Without requiring operational costs such as cabling and powering while maintaining reconfigurable phase-shift capability, self-sustainable reconfigurable intelligent surfaces (ssRISs) can be deployed in locations inaccessible to conventional relays or base stations, offering a novel approach to enhance wireless coverage. This study assesses the feasibility of ssRIS deployment by analyzing two harvest-and-reflect (HaR) schemes: element-splitting (ES) and time-splitting (TS). We examine how element requirements scale with key system parameters, transmit power, data rate demands, and outage constraints under both line-of-sight (LOS) and non-line-of-sight (NLOS) ssRIS-to-user equipment (UE) channels. Analytical and numerical results reveal distinct feasibility characteristics. The TS scheme demonstrates better channel hardening gain, maintaining stable element requirements across varying outage margins, making it advantageous for indoor deployments with favorable harvesting conditions and moderate data rates. However, TS exhibits an element requirement that exponentially scales to harvesting difficulty and data rate. Conversely, the ES scheme shows only linear growth with harvesting difficulty, providing better feasibility under challenging outdoor scenarios. These findings establish that TS excels in benign environments, prioritizing reliability, while ES is preferable for demanding conditions requiring operational robustness.

The densification of wireless networks toward fifth- and sixth-generation standards has intensified the demand for reliable high-throughput connectivity in indoor deployment scenarios (IDS), such as aircraft cabins, metro wagons, and stadiums. Although millimeter-wave (mmWave) communication offers the spectral resources needed to meet this demand, its sensitivity to propagation loss and blockages severely limits its performance, particularly in IDS. Metasurfaces have emerged as a promising means of extending mmWave coverage through manipulating the propagation environment. Advanced investigations have been conducted on metasurface-featured system performance enhancement. However, the operating cost, which is a practical and critical concern of metasurface deployment, has received insufficient attention in the literature. Deploying a reconfigurable metasurface in practice requires cabling, power supply, and control infrastructure, costs that represent a real barrier to scalable deployment, particularly in indoor environments like IDS, where infrastructure installation is physically limited or tightly regulated.

This thesis investigates the design of sustainable metasurface-assisted indoor wireless communication systems, placing operating cost alongside performance as a primary design criterion. The work examines different types of metasurfaces that differ in the metasurface gain they provide and the operating cost they incur. By identifying and verifying an optimal design choice among these alternatives, this thesis advances a sustainable metasurface-assisted system that addresses the performance-cost dilemma inherent to IDS deployments.

The first contribution studies the trade-off between operating cost and performance enhancement by optimizing a mixed static metasurface (SMS) and reconfigurable intelligent surface (RIS) deployment in an mmWave IDS. Using a fractional programming penalty-based successive convex approximation (FPPSCA)-based iterative algorithm, the results reveal a diminishing-returns relationship. While replacing two SMSs with RISs already yields a 13 Mbps gain, increasing the RIS count beyond 16 out of 22 surfaces produces less than 1 Mbps of additional gain, confirming that full reconfigurability is unnecessary and motivating a more cost-effective middle-ground solution. The second contribution proposes and evaluates a self-sustainable RIS (ssRIS)-assisted mmWave system for IDS, where ssRIS achieves self-sustainability through power harvesting via a codebook-based element splitting scheme, eliminating the need for cabling and external power. A two-stage iterative algorithm jointly optimizes phase shifts, user equipment (UE)-to-ssRIS associations, and time allocation. The results show that ssRIS outperforms SMS by up to 19.8 Mbps in compact environments, confirming a favorable position within the gain-cost trade-off, with coverage advantages diminishing as deployment distances grow. The third contribution conducts a feasibility study of ssRIS across diverse scenarios, analyzing how element count scales with transmit power, data rate demands, and outage constraints under element splitting (ES) and time switching (TS) schemes. TS benefits from stronger channel hardening under moderate conditions, but scales exponentially with harvesting difficulty, whereas ES scales only linearly, offering greater robustness in challenging environments. Together, these findings provide actionable guidance for practical ssRIS deployment.

