We implement reinforcement learning in the context of wireless communications in two very different settings. In the first setting, we study the use of reinforcement learning in an underwater acoustic communications network to adapt its transmission frequencies to avoid interference and potential malicious jammers. To that effect, we implement a reinforcement learning algorithm called contextual bandits. The harsh environment of an underwater channel provides a challenging problem. The channel may induce multipath and time delays which lead to time-varying, frequency-selective attenuation. These factors are also influenced by the distance between the transmitter and receiver, the subbands the interference is located within, and the power of the transmitter. We show that the agent is effectively able to avoid frequency bands that have degraded channel quality or that contain interference, both of which are dynamic or time-varying . In the second setting, we study the use of reinforcement learning to adapt the modulation and power scheme of a jammer seeking to disrupt a wireless communications system. To achieve this, we make use of a linear contextual bandit to learn to jam the victim system. Prior work has shown that with the use of linear bandits, improved convergence is achieved to jam a single-carrier system using time-domain jamming schemes. However, communications systems today typically employ orthogonal frequency division multiplexing (OFDM) to transmit data, particularly in 4G/5G networks. This work explores the use of linear Thompson Sampling (TS) to jam OFDM-modulated signals. The jammer may select from both time-domain and frequency-domain jamming schemes. We demonstrate that the linear TS algorithm is able to perform better than a traditional reinforcement learning algorithm, upper confidence bound-1 (UCB-1), in terms of maximizing the victim's symbol error rate. We also draw novel insights by observing the action states, to which the reinforcement learning algorithm converges. We then investigate the design and modification of the context vector in the hope of in- creasing overall performance of the bandit, such as decreased learning period and increased symbol error rate caused to the victim. This includes running experiments on particular features and examining how the bandit weights the importance of the features in the context vector. Lastly, we study how to jam an OFDM-modulated signal which employs forward error correction coding. We extend this to leverage reinforcement learning to jam a 5G-based system implementing some aspects of the 5G protocol. This model is then modified to introduce unreliable reward feedback in the form of ACK/NACK observations to the jammer to understand the effect of how imperfect observations of errors can affect the jammer's ability to learn. We gain insights into the convergence time of the jammer and its ability to jam the victim, as well as improvements to the algorithm, and insights into the vulnerabilities of wireless communications for reinforcement learning based jamming. / Master of Science / In this thesis we implement a class of reinforcement learning known as contextual bandits in two different applications of communications systems and jamming. In the first setting, we study the use of reinforcement learning in an underwater acoustic communications network to adapt its transmission frequencies to avoid interference and potential malicious jammers. We show that the agent is effectively able to avoid frequency bands that have degraded channel quality or that contain interference, both of which are dynamic or time-varying. In the second setting, we study the use of reinforcement learning to adapt the jamming type, such as using additive white Gaussian noise, and power scheme of a jammer seeking to disrupt a wireless communications system. To achieve this, we make use of a linear contextual bandit which implies that the contexts that the jammer is able to observe and the sampled probability of each arm has a linear relationship with the reward function. We demonstrate that the linear algorithm is able to outperform a traditional reinforcement learning algorithm in terms of maximizing the victim's symbol error rate. We extend this work by examining the impact of the context feature vector design, LTE/5G-based protocol specifics (such as error correction coding), and imperfect reward feedback information. We gain insights into the convergence time of the jammer and its ability to jam the victim, as well as improvements to the algorithm, and insights into the vulnerabilities of wireless communications for reinforcement learning based jamming.

Dynamic spectrum sharing (DSS) is a new paradigm for spectrum allocation that is expected to lead to more efficient spectrum usage and alleviate the spectrum-scarcity that has been perceived in recent years. DSS refers to the opportunistic, dynamic, and uncoordinated use of the spectrum by multiple, possibly non-cooperating, systems. It allows bands which may be underutilized by incumbent or legacy systems to be shared by agile or cognitive radios on a ``do no harm" basis. An ideal DSS technique is one which efficiently uses the allocated spectrum and maximizes the performance of the DSS network while causing no interference to the legacy radio system with which it coexists. We address this issue in our work by investigating desirable features for DSS with respect to the impact on a legacy radio system as well as the performance of a DSS network. It is found that ``ideal" DSS techniques with respect to both objectives are characterized by the removal of the strongest interferers in the system and averaging of the remaining interference. This motivates the use of an interference avoidance (IA) based underlay technique for DSS. The performance benefit provided by this technique, over an IA-based overlay technique, is shown to increase with the transmission bandwidth available to the DSS system. It is also shown that this technique is more robust to inaccuracies in the system knowledge required for implementing IA. An example of an IA-based underlay technique is a spreading-sequence-based transmission scheme that employs sequence adaptation to avoid interference. We use game-theoretic tools to design such schemes for distributed or ad hoc networks. The designed schemes can also be used to avoid interfering with other agile or static radios. We then extend this work to Ultra Wideband systems which can maximally exploit the gains from the proposed scheme due to the large transmission bandwidths. / Ph. D.

