[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83553-en":3,"doc-seo-83553-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},83553,962075006959,"Anda","https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297",8,"Research & Report","Fundamental Limits of Random Downlink Integrated Sensing and Communication over Rician Channels","This paper studies stochastic performance of a downlink multiple-input multiple-output integrated sensing and communication (ISAC) system over Rician fading channels. Rician fading models line-of-sight dominated deployments where a deterministic propagation component impacts sensing and communication reliability. A base station simultaneously serves a user and senses a target using beamforming. Using Gaussian approximations, coherent LoS terms yield non-identically distributed random vectors, requiring new analysis. Communication outage probability and sensing outage probability are derived via CRB, with special cases and scaling laws.","Fundamental Limits of Random Downlink Integrated Sensing and Communication over Rician  \nChannels  \nMarziyeh Soltani, Mahtab Mirmohseni, Senior Member, IEEE, Rahim Tafazolli, Fellow, IEEE,  \nand Mark F. Flanagan, Senior Member, IEEE  \narXiv :2607 .009 12v 1 [ cs .IT] 1 Jul 2026  \nAbstract—This paper studies the stochastic performance of a downlink multiple-input multiple-output integrated sensing and communication (ISAC) system over Rician fading channels. Rician fading is important in line-of-sight (LoS)-dominated deployments, where a deterministic propagation component can strongly affect both sensing and communication reliability. The considered base station (BS) simultaneously serves a user and senses a target. The BS–user channel contains both LoS and non-line-of-sight (NLoS) components. The user LoS angle maybe fixed or random, and the target angle may follow an arbitrary distribution that is potentially correlated with the user angle. Compared with the Rayleigh setting, the deterministic LoS component introduces coherent angle-dependent terms and makes the key random vectors in the Gaussian approximation generally independent but non-identically distributed, which requires new analysis. We analyze two beamforming strategies: subspace joint beamforming (SJB), which is optimal for the shared sensingcommunication waveform structure considered here, and linear beamforming (LB), a near-optimal and practically attractive alternative that uses separate sensing and communication beamformers. For both schemes, we derive the communication outage probability (OP) and the sensing OP based on the Cram´er– Rao bound (CRB). We also identify several practically important special cases that admit simpler expressions. For LB, we derive upper and lower bounds on the sensing OP together with a tractable approximation. We further characterize the largesystem and high-power scaling laws. LB without dirty paper coding (DPC) is interference-limited in the high-power regime due to radar self-interference. The results show that the Rician K-factor affects communication more strongly than sensing, with non-monotonic behavior across propagation regimes. Under the considered settings, LB with DPC provides the best overall performance in strong-LoS environments and is the only scheme observed to achieve ultra-high communication reliability in the special case of Rayleigh fading,, while SJB offers a robust lower-complexity alternative across a broad range of operating conditions.  \nIndex Terms—Integrated Sensing and Communications, Performance analysis, Outage tradeoff, CRB, Randomness, Rician  \nI. INTRODUCTION  \nThis work was supported by Taighde ´Eireann-Research Ireland under the Frontiers for the Future Programme (Grant Number 24/FFP-P/12895) . Marziyeh Soltani and Mark F. Flanagan are with the School of Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, D04 V1W8, Ireland ([e-mail: marziyeh.soltani@ucd.ie](e-mail: marziyeh.soltani@ucd.ie), mark.fl[anagan@ieee.org](anagan@ieee.org)).  \nMahtab Mirmohseni and Rahim Tafazolli are with the 6G Innovation Centre (6GIC), Institute for Communication Systems (ICS), University of Surrey, Guildford GU2 7XH, U.K. (e-mail: [m.mirmohseni@surrey.ac.uk](m.mirmohseni@surrey.ac.uk), [r.tafazolli@surrey.ac.uk](r.tafazolli@surrey.ac.uk)).  \nTHE growing need for new capabilities in wireless net  \nworks has led to the integration of different functions that were traditionally separate. A key example of this trend is integrated sensing and communications (ISAC), which brings together radar and communication systems to simultaneously perform sensing and data transmission [1] . This dual-functional approach is especially important for emerging applications in the internet of things (IoT), including smart city infrastructure, vehicular, and industrial networks [2] . By sharing spectrum and hardware resources, ISAC offers significant advantages for both sensing and communication. However, this","cbCair7dDDXS3J5D","https://ap.wps.com/l/cbCair7dDDXS3J5D","pdf",455050,4,1,14,"English","en",105,"# Abstract\n# Introduction\n## Related Works\n## Limitations of existing works","[{\"question\":\"What system and channel model does the paper analyze?\",\"answer\":\"The paper analyzes a downlink MIMO integrated sensing and communication (ISAC) system over Rician fading channels, where both LoS and NLoS components exist in the base station–user channel.\"},{\"question\":\"How are the key performance metrics derived for both communication and sensing?\",\"answer\":\"The paper derives the communication outage probability and the sensing outage probability for two beamforming schemes using the Cramér–Rao bound (CRB) and related approximations.\"},{\"question\":\"Why does the Rician LoS component require new analysis compared with Rayleigh fading?\",\"answer\":\"The deterministic LoS introduces coherent angle-dependent terms, so the Gaussian-approximation random vectors become independent but non-identically distributed, unlike the Rayleigh setting.\"}]",1784188774,35,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"fundamental-limits-of-random-downlink-integrated-sensing-and-communication-over-rician-channels","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":20},"https://docshare.wps.com/document/fundamental-limits-of-random-downlink-integrated-sensing-and-communication-over-rician-channels/83553/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-25","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What system and channel model does the paper analyze?","Question",{"text":75,"@type":76},"The paper analyzes a downlink MIMO integrated sensing and communication (ISAC) system over Rician fading channels, where both LoS and NLoS components exist in the base station–user channel.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How are the key performance metrics derived for both communication and sensing?",{"text":80,"@type":76},"The paper derives the communication outage probability and the sensing outage probability for two beamforming schemes using the Cramér–Rao bound (CRB) and related approximations.",{"name":82,"@type":73,"acceptedAnswer":83},"Why does the Rician LoS component require new analysis compared with Rayleigh fading?",{"text":84,"@type":76},"The deterministic LoS introduces coherent angle-dependent terms, so the Gaussian-approximation random vectors become independent but non-identically distributed, unlike the Rayleigh 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