Förtätningen av trådlösa nätverk mot femte och sjättegenerationens standarder har intensifierat behovet av tillförlitlig höghastighetskommunikation i inomhusmiljöer med hög användartäthet (IDS), såsom flygplanskabiner, tunnelbanevagnar och arenor. Även om millimetervågskommunikation (mmWave) erbjuder de spektralresurser som krävs för att möta denna efterfrågan, begränsar dess känslighet för utbredningsförluster och blockeringar dess prestanda avsevärt, särskilt i IDS. Metaytor har framträtt som ett lovande verktyg för att utöka mmWave-täckning genom att manipulera utbredningsomgivningen. Avancerade undersökningar har genomförts avseende prestandaförbättring i metayta-baserade system. Driftskostnaden, som utgör ett praktiskt och kritiskt problem vid driftsättning av metaytor, har dock fått otillräcklig uppmärksamhet i litteraturen. Att i praktiken implementera omkonfigurerbara metaytor kräver kablage, strömförsörjning och styrsystem, vilket medför kostnader som utgör ett reellt hinder för skalbar implementering, särskilt i miljöer där fysiska begränsningar eller stränga regleringskrav försvårar infrastrukturinstallation.

Detta avhandlingsarbete undersöker utformningen av hållbara metayta-assisterade trådlösa kommunikationssystem inomhus, där driftskostnad jämställs med prestanda som ett primärt designkriterium. Arbetet undersöker olika typer av metaytor som skiljer sig åt i den metayteförstärkning de erbjuder och den driftskostnad de medför. Genom att identifiera och verifiera ett optimalt designval bland dessa alternativ bidrar denna avhandling till ett hållbart metayta-assisterat system som hanterar prestandakostnadsdilemmat som är inneboende i IDS-miljöer.

Det första bidraget studerar avvägningen mellan den driftskostnad som följer med rekonfigurerbarheten och motsvarande prestandaförbättring, genom att optimera en blandad driftsättning av statisk metayta (SMS) och rekonfigurerbar intelligent yta (RIS) i ett mmWave IDS. Med hjälp av en algoritm baserad på successiv konvex approximation med genomförbar punktsökning (FPPSCA) påvisar resultaten ett avtagande avkastningsförhållande. Redan ersättningen av två SMS med RIS ger en vinst på 13 Mbps, men att öka antalet RIS utöver 16 av 22 ytor ger mindre än 1 Mbps ytterligare vinst, vilket bekräftar att full rekonfigurabilitet är onödig och motiverar sökandet efter en mer kostnadseffektiv mellanlösning. Det andra bidraget föreslår och utvärderar ett självhållbar rekonfigurerbar intelligent yta (ssRIS)-assisterat mmWave-system för IDS, där ssRIS uppnår självhållbarhet genom energiinsamling via ett kodbruksbaserat elementdelningsschema, vilket eliminerar behovet av kablage och extern strömförsörjning. En tvåstegs iterativ algoritm optimerar gemensamt fasskift, användarutrustning (UE)-till-ssRIS-associeringar och tidsallokering. Resultaten visar att ssRIS överträffar SMS med upp till 19,8 Mbps i kompakta miljöer, vilket bekräftar en fördelaktig position inom prestandakostnadsavvägningen, medan täckningsfördelen minskar med ökande driftsättningsavstånd. Det tredje bidraget genomför en genomförbarhetsstudie av ssRIS i varierande scenarier, och analyserar hur elementantalet skalas med sändeffekt, datahastighetsrerav och avbrottsbegränsningar under elementdelning (ES)- och tidsdelning (TS)-scheman. TS gynnas av starkare kanalhärdning under måttliga förhållanden, men dess elementantal växer exponentiellt med insamlingssvårigheten, medan ES endast skalar linjärt, vilket ger större robusthet i utmanande miljöer. Sammantaget ger dessa resultat handlingsbara riktlinjer för praktisk driftsättning av ssRIS.