Las demandas y expectativas de los usuarios y operadores móviles crecen sin parar y, consecuentemente, los nuevos estándares han incorporado tecnologías de acceso de radio cada vez más eficientes. Las especificaciones IMT-Advanced para la cuarta generación (4G) de redes móviles de banda ancha requieren, entre otras cosas, tasas más altas de transmisión de datos, del orden de 100 Mbps a 1 Gbps, dependiendo del nivel de movilidad. Para conseguir éstas tasas se ha escogido como tecnología de acceso el Acceso Múltiple por División de Frecuencias Ortogonal (OFDMA), y se han considerado femtoceldas para mejorar la cobertura de espacios interiores. Para explorar completamente la flexibilidad de estas tecnologías y utilizar los escasos recursos radio de la manera más eficiente posible se requieren técnicas de Gestión de Recursos Radio (RRM) adaptativas e inteligentes. En el ámbito de los sistemas celulares basados en OFDMA, uno de los problemas todavía no resuelto es el compromiso que existe entre la eficiencia en la utilización de los recursos y la equidad en su distribución entre los usuarios de la red. El compromiso entre eficiencia y equidad aparece cuando los recursos radio asignados dan lugar a diferentes indicadores de eficiencia con respecto a los distintos usuarios de red (diversidad multi-usuario). El uso de una asignación de recursos oportunista, para explorar estas diversidades y maximizar la capacidad, causa situaciones de desigualdad en la distribución de los recursos. Por otro lado, los esquemas de RRM que propician equidad absoluta consideran un escenario de peor caso, penalizando a los usuarios con mejores condiciones y reduciendo la capacidad del sistema. En esta tesis, se han propuesto varias políticas y técnicas de RRM para balancear este compromiso en el contexto de redes macrocelulares y femtocelulares. En el caso particular de sistemas macrocelulares, proponemos un nuevo paradigma de gestión de red basado en el control del índice de equidad de la celda en escenarios con servicios de tiempo no-real y de tiempo real. Se han estudiado dos enfoques para el control de la equidad: control instantáneo (a corto plazo) utilizando técnicas de RRM de adaptación de tasa y equidad, y control promediado (a mediano plazo) utilizando estructuras de RRM basadas en la Teoría de la Utilidad. En el caso de las femtoceldas, se ha formulado una nueva técnica para evitar la interferencia capaz de balancear el compromiso entre eficiencia espectral y la equidad entre los puntos de acceso de las femtoceldas. Esta estrategia de RRM se basa en una planificación a mediano/largo plazo de las frecuencias disponibles, que toma en consideración la topología de interferencia de grupos de femtoceldas vecinas. Las técnicas de RRM consideradas en esta tesis se han evaluada utilizando de forma sistemática técnicas de simulación numéricas a nivel de sistema. En el caso del escenario macrocelular, se demuestra que las técnicas adaptativas de RRM propuestas son, para los operadores móviles una, herramienta valiosa porqué, además de ser una generalización de estrategias clásicas bien conocidas, son capaces de garantizar de forma eficiente diferentes niveles de equidad en el sistema, y controlar el compromiso entre eficiencia y equidad. Además, se concluye que las estrategias basadas en la teoría de utilidad, que hacen un control promedio de la equidad, muestran resultados tan buenos ó incluso mejores que los presentados por las técnicas basadas en optimización instantánea de la adaptación de la tasa y la equidad, utilizando menores recursos computacionales. Finalmente, se demuestra que la técnica propuesta para evitar interferencia en redes de femtoceldas puede garantizar una coexistencia sin degradaciones entre punto de acceso vecinos para cualquier topología de interferencia. Esta técnica puede ser implementada mediante arquitecturas de red distribuidas ó centralizadas, presentando en ambos casos unos requisitos de señalización muy bajos. / User and cellular operator requirements and expectations have been continuously evolving, and consequently, advanced radio access technologies have emerged. The International Mobile Telecommunications - Advanced (IMT-Advanced) specifications for mobile broadband Fourth Generation (4G) networks state, among other requirements, that enhanced peak data rates of 100 Mbps and 1 Gbps for high and low mobility should be provided. In order to achieve this challenging performance, Orthogonal Frequency Division Multiple Access (OFDMA) has been chosen as the access