[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84091-en":3,"doc-seo-84091-105":29,"detail-sidebar-cat-0-en-105":82},{"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":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},84091,1099514067438,"River Wang","https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542",8,"Research & Report","Rethinking Fronthaul Topologies for Cell-Free 6G Networks","Dense antenna deployments are expected in future 6G systems, and cell-free MIMO is a leading candidate for enabling such scalability. While much work targets PHY layer advances, networking challenges remain underexplored. This study proposes multiple fronthaul network designs for cell-free MIMO, modeling realistic traffic demands and optimizing processing node assignment. Results show tree topologies work only for small deployments, whereas the proposed Clos topology scales and achieves performance close to an optimal baseline as antenna counts grow.","Rethinking Fronthaul Topologies for Cell-Free 6G Networks  \nMax Franke∗ , Arash Pourdamghani∗ , Fabian Göttsch∗†, Stefan Schmid∗ and Giuseppe Caire∗†  \n∗ TU Berlin, †Massive Beams  \narXiv :2607 .06288v 1 [ cs .IT] 7 Jul 2026  \nAbstract—Due to significant progress in physical layer (PHY) technologies, future 6G networks are expected to feature much denser antenna deployments. Cell-free MIMO network designs are one of the most promising candidates to enable denser networks. While significant effort has been put into its PHY research, the challengesit brings to networking disciplines remain relatively unexplored. In this work, we propose various fronthaul network designs for cell-free MIMO. Our results show that while tree topologies may suffice for small-scale deployments, they become infeasible as the number of antennas increases. In contrast, with growing network size, the proposed Clos topology performs almost as well as the optimal topology.  \nIndex Terms—Fronthaul, Cell-Free MIMO, Topologies, Optimization  \nI. Introduction  \n\n|  |  |\n| --- | --- |\n| (a) Distributed MIMO (b) Cell-free MIMO |  |\n|  |  |\n| (c) Inter DU (d) Routed Fronthaul |  |\n\nFig. 1. This figure depicts different radio access and fronthaul network designs.  \nThe wireless communications community has long searched for new methods to tackle inter-cell interference. One approach is to distribute the antennas of a BS over the cell area, a so-called distributed MIMO system. A suitable architecture for distributed MIMO is proposed by the ORAN alliance, where the monolithic BS is separated into antenna sites, i.e., radio units (RUs), and a distributed unit (DU) . The RUs handle the radio frequency (RF) processing  \nand are typically located close to the antennas, while the DU acts as processing node responsible for network resource allocation and radio link control. In a distributed MIMO system with network-centric clusters, a UE can be connected to all RUs associated with the DU in a given cell, allowing for increased macrodiversity. Hence, even if the UE is located close to the cell-edge, it will maintain good channel gains with some of the RUs, such that the quality of service inside the cell is distributed more uniformly.  \nIn an ideal user-centric cell-free network, each UE is connected to all surrounding RUs with good channel characteristics. Signals from other RUs not serving the UE are then typically weak and do not cause significant interference. This user-centric formation of RU clusters is the main difference and advantage compared to cell-based systems. The advantages of user-centric cell-free MIMO compared to cellular MIMO and small cell networks have been pointed out in several works [1], [2] .  \nWhile user-centric cell-free MIMO obtains impressive results in the physical layer, it also introduces new challenges to the higher layers in terms of architecture and protocol design. In current deployments, DUs are only indirectly connected through centralized units (CUs), which sit one layer above the DUs. In today’s O-RAN deployments, DUs communicate only via a centralized CU, which limits scalability (Fig. 1b) .  \nTo lower fronthaul load, we envision some local and cluster-level processing, meaning that some functions, such as channel estimation, are carried out at the RUs directly. Additionally, we propose a routed fronthaul network between RUs and DUs (as shown in Figs. 1c and 1d), avoiding CU bottlenecks.  \nA. Related Work  \nWhile the physical layer of cell-free networks has been extensively investigated in recent years (see [1] and references therein), the fronthaul is still very little studied. The vast majority of earlier works consider a centralizedRAN-type network, where the cluster-level processing of all UEs is done at a centralized unit [3], [4], which results in a non-scalable network. Only recently, a few works have been published that study the cluster processor placement at one of multiple DUs [5]–[7] . In [7], the objective of the propos","cbCairfCZvxZOcJM","https://ap.wps.com/l/cbCairfCZvxZOcJM","pdf",2689089,1,6,"English","en",105,"# Introduction\n## Related Work\n## Our Contributions","[{\"question\":\"What methodology is used to evaluate fronthaul performance in the paper?\",\"answer\":\"The work develops a realistic traffic-demand model, studies link-load performance, and explores load optimization through processing node assignment algorithms, then evaluates results across different scenarios.\"}]",1784192681,15,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":77,"head_meta":79,"extra_data":81,"updated_unix":27},"rethinking-fronthaul-topologies-for-cell-free-6g-networks","",{"@graph":35,"@context":76},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/rethinking-fronthaul-topologies-for-cell-free-6g-networks/84091/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-16",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70],{"name":71,"@type":72,"acceptedAnswer":73},"What methodology is used to evaluate fronthaul performance in the paper?","Question",{"text":74,"@type":75},"The work develops a realistic traffic-demand model, studies link-load performance, and explores load optimization through processing node assignment algorithms, then evaluates results across different scenarios.","Answer","https://schema.org",{"og:url":51,"og:type":78,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":80,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":83},[84,88,92,96,101,105,110,113,118,121,125],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":21,"doc_module":4,"doc_module_name":45,"category_name":102,"show_sort_weight":103,"slug":104},"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":45,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":111,"slug":112},30,"research-report",{"id":114,"doc_module":4,"doc_module_name":45,"category_name":115,"show_sort_weight":116,"slug":117},9,"Religion & Spirituality",20,"religion-spirituality",{"id":116,"doc_module":4,"doc_module_name":45,"category_name":119,"show_sort_weight":116,"slug":120},"World Cup","world-cup",{"id":122,"doc_module":4,"doc_module_name":45,"category_name":123,"show_sort_weight":122,"slug":124},10,"Lifestyle","lifestyle",{"id":126,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":97,"slug":128},19,"General","general"]