Analysis of hidden node problem in LTE networks deployed in unlicensed spectrum

LTE operation in the unlicensed spectrum based on Licensed-Assisted Access (LAA) is being considered as an option to increase the capacity of 4G/5G wireless networks. This solution allows the eNodeB to contend with other nodes by accessing the shared medium and, through carrier aggregation (CA), to use both licensed and unlicensed bands to deliver best effort services. Nevertheless, the hidden node problem over shared medium access networks is an obstacle that must be addressed in order to reduce or avoid performance degradation problems. The metrics associated to LAA reflect the behavior of a node facing collisions. A better understanding of these metrics can help to identify nodes affected by hidden terminals, making it possible to take smart decisions about the continuity of a node on the unlicensed band, resulting in an improved network performance. In this paper, we first study the Channel Quality Indicator (CQI), Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ) metrics on the context of LAA for a User Equipment (UE) that is facing different levels of interference. Then, a combination of the above metrics is used in order to develop an algorithm for collision detection. Finally, the performance of the algorithm is evaluated using a simulation tool under realistic channel conditions. The results show that is feasible to detect, with an adequate accuracy level, if a node is affected by collisions and subsequently if this node is located in hidden area. This is demonstrated with different levels of interference, realistic channel conditions and users in movement inside the hidden area

MAC-PHY Frameworks For LTE And WiFi Networks\u27 Coexistence Over The Unlicensed Band

The main focus of this dissertation is to address these issues and to analyze the interactions between LTE and WiFi coexisting on the unlicensed spectrum. This can be done by providing some improvements in the first two communication layers in both technologies. Regarding the physical (PHY) layer, efficient spectrum sensing and data fusion techniques that consider correlated spectrum sensing readings at the LTE/WiFi users (sensors) are needed. Failure to consider such correlation has been a major shortcoming of the literature. This resulted in poorly performing spectrum sensing systems if such correlation is not considered in correlated-measurements environments

Cognitive radio systems in LTE networks

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The most important fact in the mobile industry at the moment is that demand for wireless services will continue to expand in the coming years. Therefore, it is vital to find more spectrums through cognitive radios for the growing numbers of services and users. However, the spectrum reallocations, enhanced receivers, shared use, or secondary markets-will not likely, by themselves or in combination, meet the real exponential increases in demand for wireless resources. Network operators will also need to re-examine network architecture, and consider integrating the fibre and wireless networks to address this issue. This thesis involves driving fibre deeper into cognitive networks, deploying microcells connected through fibre infrastructure to the backbone LTE networks, and developing the algorithms for diverting calls between the wireless and fibre systems, introducing new coexistence models, and mobility management. This research addresses the network deployment scenarios to a microcell-aided cognitive network, specifically slicing the spectrum spatially and providing reliable coverage at either tier. The goal of this research is to propose new method of decentralized-to-distributed management techniques that overcomes the spectrum unavailability barrier overhead in ongoing and future deployments of multi-tiered cognitive network architectures. Such adjustments will propose new opportunities in cognitive radio-to-fibre systematic investment strategies. Specific contributions include: 1) Identifying the radio access technologies and radio over fibre solution for cognitive network infrastructure to increase the uplink capacity analysis in two-tier networks. 2) Coexistence of macro and microcells are studied to propose a roadmap for optimising the deployment of cognitive microcells inside LTE macrocells in the case of considering radio over fibre access systems. 3) New method for roaming mobiles moving between microcells and macrocell coverage areas is proposed for managing spectrum handover, operator database, authentication and accounting by introducing the channel assigning agent entity. The ultimate goal is to reduce unnecessary channel adaptation

