In Earth-to-Space communications, well-known propagation effects such as path loss and atmospheric loss can lead to fluctuations in the strength of the communications link between a satellite and its ground station. Additionally, a less-often considered effect of shadowing due to the geometry of the satellite and its solar panels can also lead to link degradation. As a result of these anticipated channel impairments, NASA's communication links have been traditionally designed to handle the worst-case impact of these effects through high link margins and static, lower rate, modulation formats. This thesis first characterizes the propagation environment experienced by a software-defined radio on the NASA SCaN Testbed through a full link-budget analysis. Then, the following chapters propose, design, and model a link adaptation algorithm to provide an improved trade-off between data rate and link margin through varying the modulation format as the received signal-to-noise ratio fluctuates. / Master of Science

<p>This master thesis has been done at Enea Epact AB. The purpose of this thesis is to develop and implement a Link Quality Control algorithm for GPRS/EPGRS in the current testing tool. A Link Quality Control (LQC) shall take quality values from mobile stations and base stations and decide a codingsscheme that opimizes the throughput of data. </p><p>The Advantage with LQC is that it adapts the used coding scheme to the channel quality. If the channel quality is too bad for the used coding scheme, a slower coding scheme with more redundancy should be selected. On the other hand, if the channel quality is too good for the used coding scheme, LQC should recommend a faster coding scheme with less redundancy. </p><p>The testing tool is now using a static coding schme that doesn’t change during a data session. An LQC is therefore necessary for better simulation of the traffic and to make the tests more real.</p>

In the LTE mobile system, all cells use the same set of frequencies. This means that a user could experience interference from other cells. A method that has been studied in order to reduce this interference and thereby increase data rate or system throughput is to coordinate scheduling between cells. Good results of this have been found in different studies. However, the interference is generally assumed to be known. Studies using estimated interference and simulating more than one cluster of cells have found almost no gain. This thesis will focus on how to use information from coordinated scheduling and other traffic estimates to do better interference estimation and link adaption. The suggested method is to coordinate larger clusters and use the coordination information, as well as estimates of which cells will be transmitting, to make estimates of interference from other cells. The additional information from interference estimation is used in the link adaptation. Limitations in bandwidth of the backhaul needed to send data between cells are considered, as well as the delay it may introduce. A limitation of the scope is that MIMO or HetNet scenarios have not been simulated. The suggested method for interference estimation and link adaptation have been implemented and simulated in a system simulator. The method gives a less biased estimate of SINR, but there are no gains in user bit rate. The lesser bias is since the method is better at predicting high SINR than the base estimate is. The lack of gains regarding user bit rate may result from the fact that in the studied scenarios, users where not able to make use of the higher estimated SINR since the base estimate is already high. The conclusion is that the method might be useful in scenarios where there are not full load, but the users either have bad channel quality or are able to make use of very high SINR. Such scenarios could be HetNet or MIMO scenarios, respectively.

Link adaptation is an important component of contemporary wireless networks that require high spectral efficiency and service a variety of network applications/configurations. By exploiting information about the wireless channel, link adaptation strategically selects wireless communication transmission parameters in real-time to optimize performance. Link adaptation in practice has proven challenging due to impairments outside system models and analytical intractability in modern broadband networks with multiple antennas (MIMO), orthogonal frequency division multiplexing (OFDM), forward error correction, and bit-interleaving. The objective of this dissertation is to provide simple and flexible link adaptation algorithms with few link model assumptions that are amenable to modern wireless networks. First, a complete design and analysis of supervised learning for link adaptation in MIMO-OFDM is provided. This includes the construction of a publicly available data set, a new frame error rate bound leading to a new feature set, and IEEE 802.11n performance evaluation to verify that my design outperforms existing link quality metrics. Next, two supervised learning classification algorithms are designed to exploit information collected from packets transmitted and received over standard links in real time: database learning with nearest neighbor classifiers and support vector machines. Algorithms are also proposed to preserve diversity of feature sets in the database and to allow learning algorithms to seek out more information about the network. Finally, link adaptation with supervised learning is applied to MIMO-OFDM systems where the modulation order may be adapted per-stream. This leads to the analysis of the ordered SNR per stream and its connection to the cumulative distribution function of SNR on each stream. Decoupled link adaptation algorithms, which significantly reduce the complexity of non-uniform link adaptation algorithms, are proposed. New analysis of non-uniform link adaptation shows that the performance of decoupled link adaptation algorithms converge to the performance of joint (optimal) link adaptation algorithms as the number of modulation and coding options per-stream increase. This guides the construction of future standards to reduce the complexity of link adaptation in MIMO-OFDM. / text