technology, and femtocells have been considered for improving indoor coverage. In order to fully explore the flexibility of these technologies and use the scarce radio resources in the most efficient way possible, intelligent and adaptive Radio Resource Management (RRM) techniques are crucial. There are many open RRM problems in wireless networks in general and OFDMA-based cellular systems in particular. One of such problems is the fundamental trade-off that exists between efficiency in the resource usage and fairness in the resource distribution among network players. Several opportunistic RRM algorithms, which dynamically allocate the resources to the network players that present the highest efficiency indicator with regard to these resources, have been proposed to maximize the efficiency in the resource usage. The trade-off between efficiency and fairness appears when the resources have different efficiency indicators to different network players (multi-user or multi-cell diversity). The use of opportunistic resource allocation to explore these diversities causes unfair situations in the resource distribution. On the other hand, schemes that provide absolute fairness deal with the worst case scenario, penalizing players with better condition and reducing the system capacity. In this thesis, several RRM policies and techniques are proposed to balance this compromise in macrocell and femtocell networks. In the particular case of macrocell systems, we propound a new network management paradigm based on the control of a cell fairness index in scenarios with Non-Real Time (NRT) or Real Time (RT) services. Two fairness control approaches are studied: instantaneous (short-term) control by means of generalized fairness/rate adaptive RRM techniques and average (mid-term) control using utility-based frameworks. For femtocell networks, a novel interference avoidance technique able to balance the trade-off between spectral efficiency in the femtocell tier and fairness among the Femtocell Access Points (FAPs) is formulated. This RRM strategy is based on a high-level, mid/long-term frequency planning that takes into account the topology of groups of neighboring FAPs. The RRM techniques considered in this thesis are evaluated by means of extensive system-level and/or numerical simulations. Regarding the macrocell scenario, it is shown that the proposed adaptive RRM techniques are valuable tools for the mobile operators, because they are generalizations of well-known classic strategies found in the literature and they can effectively guarantee different fairness levels in the system and control the trade-off between efficiency and fairness. Furthermore, it is concluded that the utility-based strategies that perform an average fairness control can provide performance results as good as the fairness/rate adaptive techniques, which are based on instantaneous optimization, using less computational resources. Finally, it is demonstrated that the proposed interference avoidance technique for femtocell networks can guarantee a seamless coexistence between neighboring FAPs in any interference topology. Furthermore, this technique can be implemented in both centralized and distributed network architectures and generates very low signaling overhead.

Ultrawideband and cognitive radio are two of the most important approaches that are shaping the future of wireless communication systems. At a first glance, the aims of UWB and cognitive radio do not seem to be overlapping significantly, however, there is a strong synergy between the capabilities of UWB and the goals of cognitive radio. One of the objectives of this thesis is to shed the first light on the marriage of these two important approaches.Ultrawideband (UWB) is a promising technology for future short-range, high-data rate wireless communication networks. Along with its exciting features including achieving high data rates, low transmission power requirement, and immunity to multipath effects, UWB is unique in its coexistence capability with narrowband systems.In this thesis, the details of practical UWB implementation are provided. Regarding the coexistence of UWB with licensed narrowband systems, narrowband interference (NBI)avoidance and cancelation techniques in the literature are investigated. It is aimed to emphasize that UWB is a strong candidate for cognitive radio, and this fact is proven by providing two different approaches in which ultrawideband is combined with cognitive radio to maximize the performance of unlicensed communications.