Towards Scalable Design of Future Wireless Networks

Wireless operators face an ever-growing challenge to meet the throughput and processing requirements of billions of devices that are getting connected. In current wireless networks, such as LTE and WiFi, these requirements are addressed by provisioning more resources: spectrum, transmitters, and baseband processors. However, this simple add-on approach to scale system performance is expensive and often results in resource underutilization. What are, then, the ways to efficiently scale the throughput and operational efficiency of these wireless networks? To answer this question, this thesis explores several potential designs: utilizing unlicensed spectrum to augment the bandwidth of a licensed network; coordinating transmitters to increase system throughput; and finally, centralizing wireless processing to reduce computing costs. First, we propose a solution that allows LTE, a licensed wireless standard, to co-exist with WiFi in the unlicensed spectrum. The proposed solution bridges the incompatibility between the fixed access of LTE, and the random access of WiFi, through channel reservation. It achieves a fair LTE-WiFi co-existence despite the transmission gaps and unequal frame durations. Second, we consider a system where different MIMO transmitters coordinate to transmit data of multiple users. We present an adaptive design of the channel feedback protocol that mitigates interference resulting from the imperfect channel information. Finally, we consider a Cloud-RAN architecture where a datacenter or a cloud resource processes wireless frames. We introduce a tree-based design for real-time transport of baseband samples and provide its end-to-end schedulability and capacity analysis. We also present a processing framework that combines real-time scheduling with fine-grained parallelism. The framework reduces processing times by migrating parallelizable tasks to idle compute resources, and thus, decreases the processing deadline-misses at no additional cost. We implement and evaluate the above solutions using software-radio platforms and off-the-shelf radios, and confirm their applicability in real-world settings.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133358/1/gkchai_1.pd

Spectrum Sharing and SAS-CBSD Interface Simulation

Spectrum Sharing technologies enables more dynamic spectrum management regulation and framework to provide capacity for the ever-increasing demand of mobile data traffic. This thesis reviewed the background and current state of the development of Spectrum Sharing approaches. TVWS, LSA and CBRS were examined in detail as the most representative solutions. The thesis compared architectural similarities and differences between LSA and CBRS. The thesis reviewed SAS-CBSD interface protocol and continued with a practical validation of SAS-CBSD interface specification. By implementing the interface in Python, interface simulation was conducted via the assistance of automation scripts. The thesis concluded that the SAS-CBSD interface is functioning as designed, noting that ESC will further extend the spectrum access dynamism. The thesis also pointed out the need to specify SAS-relevant data models for database API standardization

Distributed algorithms for optimized resource management of LTE in unlicensed spectrum and UAV-enabled wireless networks