This master thesis has been done at Enea Epact AB. The purpose of this thesis is to develop and implement a Link Quality Control algorithm for GPRS/EPGRS in the current testing tool. A Link Quality Control (LQC) shall take quality values from mobile stations and base stations and decide a codingsscheme that opimizes the throughput of data. The Advantage with LQC is that it adapts the used coding scheme to the channel quality. If the channel quality is too bad for the used coding scheme, a slower coding scheme with more redundancy should be selected. On the other hand, if the channel quality is too good for the used coding scheme, LQC should recommend a faster coding scheme with less redundancy. The testing tool is now using a static coding schme that doesn’t change during a data session. An LQC is therefore necessary for better simulation of the traffic and to make the tests more real.

Abstract This thesis seeks to develop a robust semi-analytical performance prediction method for an advanced iterative receiver that processes spatially multiplexed signals that have propagated through frequency-selective receive correlated multiple-input multiple-output (MIMO) wireless communication channels. In a change of perspective, the proposed performance prediction methods are applied at the transmitter, which seeks to attain a target frame error rate (FER) either by adaptive power control or by adaptive modulation and coding (AMC). The performance prediction scheme utilises the statistical properties of the channel—namely noise variance, number of separable propagation paths and the eigenvalues of the receive correlation matrix—to predict the signal-to-interference-plus-noise ratio (SINR) at the output of a frequency domain soft interference cancellation minimum mean square error equaliser. The SINR distribution is used to derive the distribution of the variance of the log-likelihood ratios (LLRs) at the output of a soft symbol-to-bit demapper. Mutual information transfer charts establish a bijective relationship between the variance of the LLRs and mutual information. A 3rd Generation Partnership Project compliant turbo code is assumed. Since the decoder operates independently from the channel, its extrinsic information transfer (EXIT) charts can be simulated in advance. By utilising the approximate LLR variance distribution of the demapped equaliser output, it is possible to evaluate the probability of an intersection between an equaliser chart associated with a random channel realisation and a fixed decoder chart. This probability provides the FER. Since the proposed performance prediction method does not require any instantaneous channel state information, it can be applied at the transmitter side as a robust link adaptation scheme. In adaptive transmission power control, the modulation order and code rate are fixed. By iteratively adjusting transmission power, the transmitter attempts to find an equaliser output LLR variance distribution that reaches a specified target FER. In AMC, transmission power is fixed. The equaliser output's LLR variance distribution is determined by the modulation order, while the decoder chart's position is determined by the code rate. The transmitter iteratively adjusts the code rate and attempts to find a modulation order and code rate pairing that reaches the target FER. For vertically encoded spatially multiplexed systems, the adaptive transmission power control and AMC schemes are complemented by adaptive repeat redundancy and incremental redundancy hybrid automatic repeat request (HARQ) techniques, respectively. / Tiivistelmä Työn tavoitteena on kehittää luotettava semianalyyttinen suorituskyvyn ennustusmenetelmä tehokkaalle iteratiiviselle vastaanottimelle, joka käsittelee taajuusselektiivisen, vastaanotinpäässä tilakorreloituneen moniantennikanavan kautta kulkeneita tilakanavoituja signaaleja. Toisessa vaiheessa esitettyjä ennustusmenetelmiä hyödynnetään mukauttamalla lähetystehoa tai modulaatioastetta ja koodisuhdetta (adaptive modulation and coding [AMC]), samalla säilyttäen tavoitteeksi asetetun kehysvirhesuhteen (frame error rate [FER]). Suorituskyvyn ennustusmenetelmä