Abstract Spectrum sharing has become a high priority research area over the past few years. The motivation behind this lies in the fact that the limited spectrum is currently inefficiently utilized. As recognized by the World radio communication conference (WRC)-07, the amount of identified spectrum is not large enough to support large bandwidths for a substantial number of operators. Therefore, it is paramount for future mobile cellular systems to share the frequency spectrum and coexist in a more efficient manner. The present dissertation deals with the problem of spectrum scarcity by examining spectrum sharing paradigms where a migration from fixed to flexible resource allocation is investigated. First, a radio resource management (RRM) architecture is proposed where advanced spectrum functionalities accounting for the short-term variations of the spectrum are examined. The achievable gains are shown in a multi-cell, multi-network environment with realistic traffic patterns from a European operator, enhancing thereby spectrum utilization. Second, inter-operator resource sharing in a broadband network is considered where a packet-based cellular network is developed. It is shown that the obtained gains in terms of quality-of-service (QoS), number of operators and different data rates requirements improve the overall efficiency of the network. Besides and in order to cope with the stringent data rate requirements, direct terminal-to-terminal (T2T) communication is examined in which a realistic algorithm is proposed advocating resource reuse in a cellular system with simultaneous communications between mobiles. Numerical results confirm the advantages of resource reuse in terms of throughput, average frame delays and power consumption. In this thesis, a proposal is made as how to enhance spectrum sharing. The concept of hierarchy is proposed in which wireless competitive operators share the same spectrum band. The decentralized hierarchical approach is shown to bridge the gap between the selfish and centralized approach. Interference avoidance is studied for point-to-point communication in a selforganized network where different optimal power allocation strategies are examined along with the impact of frequency reuse on the ergodic capacity of the network.

The traditional way of increasing capacity in a wirelesscommunication system has been cell splitting and fixedchannel-allocation based on prediction tools. However, theplanning complexity increases rapidly with the number of cellsand the method is not suitable for the large temporal andspatial traffic variations expected in the future. A lot ofresearch has therefore been performed regarding adaptivechannel allocation, where a channel can be used anywhere aslong as the signal-to-interference ratio (SIR) is acceptable. Acommon opinion is that these solutions must be decentralizedsince a centralized one would be overly complex. In this thesis, we study the locally centralizedbunch conceptfor radio resource management (RRM) in aManhattan environment and show that it can give a very highcapacity both for outdoor users and for indoor users covered byoutdoor base stations. We show how measurement limitations anderrors affect the performance and wepropose methods to handlethese problems, e.g. averaging of measured values, robustchannel selection algorithms, and increased SIR margins. Wealso study the computational and signaling complexities andshow that they can be reduced by splitting large bunches, usingsparse matrix calculations, and by using a simplified admissionalgorithm. However, a reduction of the complexity often means areduction of the system capacity. The measurements needed for RRM can also be used to find amobile terminal's geographical position. We propose and studysome simple yet accurate methods for this purpose. We alsostudy if position information can enhance RRM as is oftensuggested in the literature. In the studied scenario, thisinformation seems to be of limited use. One possible use is toestimate the mobile user's speed, to assist handover decisions.Another use is to find the location of user hotspots in anarea, which is beneficial for system planning. Our results show that the bunch concept is a promisingcandidate for radio resource management in future wirelesssystems. We believe that the complexity is manageable and themain price we have to pay for high capacity is frequentreallocation of connections. <b>Keywords:</b>bunch concept, radio resource management,network-assisted resource management, base station selection,dynamic channel allocation, DCA, channel selection,least-interfered, interference avoidance, interferenceaveraging, handover, power control, path-loss measurements,signal strength, link-gain matrix, TD-CDMA, UTRA TDD, Manhattanscenario, microcells, mobile positioning, position accuracy,trilateration, triangulation, speed estimation