Next-generation wireless cellular networks are morphing into a massive Internet of Things (IoT) environment that integrates a heterogeneous mix of wireless-enabled devices such as unmanned aerial vehicles (UAVs) and connected vehicles. This unprecedented transformation will not only drive an exponential growth in wireless traffic, but it will also lead to the emergence of new wireless service applications that substantially differ from conventional multimedia services. To realize the fifth generation (5G) mobile networks vision, a new wireless radio technology paradigm shift is required in order to meet the quality of service requirements of these new emerging use cases. In this respect, one of the major components of 5G is self-organized networks. In essence, future cellular networks will have to rely on an autonomous and self-organized behavior in order to manage the large scale of wireless-enabled devices. Such an autonomous capability can be realized by integrating fundamental notions of artificial intelligence (AI) across various network devices. In this regard, the main objective of this thesis is to propose novel self-organizing and AI-inspired algorithms for optimizing the available radio resources in next-generation wireless cellular networks. First, heterogeneous networks that encompass licensed and unlicensed spectrum are studied. In this context, a deep reinforcement learning (RL) framework based on long short-term memory cells is introduced. The proposed scheme aims at proactively allocating the licensed assisted access LTE (LTE-LAA) radio resources over the unlicensed spectrum while ensuring an efficient coexistence with WiFi. The proposed deep learning algorithm is shown to reach a mixed-strategy Nash equilibrium, when it converges. Simulation results using real data traces show that the proposed scheme can yield up to 28% and 11% gains over a conventional reactive approach and a proportional fair coexistence mechanism, respectively. In terms of priority fairness, results show that an efficient utilization of the unlicensed spectrum is guaranteed when both technologies, LTE-LAA and WiFi, are given equal weighted priorities for transmission on the unlicensed spectrum. Furthermore, an optimization formulation for LTE-LAA holistic traffic balancing across the licensed and the unlicensed bands is proposed. A closed form solution for the aforementioned optimization problem is derived. An attractive aspect of the derived solution is that it can be applied online by each LTE-LAA small base station (SBS), adapting its transmission behavior in each of the bands, and without explicit communication with WiFi nodes. Simulation results show that the proposed traffic balancing scheme provides a better tradeoff between maximizing the total network throughput and achieving fairness among all network ows compared to alternative approaches from the literature. Second, UAV-enabled wireless networks are investigated. In particular, the problems of interference management for cellular-connected UAVs and the use of UAVs for providing backhaul connectivity to SBSs are studied. Speci cally, a deep RL framework based on echo state network cells is proposed for optimizing the trajectories of multiple cellular-connected UAVs while minimizing the interference level caused on the ground network. The proposed algorithm is shown to reach a subgame perfect Nash equilibrium upon convergence. Moreover, an upper and lower bound for the altitude of the UAVs is derived thus reducing the computational complexity of the proposed algorithm. Simulation results show that the proposed path planning scheme allows each UAV to achieve a tradeoff between minimizing energy efficiency, wireless latency, and the interference level caused on the ground network along its path. Moreover, in the context of UAV-enabled wireless networks, a UAV-based on-demand aerial backhaul network is proposed. For this framework, a network formation algorithm, which is guaranteed to reach a pairwise stable network upon convergence, is presented. Simulation results show that the proposed scheme achieves substantial performance gains in terms of both rate and delay reaching, respectively, up to 3.8 and 4-fold increase compared to the formation of direct communication links with the gateway node. Overall, the results of the different proposed schemes show that these schemes yield significant improvements in the total network performance as compared to current existing literature. In essence, the proposed algorithms can also provide self-organizing solutions for several resource management problems in the context of new emerging use cases in 5G networks, such as connected autonomous vehicles and virtual reality headsets

Radio network management in cognitive LTE-Femtocell Systems

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.There is a strong uptake of femtocell deployment as small cell application platforms in the upcoming LTE networks. In such two-tier networks of LTEfemtocell base stations, a large portion of the assigned spectrum is used sporadically leading to underutilisation of valuable frequency resources. Novel spectrum access techniques are necessary to solve these current spectrum inefficiency problems. Therefore, spectrum management solutions should have the features to improve spectrum access in both temporal and spatial manner. Cognitive Radio (CR) with the Dynamic Spectrum Access (DSA) is considered to be the key technology in this research in order to increase the spectrum efficiency. This is an effective solution to allow a group of Secondary Users (SUs) to share the radio spectrum initially allocated to the Primary User (PUs) at no interference. The core aim of this thesis is to develop new cognitive LTE-femtocell systems that offer a 4G vision, to facilitate the radio network management in order to increase the network capacity and further improve spectrum access probabilities. In this thesis, a new spectrum management model for cognitive radio networks is considered to enable a seamless integration of multi-access technology with existing networks. This involves the design of efficient resource allocation algorithms that are able to respond to the rapid changes in the dynamic wireless environment and primary users activities. Throughout this thesis a variety of network upgraded functions are developed using application simulation scenarios. Therefore, the proposed algorithms, mechanisms, methods, and system models are not restricted in the considered networks, but rather have a wider applicability to be used in other technologies. This thesis mainly investigates three aspects of research issues relating to the efficient management of cognitive networks: First, novel spectrum resource management modules are proposed to maximise the spectrum access by rapidly detecting the available transmission opportunities. Secondly, a developed pilot power controlling algorithm is introduced to minimise the power consumption by considering mobile position and application requirements. Also, there is investigation on the impact of deploying different numbers of femtocell base stations in LTE domain to identify the optimum cell size for future networks. Finally, a novel call admission control mechanism for mobility management is proposed to support seamless handover between LTE and femtocell domains. This is performed by assigning high speed mobile users to the LTE system to avoid unnecessary handovers. The proposed solutions were examined by simulation and numerical analysis to show the strength of cognitive femtocell deployment for the required applications. The results show that the new system design based on cognitive radio configuration enable an efficient resource management in terms of spectrum allocation, adaptive pilot power control, and mobile handover. The proposed framework and algorithms offer a novel spectrum management for self organised LTE-femtocell architecture. Eventually, this research shows that certain architectures fulfilling spectrum management requirements are implementable in practice and display good performance in dynamic wireless environments which recommends the consideration of CR systems in LTE and femtocell networks

Centralized and Distributed Self-x Features in heterogeneous 5G Networks.

