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Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment
We investigate the uplink and downlink achievable rates of full-duplex (FD) massive multi-input multi-output (MIMO) systems with low-resolution analog-digital converters/digital-to-analog converters (ADCs/DACs), where maximum ratio combining/maximum ratio transmission (MRC/MRT) processing are adopte...
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Published in: | EURASIP journal on wireless communications and networking 2018-09, Vol.2018 (1), p.1-12 |
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description | We investigate the uplink and downlink achievable rates of full-duplex (FD) massive multi-input multi-output (MIMO) systems with low-resolution analog-digital converters/digital-to-analog converters (ADCs/DACs), where maximum ratio combining/maximum ratio transmission (MRC/MRT) processing are adopted and imperfect channel state information (CSI) is assumed. In this paper, the quantization noise is encapsulated as an additive quantization noise model (AQNM). Then, employing the minimum mean-square error (MMSE) channel estimator, approximate expressions of the uplink and downlink achievable rates are derived, based on the analysis of the quantization error, loop interference (LI), and the inter-user interference (IUI). It is shown that the interference and noise can be eliminated by applying power scaling law properly and increasing the number of antennas. Moreover, given the number of antennas, it is found that the uplink and downlink approximate achievable rates will converge to a constant when the number of quantization bit tends to infinity. Therefore, the system performance that can be improved by increasing ADC/DAC resolution is limited, implying that it is reasonable to adopt low-resolution ADCs/DACs in FD massive MIMO systems. |
doi_str_mv | 10.1186/s13638-018-1242-y |
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In this paper, the quantization noise is encapsulated as an additive quantization noise model (AQNM). Then, employing the minimum mean-square error (MMSE) channel estimator, approximate expressions of the uplink and downlink achievable rates are derived, based on the analysis of the quantization error, loop interference (LI), and the inter-user interference (IUI). It is shown that the interference and noise can be eliminated by applying power scaling law properly and increasing the number of antennas. Moreover, given the number of antennas, it is found that the uplink and downlink approximate achievable rates will converge to a constant when the number of quantization bit tends to infinity. Therefore, the system performance that can be improved by increasing ADC/DAC resolution is limited, implying that it is reasonable to adopt low-resolution ADCs/DACs in FD massive MIMO systems.</description><identifier>ISSN: 1687-1472</identifier><identifier>EISSN: 1687-1499</identifier><identifier>DOI: 10.1186/s13638-018-1242-y</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Achievable rates ; Antennas ; Communication channels ; Communications Engineering ; Digital to analog conversion ; Digital to analog converters ; Engineering ; Error analysis ; Full-duplex ; Imperfect CSI ; Information Systems Applications (incl.Internet) ; Interference ; Low-resolution ADCs/DACs ; Massive MIMO ; Mean square errors ; Measurement ; MIMO (control systems) ; Networks ; Noise ; Scaling laws ; Signal,Image and Speech Processing ; State (computer science) ; Ultra-Reliable-and-Available Low-Latency Communications for 5G/B5G-enabled IoT</subject><ispartof>EURASIP journal on wireless communications and networking, 2018-09, Vol.2018 (1), p.1-12</ispartof><rights>The Author(s) 2018</rights><rights>EURASIP Journal on Wireless Communications and Networking is a copyright of Springer, (2018). All Rights Reserved. © 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-d222t-8a4942aeb9330c525ad3cfa54623748dd44472706b3d004b766d3e2117bfa803</cites><orcidid>0000-0001-5735-4000</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2104560027/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2104560027?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25752,27923,27924,37011,44589,74897</link.rule.ids></links><search><creatorcontrib>Liu, Juan</creatorcontrib><creatorcontrib>Dai, Jianxin</creatorcontrib><creatorcontrib>Wang, Jiangzhou</creatorcontrib><creatorcontrib>Yin, Xiaohui</creatorcontrib><creatorcontrib>Jiang, Zhifang</creatorcontrib><creatorcontrib>Wang, Jinyuan</creatorcontrib><title>Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment</title><title>EURASIP journal on wireless communications and networking</title><addtitle>J Wireless Com Network</addtitle><description>We investigate the uplink and downlink achievable rates of full-duplex (FD) massive multi-input multi-output (MIMO) systems with low-resolution analog-digital converters/digital-to-analog converters (ADCs/DACs), where maximum ratio combining/maximum ratio transmission (MRC/MRT) processing are adopted and imperfect channel state information (CSI) is assumed. In this paper, the quantization noise is encapsulated as an additive quantization noise model (AQNM). Then, employing the minimum mean-square error (MMSE) channel estimator, approximate expressions of the uplink and downlink achievable rates are derived, based on the analysis of the quantization error, loop interference (LI), and the inter-user interference (IUI). It is shown that the interference and noise can be eliminated by applying power scaling law properly and increasing the number of antennas. Moreover, given the number of antennas, it is found that the uplink and downlink approximate achievable rates will converge to a constant when the number of quantization bit tends to infinity. Therefore, the system performance that can be improved by increasing ADC/DAC resolution is limited, implying that it is reasonable to adopt low-resolution ADCs/DACs in FD massive MIMO systems.