<p>The traditional way of increasing capacity in a wirelesscommunication system has been cell splitting and fixedchannel-allocation based on prediction tools. However, theplanning complexity increases rapidly with the number of cellsand the method is not suitable for the large temporal andspatial traffic variations expected in the future. A lot ofresearch has therefore been performed regarding adaptivechannel allocation, where a channel can be used anywhere aslong as the signal-to-interference ratio (SIR) is acceptable. Acommon opinion is that these solutions must be decentralizedsince a centralized one would be overly complex.</p><p>In this thesis, we study the locally centralized<i>bunch concept</i>for radio resource management (RRM) in aManhattan environment and show that it can give a very highcapacity both for outdoor users and for indoor users covered byoutdoor base stations. We show how measurement limitations anderrors affect the performance and wepropose methods to handlethese problems, e.g. averaging of measured values, robustchannel selection algorithms, and increased SIR margins. Wealso study the computational and signaling complexities andshow that they can be reduced by splitting large bunches, usingsparse matrix calculations, and by using a simplified admissionalgorithm. However, a reduction of the complexity often means areduction of the system capacity.</p><p>The measurements needed for RRM can also be used to find amobile terminal's geographical position. We propose and studysome simple yet accurate methods for this purpose. We alsostudy if position information can enhance RRM as is oftensuggested in the literature. In the studied scenario, thisinformation seems to be of limited use. One possible use is toestimate the mobile user's speed, to assist handover decisions.Another use is to find the location of user hotspots in anarea, which is beneficial for system planning.</p><p>Our results show that the bunch concept is a promisingcandidate for radio resource management in future wirelesssystems. We believe that the complexity is manageable and themain price we have to pay for high capacity is frequentreallocation of connections.</p><p><b>Keywords:</b>bunch concept, radio resource management,network-assisted resource management, base station selection,dynamic channel allocation, DCA, channel selection,least-interfered, interference avoidance, interferenceaveraging, handover, power control, path-loss measurements,signal strength, link-gain matrix, TD-CDMA, UTRA TDD, Manhattanscenario, microcells, mobile positioning, position accuracy,trilateration, triangulation, speed estimation</p>

Theoretic results have shown that the capacity of a channel does not decrease if the receiver observes the transmitted signal in the presence of interference, provided that the transmitter knows this interference non-causally. That is, if the transmitter has non-causal access to the interference, by using proper precoding this interference could be “avoided” (as if it were not present) under the same transmit power constraint. It indicates that lossless (in the sense of capacity) precoding is theoretically possible at any signal-to-noise-ratio (SNR). This is of special interest in digital watermarking, transmission for ISI channels as well as for MIMO broadcast channels. Recent research has elegantly demonstrated the (near) achievability of this “existence-type” result, while the complexity is notable. An interesting question is what one can do when very little extra complexity is permitted. This thesis treats such special cases of this problem in order to shed some light on this question. In the AWGN channel with additive interference, an optimum modulator is designed under the constraint of a binary signaling alphabet with binary interference.Tomlinson-Harashima precoding (THP), which is originally proposed for ISI channels, is improved by picking up optimized parameters and then taken as a benchmark. Simulation results show that the Optimum Modulator always outperforms the THP with optimized parameters. The difference in performance, in terms of mutual information between channel input and output as well as coded bit error rate with Turbo codes, is significant in many scenarios.

L’amélioration de la qualité et de l’efficacité en santé est un réel enjeu sociétal. Elle implique la surveillance continue des paramètres vitaux ou de l’état mental du sujet. Les champs d’applications sont vastes : l’application la plus importante est la surveillance des patients à distance. Les avancées en micro-électronique, capteurs et réseaux sans-fil permettent aujourd’hui le développement de systèmes ambulatoires performants pour le monitoring de paramètres physiologiques, capables de prendre en compte d’importantes contraintes techniques : forte intégration pour la réduction de la taille et faible consommation pour une plus grande autonomie [1]. Cependant, la conception de ce type de réseaux de capteurs médicaux WBANs (Wireles Body Area Networks) se heurte à un certain nombre de difficultés techniques, provenant des contraintes imposées par les capacités réduites des capteurs individuels : basse puissance, énergie limitée et faible capacité de stockage. Ces difficultés requièrent des solutions différentes, encore très embryonnaires, selon l’application visée (monitoring à but médical). La forte mobilité et le changement rapide de la topologie du réseau dévoilent un verrou scientifique et social. En outre, l’interférence de différents capteurs constituant le WBAN augmente la difficulté de la mise en place de ce type de réseaux. De nombreuses solutions dans la littérature ont été étudiées, comme nous allons illustrer dans ce manuscrit, néanmoins elles restent limitées. Nous nous intéresserons tout particulièrement à la gestion des interférences Intra- et Inter-WBAN, leur impacte sur la fiabilité des transmissions (des liens) et la durée de vie de ce type de réseaux. Plus précisément, nous