The continuous evolution of mobile network technology is leading to the 5th Generation (5G) of cellular networks, a level of development that exhibits unprecedented network features, capability, and intelligence. New technological cost–efficient solutions are, therefore, required to boost the network capacity and advance its capabilities in order to support the Quality of Service (QoS) requirements. Network densification is known to be as one of the promising approaches aiming to increase the network capacity and reduce latency. For example, Heterogeneous Wireless Networks (HWN) can provide flexible and diverse network access to the users by integration of different wireless technologies. By introducing dense and diverse networks, the importance of network coordination and automated controllability has never been higher. Despite the advantages of network densifications, there are challenges that have to be addressed properly in order to use the best performance of heterogeneous networks. An example of HWN is the 5 GHz unlicensed band which is open to different wireless systems such as WiFi or Unlicensed LTE. The presence of the two mentioned OFDM-based systems in the same band rise the importance of studying their performance when sharing the same band with the other technologies and introduce new models and methods to reach the friendly coexistence. Another example of dense networks is roaming, especially in the 5G systems, with ever-increasing heterogeneous users. In the small cells and densified networks, Mobile Network Operators (MNOs) need to share their mobile networks with other operators more often to reduce the operator investment costs on infrastructure. Thus, the mobile networks are transferring from uniquely own single authorities to complex interactions among heterogeneous participants which rise the need for a new level of controllability

Técnicas para melhorar a eficiência do sensoriamento colaborativo em redes 5G para áreas remotas

