294 research outputs found
Modeling and Analysis of Massive Low Earth Orbit Communication Networks
Non-terrestrial networks are foreseen as a crucial component for developing 6th generation (6G) of wireless cellular networks by many telecommunication industries. Among non-terrestrial networks, low Earth orbit (LEO) communication satellites have shown a great potential in providing global seamless coverage for remote and under-served regions where conventional terrestrial networks are either not available or not economically justifiable to deploy. In addition, to the date of writing this summary, LEO communication networks have became highly commercialized with many prominent examples, compared to other non-terrestrial networks, e.g., high altitude platforms (HAPs) which are still in prototyping stage.
Despite the rapid promotion of LEO constellations, theoretical methodologies to study the performance of such massive networks at large are still missing from the scientific literature. While commercial plans must obviously have been simulated before deployment of these constellations, the deterministic and network-specific simulations rely on instantaneous positions of satellites and, consequently, are unable to characterize the performance of massive satellite networks in a generic scientific form, given the constellation parameters.
In order to address this problem, in this thesis, a generic tractable approach is proposed to analyze the LEO communication networks using stochastic geometry as a central tool. Firstly, satellites are modeled as a point process which enables using the mathematics of stochastic geometry to formulate two performance metrics of the network, namely, coverage probability and data rate, in terms of constellation parameters. The derivations are applicable to any given LEO constellation regardless of satellites’ actual locations on orbits. Due to specific geometry of satellites, there is an inherent mismatch between the actual distribution of satellites and the point processes that are used to model their locality. Secondly, different approaches have thus been investigated to eliminate this modeling error and improve the accuracy of the analytical derivations.
The results of this research are published in seven original publications which are attached to this summary. In these publications, coverage probability and average achievable data rate of LEO satellite networks are derived for several communication scenarios in both uplink and downlink directions under different propagation models and user association techniques. Moreover, the analysis was generalized to cover the performance analysis of a multi-altitude constellation which imitates the geometry of some well-known commercial constellations with satellites orbiting on multiple altitude levels. While direct communication between the satellites and ground terminals is the main studied communication scenario in this thesis, the performance of a LEO network as a backhaul for aerial platforms is also addressed and compared with terrestrial backhaul networks.
Finally, all analytical derivations, obtained from stochastic modeling of the LEO constellations, are verified through Monte Carlo simulations and compared with actual simulated constellations to ensure their accuracy. Through the numerical results, the performance metrics are evaluated in terms of different constellation parameters, e.g., altitude, inclination angle, and total number of satellites, which reveals their optimal values that maximize the capacity and/or coverage probability. Therefore, other than performance analysis, several insightful guidelines can be also extracted regarding the design of LEO satellite networks based on the numerical results.
Stochastic modeling of a LEO satellite network, which is proposed for the first time ever in this thesis, extends the application of stochastic geometry in wireless communication field from planar two-dimensional (2D) networks to highly heterogeneous three-dimensional (3D) spherical networks. In fact, the results show that stochastic modeling can also be utilized to precisely model the networks with deterministic nodes’ locations and specific distribution of nodes over the Euclidean space. Thus, the proposed methodology reported herein paves the way for comprehensive analytical understanding and generic performance study of heterogeneous massive networks in the future
Komunikace na milimetrových vlnách v 5G a dalších sítích: Nové systémové modely a analýza výkonnosti
The dissertation investigates different network models, focusing on three important features for next generation cellular networks with respect to millimeter waves (mmWave) communications: the impact of fading and co-channel interference (CCI), energy efficiency, and spectrum efficiency.
To address the first aim, the dissertation contains a study of a non-orthogonal multiple access (NOMA) technique in a multi-hop relay network which uses relays that harvest energy from power beacons (PB). This part derives the exact throughput expressions for NOMA and provides a performance analysis of three different NOMA schemes to determine the optimal parameters for the proposed system’s throughput. A self-learning clustering protocol (SLCP) in which a node learns its neighbor’s information is also proposed for determining the node density and the residual energy used to cluster head (CH) selection and improve energy efficiency, thereby prolonging sensor network lifetime and gaining higher throughput.
Second, NOMA provides many opportunities for massive connectivity at lower latencies, but it may also cause co-channel interference by reusing frequencies. CCI and fading play a major role in deciding the quality of the received signal. The dissertation takes into account the presence of η and µ fading channels in a network using NOMA. The closed-form expressions of outage probability (OP) and throughput were derived with perfect successive interference cancellation (SIC) and imperfect SIC. The dissertation also addresses the integration of NOMA into a satellite communications network and evaluates its system performance under the effects of imperfect channel state information (CSI) and CCI.