hyödyntää kanavan tilastollisia ominaisuuksia – kohinan varianssia, eroteltavien etenemispolkujen lukumäärää sekä vastaanottimen korrelaatiomatriisin ominaisarvoja – ennustaakseen signaali–kohina-plus-interferenssisuhteen (signal-to-interference-plus-noise ratio [SINR]) jakauman taajuustasossa toimivan, häiriötä poistavan pienimmän keskineliösumman kanavakorjaimen lähdössä. SINR-jakaumasta johdetaan pehmän symboleista biteiksi -muunnoksen jälkeisten logaritmisten bittitodennäköisyyksien suhdelukujen (log-likelihood ratio [LLR]) jakauma. Keskinäisinformaation siirroskartat perustuvat LLR:ien varianssin sekä keskinäisinformaation väliseen bijektiivisyyteen. Informaatio on kanavakoodattu 3rd Generation Partnership Project -standardin mukaisella turbokoodilla. Turbodekooderin toiminta on kanavasta riippumatonta, joten dekooderin lisäinformaation siirroskartat (extrinsic information transfer [EXIT] charts) voidaan simuloida itsenäisesti. Hyödyntämällä kanavakorjaimen lähdön pehmeiden bittipäätösten LLR:ien varianssin jakaumaa, on mahdollista arvioida millä todennäköisyydellä korjaimen satunnaisen kanavarealisaation siirroskartta leikkaa dekooderin siirroskartan. Tämä todennäköisyys voidaan tulkita kehysvirhesuhteeksi. Koska suorituskyvyn ennustusmenetelmä ei vaadi hetkellistä tietoa kanavan tilasta, sitä voidaan hyödyntää lähetyksen mukautuksessa. Mukautuvassa tehonsäädössä modulaatio ja koodisuhde eivät muutu. Lähetin pyrkii iteratiivisella tehonsäädöllä löytämään korjaimen lähdölle LLR-jakauman, joka tuottaa halutun kehysvirhesuhteen. Mukautuvassa modulaation ja koodisuhteen valinnassa lähetysteho säilyy vakiona. Modulaatioaste vaikuttaa korjaimen lähdön LLR-jakaumaan ja koodisuhde dekooderin siirroskartan muotoon. Iteratiivisesti koodisuhdetta säätämällä lähetin pyrkii löytämään modulaation ja koodisuhteen yhdistelmän, joka saavuttaa tavoitellun kehysvirhesuhteen. Vertikaalisesti tilakanavoiduissa järjestelmissä mukautuvaa tehonsäätöä täydennetään lähetystehoa mukauttavilla uudellenlähetyksillä, kun taas mukautuvaa modulaation ja koodisuhteen valintaa täydennetään puolestaan koodisuhdetta pienentävillä automattisilla uudelleenlähetyspyynnöillä (hybrid automatic repeat request [HARQ]).

The application area of Fifth Generation New Radio (5G-NR) called Ultra-Reliable and Low-Latency Communication (URLLC) requires a reliability, the probability of receiving and decoding a data packet correctly, of 1 - 10^5. For this requirement to be fulfilled in a resource-efficient manner, it is necessary to have a good estimation of extremely low quan- tiles of the channel quality distribution, so that appropriate resources can be distributed to users of the network system.  This study proposes and evaluates two methods for estimating extreme quantiles of the downlink channel quality distribution, linear quantile regression and Quantile Regression Neural Network (QRNN). The models were trained on data from Ericsson’s system-level radio network simulator, and evaluated on goodness of fit and resourcefulness. The focus of this study was to estimate the quantiles 10^2, 10^3 and 10^4 of the distribution.  The results show that QRNN generally performs better than linear quantile regression in terms of pseudoR2, which indicates goodness of fit, when the sample size is larger. How- ever, linear quantile regression was more effective for smaller sample sizes. Both models showed difficulty estimating the most extreme quantiles. The less extreme quantile to esti- mate, the better was the resulting pseudoR2-score. For the largest sample size, the resulting pseudoR2-scores of the QRNN was 0.20, 0.12 and 0.07, and the scores of linear quantile regression was 0.16, 0.10 and 0.07 for the respective quantiles 10^2, 10^3 and 10^4.  It was shown that both evaluated models were significantly more resourceful than us- ing the average of the 50 last measures of channel quality subtracted with a fixed back-off value as a predictor. QRNN had the most optimistic predictions. If using the QRNN, theo- retically, on average 43% more data could be transmitted while fulfilling the same reliability requirement than by using the fixed back-off value.