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2020.A revolução dos smartphones em 2007 iniciou a um processo de crescimento exponencial da demanda por serviços de telefonia móvel. O aumento da demanda sem contrapartida da oferta, dependente do espectro disponível provoca uma queda na qualidade dos serviços prestados. As técnicas que usam Rádios cognitivos e acesso dinâmico ao espectro são con- sideradas fundamentais para otimizar a utilização do espectro e aumentar a quantidade de banda disponível para as redes 5G, ao permitir acesso oportunístico ao espectro licenciado ocioso. Diversos estudos apontam a subutilização de bandas, especialmente longe das grandes cidades, em que há menor demanda e menor incentivo econômico para a instalação de infraestrutura por parte das operadoras. Esse comportamento é incentivado devido ao processo de licenciamento de bandas em blocos e alocação estática do espectro, em que uma operadora licencia uma banda e junto a ela fica encarregada por dar cobertura a uma área atrelada à licença, enquanto pequenas operadoras locais ficam completamente de fora dos leilões e são impedidas de competir neste mercado. O acesso dinâmico ao espectro depende de informações que garantam a identificação de transmissões no canal candidato, afim de se reduzir interferência ao detentor da licença do canal. Algumas das técnicas mais comuns para se detectar a ocupação do canal via senso- riamento do espectro são carrier-sense e detecção de energia, dependendo da largura do canal. O sensoriamento colaborativo melhora a capacidade de detecção de uso do canal quando comparado com o sensoriamento individual, visto que diversifica geograficamente a informação disponível para análise. A qualidade do sensoriamento colaborativo depende não só dos sensoriamentos individuais recebidos, mais também da técnica que consolida ou executa a fusão desses resultados. Existem diversos algoritmos de fusão, cada um com vantagens e desvantagens. Algumas das técnicas de fusão clássicas são baseadas em votação k-em-n, em que k sensoriamentos indicando ocupação do canal resultam em uma fusão indicando ocupação do canal. A fusão 1-em-N, OU lógico, resulta em um número alto de falsos positivos, detectando ocupação do canal mesmo quando está desocupado, enquanto minimiza falsos negativos e a não detecção do canal de fato ocupado. Por fim, é parte do ciclo de sensoriamento colaborativo filtrar sensoriamentos de usuários maliciosos que desejam perturbar não só o resultado do sensoriamento colab- orativo como o funcionamento da rede. No caso de uma fusão simples como OU lógico, um único nó malicioso é capaz de inviabilizar por completo o uso oportunístico do es- pectro ao transmitir resultados falsos indicando que o canal está ocupado quando de fato está livre. Diante essa problemática, neste trabalho são propostas duas técnicas para melhorar os resultados do sensoriamento colaborativo, a saber : (1) uma técnica baseada em cadeias de Markov que aplicada aos resultados de sensoriamentos individuais, reduz falsos positivos e falsos negativos, além de reduzir o envio de mensagens de controle ; (2) uma técnica baseada na média harmônica para filtragem de resultados de sensoriamentos individuais recebidos, descartando sensoriamentos de nós mais distantes das fontes de interferência, protegendo de ataques Bizantinos. Ambas as técnicas são avaliadas em cenários de 5G na área rural, em que encontra-se a maior porção de bandas do espectro subutilizadas, candidatas ao acesso oportunístico. A fim de permitir a avaliação das técnicas propostas, foram realizadas diversas alter- ações para o modelo de pilha de rede LTE implementado no simulador de redes a nível de sistemas ns-3. As alterações incluem os procedimentos de sensoriamento do espectro individual feito pelos dispositivos de usuários (UEs), a transmissão dos resultados para o ponto de acesso (eNodeB), a fusão dos resultados recebidos e utilização do resultado de fusão no escalonamento de recursos para os dispositivos. Os sensoriamentos individu- ais são obtidos a partir de curvas de probabilidade de detecção e probabilidade de falsos positivos feitos através de medições em experimentos ou através de simulações a nível de camada física-enlace. As curvas são carregadas durante a configuração inicial da simu- lação, sendo interpoladas conforme necessário. As curvas podem ser tanto baseadas em distância euclidiana quanto em relação sinal ruído e interferência (SINR). O sensoria- mento individual consiste em utilizar a probabilidade de detecção relacionada a um dado valor de SNR ou de distância euclidiana é utilizada para gerar uma amostra aleatória a partir de um gerador com distribuição de Bernoulli. O procedimento se repete a cada 1 milissegundo no ciclo padrão de indicação do subquadro LTE. A técnica baseada em cadeias de Markov se baseia em um Teorema Central do Limite, em que a média de um certo número de amostras uniformemente distribuídas tende a se aproximar ou ao valor real da distribuição de probabilidade fonte ou ao valor central da distribuição. Em outras palavras, ao amostrar uniformemente uma distribuição de- sconhecida com