Finally, the dissertation presents a new model for a NOMA-based hybrid satellite-terrestrial relay network (HSTRN) using mmWave communications. The satellite deploys the NOMA scheme, whereas the ground relays are equipped with multiple antennas and employ the amplify and forward (AF) protocol. The rain attenuation coefficient is considered as the fading factor of the mmWave band to choose the best relay, and the widely applied hybrid shadowed-Rician and Nakagami-m channels characterize the transmission environment of HSTRN. The closed-form formulas for OP and ergodic capacity (EC) were derived to evaluate the system performance of the proposed model and then verified with Monte Carlo simulations.Dizertační práce zkoumala různé modely sítí a zaměřila se na tři důležité vlastnosti pro buňkové sítě příští generace s ohledem na mmW komunikace, kterými jsou: vliv útlumu a mezikanálového rušení (CCI), energetická účinnost a účinnost spektra.
Co se týče prvního cíle, dizertace obsahuje studii techniky neortogonálního vícenásobného přístupu (NOMA) v bezdrátové multiskokové relay síti využívající získávání energie, kde relay uzly sbírají energii z energetických majáků (PB). Tato část přináší přesné výrazy propustnosti pro NOMA a analýzu výkonnosti se třemi různými schématy NOMA s cílem určit optimální parametry pro propustnost navrženého systému. Dále byl navržen samoučící se shlukovací protokol (SLCP), ve kterém se uzel učí informace o sousedech, aby určil hustotu uzlů a zbytkovou energii použitou k výběru hlavy shluku CH pro zlepšení energetické účinnosti, čímž může prodloužit životnost sensorové sítě a zvýšit propustnost.
Za druhé, přístup NOMA poskytl mnoho příležitostí pro masivní připojení s nižší latencí, NOMA však může způsobovat mezikanálové rušení v důsledku opětovného využívání kmitočtů. CCI a útlum hrají klíčovou roli při rozhodování o kvalitě přijímaného signálu. V této dizertace je brána v úvahu přítomnost η a µ útlumových kanálů v síti užívající NOMA. Odvozeny jsou výrazy v uzavřené formě pro pravděpodobnost výpadku (OP) a propustnost s dokonalým postupným rušením rušení (SIC) a nedokonalým SIC. Dále se dizertace zabývá integrací přístupu NOMA do satelitní komunikační sítě a vyhodnocuje výkonnost systému při dopadech nedokonalé informace o stavu kanálu (CSI) a CCI.
Závěrem disertační práce představuje nový model pro hybridní družicově-terestriální přenosovou síť (HSTRN) založenou na NOMA vícenásobném přístupu využívající mmWave komunikaci. Satelit využívá NOMA schéma, zatímco pozemní relay uzly jsou vybaveny více anténami a aplikují protokol zesilování a předávání (AF). Je zaveden srážkový koeficient, který je uvažován jako útlumový faktor mmWave pásma při výběru nejlepšího relay uzlu. Samotné přenosové prostředí HSTRN je charakterizováno pomocí hybridních Rician a Nakagami-m kanálů. Vztahy pro vyhodnocení výkonnosti systému navrženého modelu vyjadřující ergodickou kapacitu (EC) a pravděpodobnost ztrát (OP) byly odvozeny v uzavřené formě a následně ověřeny pomocí simulační numerické metody Monte Carlo.440 - Katedra telekomunikační technikyvyhově
Performance Analysis of RIS-assisted MIMO-OFDM Cellular Networks Based on Matern Cluster Processes
Reconfigurable Intelligent Surfaces (RIS) technology are a promising
physical-layer candidate for sixth-generation (6G) cellular networks. This
paper provides a system-level performance assessment of RIS-assisted
multi-input multi-output (MIMO) cellular networks in terms of downlink coverage
probability and ergodic rate. To capture the inherent randomness in the spatial
deployments of both Base Stations (BSs) and RISs, we propose a new stochastic
geometry model for such systems based on the Matern Cluster Process (MCP). This
model consists in randomly distributed RISs around BSs, whose placement is
according to a Poisson Point Process (PPP). The RISs provide the multipath
diversity and the multiple antenna receiver provide the antenna diversity. The
system is assumed to use the orthogonal frequency division multiplexing (OFDM)
technique to modulate the former and employ the maximal ratio combining (MRC)
technique at the receiver to exploit the latter. We show that the coverage
probability and the ergodic rate can be evaluated when considering RISs operate
as batched powerless beamformers. The resulting analytical expressions provide
a generic methodology to evaluate the impact of key RIS-related parameters,
such as the size of RIS and the density of nodes, on system level performance.