Millimeter-wave channel modeling for airplanes, trains, and other in-vehicle environments can be considered jointly as different variations of a general site, namely an indoor dense space (IDS). In this work, by using ray-tracing (RT) simulations, we compare the effect of frame material, user density, and geometry on the channel characteristics at 28, 39, and 60 GHz bands. We observe that temporal and spatial parameters in IDS have unique distributions some depending on the transmitter (TX)-receiver (RX) separation in comparison to the indoor office (IO) channel model. The frame material is the main determining factor of the channel characteristics, while variations in frequency bands and geometries have only a minor impact. We extend our channel modeling effort to MIMO deployment analysis to compare the validity of the proposed model in terms of coverage and spectral efficiency with the IO model. Several dominant angular intervals in the channel cause five times higher spectral efficiency gained by digital beamforming (BF) in comparison to analog BF. We observe that the path loss in IDS is more severe compared with IO, resulting in at least a 50% reduction in the coverage area.

In this paper, we investigate how metasurfaces can be deployed to deliver high data rates in a millimeter-wave (mmWave) indoor dense space with many blocking objects. These surfaces can either be static metasurfaces (SMSs) that reflect with fixed phase-shifts or reconfigurable intelligent surfaces (RISs) that can reconfigure their phase-shifts to the currently served user. The latter comes with an increased power, cabling, and signaling cost. To see how reconfigurability affects the network performance, we propose an iterative algorithm based on the feasible point pursuit successive convex approximation method. We jointly optimize the types and phase-shifts of the surfaces and the time portion allocated to each user equipment to maximize the minimum data rate achieved by the network. Our numerical results demonstrate that the minimum data rate improves as more RISs are introduced but the gain diminishes after some point. Therefore, introducing more reconfigurability is not always necessary. Another result shows that to reach the same data rate achieved by using 22 SMSs, at least 18 RISs are needed. This suggests that when it is costly to deploy many RISs, as an inexpensive alternative solution, one can reach the same data rate just by densely deploying more SMSs.

In this work, we consider the deployment of reconfigurable intelligent surfaces (RISs) to extend the coverage of a millimeter-wave (mmWave) network in indoor dense spaces. We first integrate RIS into ray-tracing simulations to realistically capture the propagation characteristics, then formulate a non-convex optimization problem that minimizes the number of RISs under rate constraints. We propose a feasible point pursuit and successive convex approximation-based algorithm, which solves the problem by jointly selecting the RIS locations, optimizing the RIS phase-shifts, and allocating time resources to user equipments (UEs). The numerical results demonstrate substantial coverage extension by using at least four RISs, and a data rate of 130 Mbit/s is guaranteed for UEs in the considered area of an airplane cabin.

In the design of a metasurface-assisted system for indoor environments, it is essential to take into account not only the performance gains and coverage extension provided by the metasurface but also the operating costs brought by its reconfigurability, such as powering and cabling. These costs can present challenges, particularly in indoor dense spaces (IDSs). A self-sustainable reconfigurable intelligent surface (ssRIS), which retains reconfigurability unlike a static metasurface (SMS), achieves a lower operating cost than a reconfigurable intelligent surface (RIS) by being self-sustainable through power harvesting. In this paper, in order to find a better trade-off between metasurface gain, coverage, and operating cost, the design and performance of an ssRIS-assisted indoor mmWave communication system are investigated. We simplify the use of the ssRIS by considering a preset-based element splitting scheme for maintaining self-sustainability and the formation of coverage groups by associating ssRISs with the closest user equipments (UEs). We propose a two-stage iterative algorithm to maximize the minimum data rate by jointly deciding the association between the UEs and the ssRISs, the phase shifts of the ssRISs, and allocating time resources for each UE. The non-convex optimization problem is tackled using the feasible point pursuit successive convex approximation method. To understand the best scenario for using ssRIS, the resulting performance is compared with that achieved with RIS and SMS. Our numerical results indicate that ssRISs are best utilized in a small environment where self-sustainability is easier to achieve when the budget for operating costs is tight.