número suficiente de amostras, encontra-se uma boa aproximação para o valor real que é procurado. Este princípio é aplicado para o sensoriamento individual do espectro, em que o valor do último sensoriamento é comparado com o resultado atual, e quando idêntico aumenta o grau de certeza de que este resultado é de fato o real. Quando os resultados diferem, o grau de certeza é perdido. Quando um dado limiar de certeza é ultrapassado, o resultado do sensoriamento que é de fato transmitido para o eNodeB é substituído pelo valor do último sensoriamento. A modelagem deste processo estocástico binomial é feita baseado no lançamento de N moedas, em que apenas o caso em que N resultados iguais consecutivos levam à troca do valor transmitido, sendo facilmente modelado como uma cadeia de Markov de N − 1 estados. Já a técnica baseada em média harmônica se baseia no fato de que as estações próx- imas das fontes de interferência são mais confiáveis que estações distantes, baseando-se nas curvas de probabilidade de detecção. Com isto, é necessário eliminar os resultados de sensoriamentos informados por usuários maliciosos com alguma informação adicional que sirva de prova que seu sensoriamento reportado é falso. Uma das maneiras de se mitigar informações falsas é utilizando a média harmônica dos CQIs reportados, permitindo iden- tificar UEs mais afetados pela fonte de interferência e descartar todos os resultados por UEs pouco afetadas, mais afastadas da fonte. Para poder se confiar no CQI reportado pelos UEs, é necessário medir a quantidade de retransmissões feitas para cada uma delas. Uma taxa de retransmissões próxima de 10% indica um CQI adequado, enquanto taxas próximas de 0% indicam CQI reportado abaixo do real e taxas acima de 10% indicam CQI reportado acima do real. O limiar de retransmissões é definido nos padrões 3GPP. A avaliação das propostas foi feita em duas partes: primeira parte com a validação do modelo proposto para o sensoriamento colaborativo no modelo do padrão LTE do simulador, e a segunda parte avaliando o desempenho das técnicas propostas. Durante a validação, foi confirmado o comportamento esperado do sensoriamento colaborativo (sensoriamentos individuais, transmissão dos resultados e fusões) em termos de taxas de falsos positivos e taxas de falsos negativos quando comparado com os modelos matemáticos. Na avaliação do desempenho das técnicas propostas foram avaliadas acurácia, taxas de falso positivos e taxas de falsos negativos. Em ambos os casos, foram utilizados cenários inspirados em zonas rurais, com: baixo número de nós (10, 20, 50, 100); uma célula com 50 quilômetros de raio; canal de 20 MHz na banda 5 com portadora em 870 MHz; eNodeB transmitindo à 53 dBm; UEs transmitindo à 23 dBm; eNodeB e UEs com antenas com 9 dBi de ganho; detentor da licença do canal (PU) transmitindo à 40 dBm ou 35 dBm; um PU por subcanal de 5 MHz; algoritmos de fusão simples. O cenário de validação foi pouco realístico, com UEs dispersas ao longo de um certo raio fixo de distância do PU, garantindo uma mesma probabilidade de detecção para todos os UEs. Os cenários de avaliação das técnicas foram separados em dois conjuntos, um menos realístico com dispersão aleatória pela célula, outro mais realístico com dispersão aleatória dos PUs pela célula e dispersão aleatória de grupos de UEs pela célula, formando clusters de UESs Os resultados mostram que as técnicas propostas aumentam a acurácia em relação à técnica clássica de fusão de resultados do sensoriamento colaborativo (fusão OU lógico, ou 1-em-N), reduzindo falsos positivos em até 790 vezes, de 63.23% para 0.08% no cenário com dispersão aleatória dos UEs e sem atacantes. Neste mesmo cenário houve um aumento de 0% para 0.47% do número de falsos negativos, sem impactar severamente o detentor da licença do canal. Nos cenários com atacantes, todas as fusões simples apresentam resultados ruins, com ou sem a técnica das cadeias de Markov, até 100% de falsos positivos, inviabilizando o acesso oportunístico. Já a técnica da média harmônica apresenta bom grau de proteção contra atacantes, em especial nos cenários com mais dispositivos. Sem a técnica baseada em Markov e no cenário com 100 UEs, dos quais 10 atacantes, conseguiu reduzir falsos positivos da fusão OU de 100% para 60%, sem aumentar significativamente o número de falsos negativos. Quando as duas técnicas são combinadas, o número de falsos positivos cai para 5% enquanto falsos negativos sobem para 18%. Nos cenários com menos UEs e com clusters, falsos negativos são consistentemente mais altos, porém superiores às fusões 2-em-N, 3-em-N e E utilizando a técnica de Markov no cenário sem atacantes. Em todos os cenários, a técnica baseada em cadeias de Markov também reduziu a taxa média de notificação dos quadros em 2 ordens de grandeza, economizando banda do canal de controle licenciado. Esses resultados permitem concluir que ambas as técnicas são efetivas para o cenário rural para a qual foram propostas. Também se depreende que o número de estados da cadeia de Markov e da técnica da média harmônica podem ser alterados para se trocar alcance da detecção por certeza da detecção e