Numerical evaluations of the analytical expressions and Monte-Carlo simulations
jointly validate the proposed analytical approach and provide valuable insights
into the design of future RIS-assisted radio cellular networks
Channel parameter tuning in a hybrid Wi-Fi-Dynamic Spectrum Access Wireless Mesh Network
This work addresses Channel Assignment in a multi-radio multi-channel (MRMC) Wireless Mesh Network (WMN) using both Wi-Fi and Dynamic Spectrum Access (DSA) spectrum bands and standards. This scenario poses new challenges because nodes are spread out geographically so may have differing allowed channels and experience different levels of external interference in different channels. A solution must meet two conflicting requirements simultaneously: 1) avoid or minimise interference within the network and from external interference sources, and 2) maintain connectivity within the network. These two requirements must be met while staying within the link constraints and the radio interface constraints, such as only assigning as many channels to a node as it has radios. This work's original contribution to the field is a unified framework for channel optimisation and assignment in a WMN that uses both DSA and traditional Wi-Fi channels for interconnectivity. This contribution is realised by providing and analysing the performance of near-optimal Channel Assignment (CA) solutions using metaheuristic algorithms for the MRMC WMNs using DSA bands. We have created a simulation framework for evaluating the algorithms. The performance of Simulated Annealing, Genetic Algorithm, Differential Evolution, and Particle Swarm Optimisation algorithms have been analysed and compared for the CA optimisation problem. We introduce a novel algorithm, used alongside the metaheuristic optimisation algorithms, to generate feasible candidate CA solutions. Unlike previous studies, this sensing and CA work takes into account the requirement to use a Geolocation Spectrum Database (GLSD) to get the allowed channels, in addition to using spectrum sensing to identify and estimate the cumulative severity of both internal and external interference sources. External interference may be caused by other secondary users (SUs) in the vicinity or by primary transmitters of the DSA band whose emissions leak into adjacent channels, next-toadjacent, or even into further channels. We use signal-to-interference-plus-noise ratio (SINR) as the optimisation objective. This incorporates any possible source or type of interference and makes our method agnostic to the protocol or technology of the interfering devices while ensuring that the received signal level is high enough for connectivity to be maintained on as many links as possible. To support our assertion that SINR is a reasonable criterion on which to base the optimisation, we have carried out extensive outdoor measurements in both line-of-sight and wooded conditions in the television white space (TVWS) DSA band and the 5 GHz Wi-Fi band. These measurements show that SINR is useful as a performance measure, especially when the interference experienced on a link is high. Our statistical analysis shows that SINR effectively differentiates the performance of different channels and that SINR is well correlated with throughput and is thus a good predictor of end-user experience, despite varying conditions. We also identify and analyse the idle times created by Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) contention-based Medium Access Control (MAC) operations and propose the use of these idle times for spectrum sensing to measure the SINR on possible channels. This means we can perform spectrum sensing with zero spectrum sensing delay experienced by the end user. Unlike previous work, this spectrum sensing is transparent and can be performed without causing any disruption to the normal data transmission of the network. We conduct Markov chain analysis to find the expected length of time of a sensing window. We also derive an efficient minimum variance unbiased estimator of the interference plus noise and show how the SINR can be found using this estimate. Our estimation is more granular, accurate, and appropriate to the problem of Secondary User (SU)-SU coexistence than the binary hypothesis testing methods that are most common in the literature. Furthermore, we construct confidence intervals based on the probability density function derived for the observations. This leads to finding and showing the relationships between the number of sampling windows and sampling time, the interference power, and the achievable confidence interval width. While our results coincide with (and thus are confirmed by) some key previous recommendations, ours are more precise, granular, and accurate and allow for application to a wider range of operating conditions. Finally, we present alterations to the IEEE 802.11k protocol to enable the reporting of spectrum sensing results to the fusion or gateway node and algorithms for distributing the Channel Assignment once computed. We analyse the convergence rate of the proposed procedures and find that high network availability can be maintained despite the temporary loss of connectivity caused by the channel switching procedure. This dissertation consolidates the different activities required to improve the channel parameter settings of a multi-radio multi-channel DSA-WMN. The work facilitates the extension of Internet connectivity to the unconnected or unreliably connected in rural or peri-urban areas in a more cost-effective way, enabling more meaningful and affordable access technologies. It also empowers smaller players to construct better community networks for sharing local content. This technology can have knock-on effects of improved socio-economic conditions for the communities that use it