The IEEE 802.11 standards define several transmission rates that can be used at the physical layer to adapt the transmission rate to channel conditions. This dynamic adaptation attempts to improve the performance in Wireless LAN (WLAN) and hence can have impact on the Quality of Service (QoS) perceived by the users. In this work we present the design and implementation of several new link adaptation (LA) algorithms. The performance of the developed algorithms is tested and compared against some existing algorithms such as Minstrel as well as an ideal LA. The evaluation is carried out in a network system simulator that models all the pro- cedures needed for the exchange of data frames according to the 802.11 standards. Different scenarios are used to simulate various realistic conditions. In particular, the Clear Channel Assessment Threshold (CCAT) is modified in the scenarios and the impact of its modification is also assessed. The algorithms are tested under identical environments to ensure that the experiments are controllable and repeatable. For each algorithm the mean and 5th percentile throughput are measured under different traffic loads to evaluate and compare the performance of the different algorithms. The tradeoff between signaling overhead and performance is also evaluated. It was found that the proposed link adaptation schemes achieved higher mean through- put than the Minstrel algorithm. We also found that the performance of some of the proposed schemes is close to that of the ideal LA. / IEEE 802.11-standarderna definierar flera överföringshastigheter som kan användas vid det fysiska skiktet för att anpassa överföringshastigheten till kanal förhållanden. Denna dynamiska anpassning försöker förbättra prestandan i wireless LAN (WLAN) och därmed kan ha inverkan på Quality of Service (QoS) uppfattas av användarna. I detta examensarbete presenterar vi utformningen och genomförandet av flera ny link adaptation (LA) algoritmer. Prestandan hos de utvecklade algoritmer testas och jämförs med vissa befintliga algoritmer så som Minstrel liksom en ideal LA. Utvärderingen genomförs i ett nätverkssystem simulator som ger alla de förfaranden som behövs för utbyte av dataramar enligt 802.11-standarderna. Olika scenarier används för att simulera olika realistiska förhå llanden. Algoritmerna är testade under identiska miljöer för att experimenten är styrbar och repeterbar. För varje algoritm genomströmningen mättes under olika trafikbelastningar för att utvärdera och jämföra resultaten för de olika algoritmer. Den avvägning mellan signalering overhead och prestanda utvärderas också . Det konstaterades att de system som föreslå s link adaptation uppnå s högre genom- snittlig throughput än Minstrel algoritm. Vi fann också att utförandet av vissa av de föreslagna systemen är nära den av ideal LA.

In recent years, Software Defined and Cognitive Radios (SDRs and CRs) have become popular topics of research. Game theory has proven to be a useful set of tools for analyzing wireless networks, including Cognitive Networks (CNs). This thesis provides a game theoretic cross-layer mechanism that can be used to control SDRs and CRs. We have constructed an upper-layer Topology Control (TC) game, which decides which links each node uses. A TDMA algorithm which we have adapted is then run on these links. The links and the TDMA schedule are then passed to a lower-layer game, the Link Adaptation Game (LAG), where nodes adjust their transmit power and their link parameters, which in this case are modulation scheme and channel coding rate. It is shown that both the TC game and the LAG converge to a Nash Equilibrium (NE). It is also shown that the solution for the TC game approximates the topology that results from maximizing the utility function when appropriate link costs are used. Also seen is the increase in throughput provided by the LAG when compared to the results of Greedy Rate Packing (GRP). / Master of Science