</description><subject>Achievable rates</subject><subject>Antennas</subject><subject>Communication channels</subject><subject>Communications Engineering</subject><subject>Digital to analog conversion</subject><subject>Digital to analog converters</subject><subject>Engineering</subject><subject>Error analysis</subject><subject>Full-duplex</subject><subject>Imperfect CSI</subject><subject>Information Systems Applications (incl.Internet)</subject><subject>Interference</subject><subject>Low-resolution ADCs/DACs</subject><subject>Massive MIMO</subject><subject>Mean square errors</subject><subject>Measurement</subject><subject>MIMO (control systems)</subject><subject>Networks</subject><subject>Noise</subject><subject>Scaling laws</subject><subject>Signal,Image and Speech Processing</subject><subject>State (computer science)</subject><subject>Ultra-Reliable-and-Available Low-Latency Communications for 5G/B5G-enabled IoT</subject><issn>1687-1472</issn><issn>1687-1499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpFkctu2zAQRYUiAZrXB2RHIGvWfJNaGkofBhJk0ewJShwlNCTRISmn_vvKdZGsZjC4uDN3TlXdUvKNUqNWmXLFDSbUYMoEw4cv1QVVRmMq6vrso9fsa3WZ85YQzkXNLqq87l4D7F07AEquQEZ9TKifhwH7eTfAHzS6nMMe0OPm8QnlQy4wZvQeyisa4jtOkOMwlxAntL5v8up-3WQ0Tx4SCuMOUg9dQc3vDYJpH1KcRpjKdXXeuyHDzf96VT3_-P7c_MIPTz83zfoBe8ZYwcaJWjAHbc056SSTzvOud1IoxrUw3gux5NFEtdwTIlqtlOfAKNVt7wzhV9XmZOuj29pdCqNLBxtdsP8GMb1Yl0roBrDAZau0UbqWx38RQ4WUvKZSetES1y1edyevXYpvM-Rit3FO03K9ZZQIqQhhelGxkyov26YXSJ8qSuyRkz1xsgsne-RkD_wvrZaEvA</recordid><startdate>20180915</startdate><enddate>20180915</enddate><creator>Liu, Juan</creator><creator>Dai, Jianxin</creator><creator>Wang, Jiangzhou</creator><creator>Yin, Xiaohui</creator><creator>Jiang, Zhifang</creator><creator>Wang, Jinyuan</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><general>SpringerOpen</general><scope>C6C</scope><scope>3V.</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-5735-4000</orcidid></search><sort><creationdate>20180915</creationdate><title>Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment</title><author>Liu, Juan ; Dai, Jianxin ; Wang, Jiangzhou ; Yin, Xiaohui ; Jiang, Zhifang ; Wang, Jinyuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-d222t-8a4942aeb9330c525ad3cfa54623748dd44472706b3d004b766d3e2117bfa803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Achievable rates</topic><topic>Antennas</topic><topic>Communication channels</topic><topic>Communications Engineering</topic><topic>Digital to analog conversion</topic><topic>Digital to analog converters</topic><topic>Engineering</topic><topic>Error analysis</topic><topic>Full-duplex</topic><topic>Imperfect CSI</topic><topic>Information Systems Applications (incl.Internet)</topic><topic>Interference</topic><topic>Low-resolution ADCs/DACs</topic><topic>Massive MIMO</topic><topic>Mean square errors</topic><topic>Measurement</topic><topic>MIMO (control systems)</topic><topic>Networks</topic><topic>Noise</topic><topic>Scaling laws</topic><topic>Signal,Image and Speech Processing</topic><topic>State (computer science)</topic><topic>Ultra-Reliable-and-Available Low-Latency Communications for 5G/B5G-enabled IoT</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Juan</creatorcontrib><creatorcontrib>Dai, Jianxin</creatorcontrib><creatorcontrib>Wang, Jiangzhou</creatorcontrib><creatorcontrib>Yin, Xiaohui</creatorcontrib><creatorcontrib>Jiang, Zhifang</creatorcontrib><creatorcontrib>Wang, Jinyuan</creatorcontrib><collection>SpringerOpen</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>EURASIP journal on wireless communications and networking</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Juan</au><au>Dai, Jianxin</au><au>Wang, Jiangzhou</au><au>Yin, Xiaohui</au><au>Jiang, Zhifang</au><au>Wang, Jinyuan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment</atitle><jtitle>EURASIP journal on wireless communications and networking</jtitle><stitle>J Wireless Com Network</stitle><date>2018-09-15</date><risdate>2018</risdate><volume>2018</volume><issue>1</issue><spage>1</spage><epage>12</epage><pages>1-12</pages><issn>1687-1472</issn><eissn>1687-1499</eissn><abstract>We investigate the uplink and downlink achievable rates of full-duplex (FD) massive multi-input multi-output (MIMO) systems with low-resolution analog-digital converters/digital-to-analog converters (ADCs/DACs), where maximum ratio combining/maximum ratio transmission (MRC/MRT) processing are adopted and imperfect channel state information (CSI) is assumed. In this paper, the quantization noise is encapsulated as an additive quantization noise model (AQNM). Then, employing the minimum mean-square error (MMSE) channel estimator, approximate expressions of the uplink and downlink achievable rates are derived, based on the analysis of the quantization error, loop interference (LI), and the inter-user interference (IUI). It is shown that the interference and noise can be eliminated by applying power scaling law properly and increasing the number of antennas. Moreover, given the number of antennas, it is found that the uplink and downlink approximate achievable rates will converge to a constant when the number of quantization bit tends to infinity. Therefore, the system performance that can be improved by increasing ADC/DAC resolution is limited, implying that it is reasonable to adopt low-resolution ADCs/DACs in FD massive MIMO systems.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1186/s13638-018-1242-y</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-5735-4000</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Achievable rates Antennas Communication channels Communications Engineering Digital to analog conversion Digital to analog converters Engineering Error analysis Full-duplex Imperfect CSI Information Systems Applications (incl.Internet) Interference Low-resolution ADCs/DACs Massive MIMO Mean square errors Measurement MIMO (control systems) Networks Noise Scaling laws Signal,Image and Speech Processing State (computer science) Ultra-Reliable-and-Available Low-Latency Communications for 5G/B5G-enabled IoT |
title | Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment |
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