Application of diverse techniques to reduce the impact of α-k-μ-g and k-μ-g feding on wireless performance
U ovoj tezi izvršena je analiza performansi bežičnog prenosa_signala_u_prisustvu α-k-μ-g i k-μ-g fedinga_u_kanalu. Izvedeni_su_izrazi u zatvorenom obliku za funkcije_gustine verovatnoće_raspodele i kumulativnu_funkciju_raspodele odnosa signal-šum (SNR) na prijemu kada se bežični prenos vrši kroz kanale sa fedingom. Primenjene_su_standardne_mere_kvaliteta odnosno_performansi_primljenog_signala, kao što su verovatnoća otkaza (OP - Outage probability) i srednji broj osnih preseka (LCR- Level Crossing Rate), koje su_dobijene za_slučajeve_prenosa u funkciji različitih vrednosti parametara sistema. Poboljšanje ovih mera performansi analizirano je za slučaj kada su kada su na prijemnoj_strani_korišćene_prostorne diverziti tehnike_kombinovanja. U tezi je razmatrano nekoliko tehnika_kombinovanja_signala na prijemu. Korišćene_su_tehnika selektivnog_kombinovanja_signala (SC-Selection Combining) i tehnika_kombinacija_signala_sa_maksimalnim_odnosom (MRC-Maximal Ratio Combining), u cilju_procene_mogućnosti_slabljenja_uticaja fedinga pri prenosu signala u kanalu. Izvršena je i analiza_istovremenog_uticaja pojavljive_fedinga i efekta_senke pri bežičnom_prenosu_signala, a razmatrane su mogućnosti_istovremene_primene tehnika makro-diverziti_kombinovanja gore navedenih prostornih diverziti tehnika, kako_bi_se_smanjili ovi štetni efekti uticaja smetnji i poboljšao_kvalitet_signala_na_prijemnoj_strani. Rezultati_dobijeni u_ovoj_tezi, pokazuju da se primenom_pristupa_predloženih u disertaciji_može postići smanjenje štetnih efekata α-k-μ-g i k-μ-g fedinga u kanalu pri_različitim_scenarijima_bežičnog prenosa
A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches
Wireless communication networks have been witnessing an unprecedented demand
due to the increasing number of connected devices and emerging bandwidth-hungry
applications. Albeit many competent technologies for capacity enhancement
purposes, such as millimeter wave communications and network densification,
there is still room and need for further capacity enhancement in wireless
communication networks, especially for the cases of unusual people gatherings,
such as sport competitions, musical concerts, etc. Unmanned aerial vehicles
(UAVs) have been identified as one of the promising options to enhance the
capacity due to their easy implementation, pop up fashion operation, and
cost-effective nature. The main idea is to deploy base stations on UAVs and
operate them as flying base stations, thereby bringing additional capacity to
where it is needed. However, because the UAVs mostly have limited energy
storage, their energy consumption must be optimized to increase flight time. In
this survey, we investigate different energy optimization techniques with a
top-level classification in terms of the optimization algorithm employed;
conventional and machine learning (ML). Such classification helps understand
the state of the art and the current trend in terms of methodology. In this
regard, various optimization techniques are identified from the related
literature, and they are presented under the above mentioned classes of
employed optimization methods. In addition, for the purpose of completeness, we
include a brief tutorial on the optimization methods and power supply and
charging mechanisms of UAVs. Moreover, novel concepts, such as reflective
intelligent surfaces and landing spot optimization, are also covered to capture
the latest trend in the literature.Comment: 41 pages, 5 Figures, 6 Tables. Submitted to Open Journal of
Communications Society (OJ-COMS
Performance Analysis of LEO Satellite-Based IoT Networks in the Presence of Interference
This paper explores a star-of-star topology for an internet-of-things (IoT)
network using mega low Earth orbit constellations where the IoT users broadcast
their sensed information to multiple satellites simultaneously over a shared
channel. The satellites use amplify-and-forward relaying to forward the
received signal to the ground station (GS), which then combines them coherently
using maximal ratio combining. A comprehensive outage probability (OP) analysis
is performed for the presented topology. Stochastic geometry is used to model
the random locations of satellites, thus making the analysis general and
independent of any constellation. The satellites are assumed to be visible if
their elevation angle is greater than a threshold, called a mask angle.
Statistical characteristics of the range and the number of visible satellites
are derived for a given mask angle. Successive interference cancellation (SIC)
and capture model (CM)-based decoding schemes are analyzed at the GS to
mitigate interference effects. The average OP for the CM-based scheme, and the
OP of the best user for the SIC scheme are derived analytically. Simulation
results are presented that corroborate the derived analytical expressions.
Moreover, insights on the effect of various system parameters like mask angle,
altitude, number of satellites and decoding order are also presented. The
results demonstrate that the explored topology can achieve the desired OP by
leveraging the benefits of multiple satellites. Thus, this topology is an
attractive choice for satellite-based IoT networks as it can facilitate burst
transmissions without coordination among the IoT users.Comment: Submitted to IEEE IoT Journa
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