Over the last few decades, wireless networks have morphed from traditional cellular/wireless local area networks (WLAN), into a wide range of applications, such as the Internet-of-Things (IoT), vehicular-to-everything (V2X), and smart grid communication networks. This transition has been facilitated by research and development efforts in academia and industry, which has resulted in the standardization of fifth-generation (5G) wireless networks. To meet the performance requirements of these diverse use-cases, 5G networks demand higher performance in terms of data rate, latency, security, and reliability, etc. At the physical layer, these performance enhancements are achieved by (a) optimizing spectrum utilization shared amongst multiple technologies (termed as spectrum sharing), and (b) leveraging advanced spatial signal processing techniques using large antenna arrays (termed as massive MIMO). In this dissertation, we focus on enhancing the performance of next-generation vehicular communication and spectrum sharing systems. In the first contribution, we present a novel pilot configuration design and adaptation mechanism for cellular vehicular-to-everything (C-V2X) networks. Drawing inspiration from 4G and 5G standards, the proposed approach is based on limited feedback of indices from a codebook comprised of quantized channel statistics information. We demonstrate significant rate improvements using our proposed approach in terrestrial and air-to-ground (A2G) vehicular channels. In the second contribution, we demonstrate the occurrence of cellular link adaptation failure due to channel state information (CSI) contamination, because of coexisting pulsed radar signals that act as non-pilot interference. To mitigate this problem, we propose a low-complexity semi-blind SINR estimation scheme that is robust and accurate in a wide range of interference and noise conditions. We also propose a novel dual CSI feedback mechanism for cellular systems and demonstrate significant improvements in throughput, block error rate, and latency, when sharing spectrum with a pulsed radar. In the third contribution, we develop fundamental insights on underlay radar-massive MIMO spectrum sharing, using mathematical tools from stochastic geometry. We consider a multi-antenna radar system, sharing spectrum with a network of massive MIMO base stations distributed as a homogeneous Poisson Point Process (PPP) outside a circular exclusion zone centered around the radar. We propose a tractable analytical framework, and characterize the impact of worst-case downlink cellular interference on radar performance, as a function of key system parameters. The analytical formulation enables network designers to systematically isolate and evaluate the impact of each parameter on the worst-case radar performance and complements industry-standard simulation methodologies by establishing a baseline performance for each set of system parameters, for current and future radar-cellular spectrum sharing deployments. Finally, we highlight directions for future work to advance the research presented in this dissertation and discuss its broader impacts across the wireless industry, and policy-making. / Doctor of Philosophy / The impact of today's technologies has been magnified by wireless networks, due to the standardization and deployment of fifth-generation (5G) cellular networks. 5G promises faster data speeds, lower latency and higher user security, among other desirable features. This has made it capable of meeting the performance requirements of key infrastructure such as smart grid and mission-critical networks, and novel consumer applications such as smart home appliances, smart vehicles, and augmented/virtual reality. In part, these capabilities have been achieved by (a) better spectrum utilization among various wireless technologies (called spectrum sharing), and (b) serving multiple users on the same resource using large multi-antenna systems (called massive MIMO). In this dissertation, we make three contributions that enhance the performance of vehicular communications and spectrum sharing systems. In the first contribution, we present a novel scheme wherein a vehicular communication link adapts to the channel conditions by controlling the resource overhead in real-time, to improve spectral utilization of data resources. The proposed scheme enhances those of current 4G and 5G networks, which are based on limited feedback of quantized channel statistics, fed back from the receiver to the transmitter. In the second contribution, we show that conventional link adaptation methods fail when 4G/5G networks share spectrum with pulsed radars. To mitigate this problem, we develop a comprehensive signal processing framework, consisting of a hybrid SINR estimation method that is robust and accurate in a wide range of interference and noise conditions. Concurrently, we also propose a scheme to pass additional information that captures the channel conditions in the presence of radar interference, and analyze its performance in detail. In the third contribution, we focus on characterizing the impact of 5G cellular interference on a radar system in shared spectrum, using mathematical tools from stochastic geometry. We model the worst-case interference scenario, and study the impact of the system parameters on the worst-case radar performance. In summary, this dissertation advances the state-of-the-art in vehicular communications and spectrum sharing, through (a) novel contributions in protocol design and (b) development of mathematical tools for performance characterization.