The Max SINR algorithm then alternates the direction of communication and repeats this process. This algorithm is known to perform well, but there is no proof that it converges. We propose a modification to Max SINR using a power control step to make a metric similar to sum rate converge. With successive interference cancellation (SIC), then the new metric is exactly the sum rate. Finally, simulations show that the performance of the modified Max SINR algorithm, unlike other convergent alternatives, is nearly identical to that of the original Max SINR algorithm.","abstract_has_math":false,"creators":["Wilson, Craig"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Veeravalli, Venugopal V."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-02-06T20:17:33Z","date_published":"2012-02-06T20:17:33Z","updated_at":"2026-07-22T22:25:29Z","subjects":["wireless networks","interference channels","iterative algorithms","throughput"],"languages":["en"],"rights":["Copyright 2011 Craig Wilson"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/29794","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Veeravalli, Venugopal V."]},{"key":"dc:creator","label":"Author","values":["Wilson, Craig"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2012-02-06T20:17:33Z","2011-12"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation / Thesis","text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["wireless networks","interference channels","iterative algorithms","throughput"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2011 Craig Wilson"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/29794"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Managing interference for wireless networks is crucial for meeting future demand for higher mobile data rates. Interference can be viewed through the interference channel (IC) in which pairs of transmitters and receivers interfere with each other, so an interesting way to manage interference is to develop communication strategies for the IC. We consider the problem of designing signals to transmit over the multiple input and multiple output (MIMO) interference channel by extending the Max SINR algorithm. The Max SINR algorithm starts with arbitrary beamformers and then designs optimal receivers to maximize the SINR at each receiver. The Max SINR algorithm then alternates the direction of communication and repeats this process. This algorithm is known to perform well, but there is no proof that it converges. We propose a modification to Max SINR using a power control step to make a metric similar to sum rate converge. With successive interference cancellation (SIC), then the new metric is exactly the sum rate. Finally, simulations show that the performance of the modified Max SINR algorithm, unlike other convergent alternatives, is nearly identical to that of the original Max SINR algorithm.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2011-12-05T22:19:15Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 wilson_craig_masters_thesis_originals.zip: 1107977 bytes, checksum: 4b5a7d329582d9a6b7390e854296a9ee (MD5) wilson_craig.pdf: 726103 bytes, checksum: 2e6c330f46ac4eaf9f4d34adb5b9bb5b (MD5)","Made available in DSpace on 2012-02-06T20:17:33Z (GMT). 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We consider the problem of designing signals to transmit over the multiple input and multiple output (MIMO) interference channel by extending the Max SINR algorithm. The Max SINR algorithm starts with arbitrary beamformers and then designs optimal receivers to maximize the SINR at each receiver. The Max SINR algorithm then alternates the direction of communication and repeats this process. This algorithm is known to perform well, but there is no proof that it converges. We propose a modification to Max SINR using a power control step to make a metric similar to sum rate converge. With successive interference cancellation (SIC), then the new metric is exactly the sum rate. Finally, simulations show that the performance of the modified Max SINR algorithm, unlike other convergent alternatives, is nearly identical to that of the original Max SINR algorithm.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2011-12-05T22:19:15Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 wilson_craig_masters_thesis_originals.zip: 1107977 bytes, checksum: 4b5a7d329582d9a6b7390e854296a9ee (MD5) wilson_craig.pdf: 726103 bytes, checksum: 2e6c330f46ac4eaf9f4d34adb5b9bb5b (MD5)","Made available in DSpace on 2012-02-06T20:17:33Z (GMT). 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