nível de proteção contra atacantes por falsos negativos, respectivamente. Como trabalhos futuros, cabem a adaptação da técnica para: incluir cenários urbanos, mais densos, utilizando técnicas de amostragem; utilização de técnicas de localização (e.g. Time-of-Arrival, Angle-of-Arrival) para segmentação da célula em setores; melhorar a técnica da média harmônica para reduzir falsos negativos mantendo o mesmo nível de proteção contra atacantes.The smartphone revolution of 2007 started an exponential demand growth of mobile con- nectivity. The ever increasing demand requires an increase in supply, which is depends in the amount of available spectrum. The amount of available spectrum however is limited, curving supply growth and reducing the quality of services perceived by the users. Cogni- tive radio and dynamic spectrum access are essential to increase the spectrum utilization and amount of available bandwidth in 5G networks, by opportunistically accessing unused licensed spectrum. The dynamic spectrum access depends on channel information that guarantees the detection of transmissions in the candidate channel, as a means of reducing interference to the channel licensee. The collaborative spectrum sensing increases the channel usage detection capacity when compared to individual spectrum sensing, as there is more geographically diverse information for analysis and decision-making. The quality of the collaborative sensing depends not only on the individual sensing that feeds information into it, but also on the technique that fuses those results into the final sensing result. Two techniques to improve the collaborative spectrum sensing results are proposed in this dissertation: (1) a technique based in Markov chains to smooth consecutive individual spectrum sensing results, reducing both false positives and false negatives, while enabling the reduction of sensing reports by skipping sensing reports with the same results; (2) a technique based in the harmonic mean of the channel quality indicator, used to filter the received individual spectrum sensing, discarding nodes far from the source of interference, mitigating against Byzantine attacks. Both techniques are evaluated in rural 5G scenarios, which are the best place to use opportunistic access due to the amount of unutilized and underused spectrum bands. In order to evaluate the proposed techniques, a set of modifications to the LTE net- work stack model of the ns-3 system-level simulator is proposed. The modifications include a complete collaborative sensing cycle, including: the individual spectrum sensing pro- cedure, performed by user equipment’s (UEs); the transmission of control messages to the access point (eNodeB), the fusion of the received results and utilization of the free spectrum for the UEs. The individual spectrum sensing is performed by interpolating probability of detection curves and false positive probability, which are produced either by experimental measurements or by link-layer simulations. The evaluation of the proposals was made in two parts: first part focusing on the validating the collaborative spectrum sensing cycle implementation and integration to the LTE model; second part focusing on the performance of the proposed techniques. The collaborative spectrum sensing cycle (individual sensing, sensing report and fusion) was validated and closely follows the mathematical model. The evaluation of the techniques included accuracy of the fused result, false positive and false negative rates. The results show the techniques are effective in increasing the accuracy of the collab- orative sensing when compared to the standalone classic fusion techniques (OR fusion, or 1-out-of-n). There were reductions in false positives rates of up to 790 times, from 63.23% to 0.08% in the scenario with randomized dispersion of UEs across the cell and without attackers. In the same scenario, the false negatives increased from 0% to 0.47%, which does not severely impact the licensee with interference. All classic fusions behave very poorly in scenarios with attackers, with and without the Markov chain technique. False positive rates soar to as high as 100%, making the opportunistic access impossible. The harmonic mean-based technique reduces the false positives, providing good protec- tion against attackers especially in scenarios with more UEs. The harmonic mean alone reduced false positives for the OR fusion from 100% to 60% without significantly impact- ing false negatives in the scenario with 100 UEs and 10 attackers. When both techniques are used together, the rate of false positives fall to 5% while false negatives increase to 18%. Scenarios with less UEs and distributed in clusters tend to have higher false negative rates when both techniques are used, but false positives are consistently lower than other classical fusions (e.g. 2-out-of-N, 3-out-of-N and AND). The Markov chain technique effectively reduced the sensing report rate by 2 orders of magnitude, saving up scarce control bandwidth. These results allow us to conclude that the both techniques are effective for the rural scenario they were proposed