abordons ces problématiques en se basant sur des modélisations théoriques et analytiques et avec une conception pratique des solutions proposées. Afin d’atteindre les objectifs cités ci-dessous, nous abordons quatre solutions : • Une gestion des interférences intra-WBAN • Une gestion coopérative des interférences Inter-WBAN • Une gestion non coopérative des interférences, Inter-WBAN • Une gestion des interférences WBAN dans un contexte IoT Dans la première partie de cette thèse et afin de répondre en partie aux problèmes de gestion des interférences Intra-WBAN. Nous présentons deux mécanismes pour le WBAN : (a) CFTIM qui alloue dynamiquement des slots et des canaux dit- stables (avec un taux d’interférences le bas possible dans le temps) pour réduire les interférences intra-WBAN. (b) IAA ajuste dynamiquement la taille du superframe et limite le nombre de canaux à 2 pour abaisser les interférences Intra-WBAN et ainsi économiser l’énergie. Une validation avec un model probabiliste est proposé afin de valider théoriquement l’efficacité de notre solution. Les résultats de la simulation démontrent l’efficacité du CFTIM et de l’IAA en termes de réduction de la probabilité d’interférence, l’extension de la durée de vie du réseau et l’amélioration du débit et de la fiabilité des transmissions. Notre seconde contribution, propose une gestion coopératives des interférences Inter-WBAN en utilisant des codes orthogonaux. Motivé par un approvisionnement temporel distribué basé sur la norme [2] IEEE 802.15.6, nous proposons deux solutions. (a) DTRC qui fournit à chaque WBAN les connaissances sur les superframes qui se chevauchent. Le second, (b) OCAIM qui attribue des codes orthogonaux aux capteurs appartenant à deux listes de groupe de capteur en interférences de deux WBAN différents (SIL). Les résultats démontrent qu’OCAIM diminue les interférences, améliore le débit et préserve la ressources énergétiques. La troisième partie nous a permis d’aborder la gestion des interférences, mais cette fois ci d’une manière non-coopérative en se basant sur l’affectation couple Slot/Canal. Plus précisément, nous proposons deux schémas basés sur les carrés latins. (...) / A Wireless Body Area Network (WBAN) is a short-range network that consists of a coordinator (Crd) and a collection of low-power sensors that can be implanted in or attached to the human body. Basically, WBANs can provide real-time patient monitoring and serve in various applications such as ubiquitous health-care, consumer electronics, military, sports, etc. [1]. As the license-free 2.4 GHz ISM band is widely used among WBANs and across other wireless technologies, the fundamental problem is to mitigate the resulting co-channel interference. Other serious problems are to extend the network lifetime and to ensure reliable transmission within WBANs, which is an urgent requirement for health-care applications. Therefore, in this thesis, we conduct a systematic research on a few number of research problems related to radio co-channel interference, energy consumption, and network reliability. Specifically, we address the following problems ranging from theoretical modeling and analysis to practical protocol design: • Intra-WBAN interference mitigation and avoidance • Cooperative inter-WBAN interference mitigation and avoidance • Non-cooperative inter-WBAN interference mitigation and avoidance • Interference mitigation and avoidance in WBANs with IoT Firstly, to mitigate the intra-WBAN interference, we present two mechanisms for a WBAN. The first is called CSMA to Flexible TDMA combination for Interference Mitigation, namely, CFTIM, which dynamically allocates time-slots and stable channels to lower the intra-WBAN interference. The second is called Interference Avoidance Algorithm, namely IAA that dynamically adjusts the superframe length and limits the number of channels to 2 to lower the intra-WBAN interference and save energy. Theoretically, we derive a probabilistic model that proves the SINR outage probability is lowered. Simulation results demonstrate the effectiveness and the efficiency of CFTIM and IAA in terms of lowering the probability of interference, extending network lifetime, improving throughput and reliability. Secondly, we address the problem of interference among cooperative WBANs through using orthogonal codes. Motivated by distributed time provisioning supported in IEEE 802.15.6 standard [2], we propose two schemes. The first is called Distributed Time Correlation Reference, namely, DTRC that provides each WBAN with the knowledge about which superframes overlap with each other. The second is called Orthogonal Code Allocation Algorithm for Interference Mitigation, namely, OCAIM, that allocates orthogonal codes to interfering sensors belonging to sensor interference lists (SILs), which are generated based on the exchange of power-based information among WBANs. Mathematically, we derive the successful and collision probabilities of frames transmissions. Extensive simulations are conducted and the results demonstrate that OCAIM can diminish the interference, improve the throughput and save the power resource. Thirdly, we address the problem of co-channel interference among non-cooperative WBANs through time-slot and channel hopping. Specifically, we propose two schemes that are based on Latin rectangles. The first is called Distributed Algorithm for Interference mitigation using Latin rectangles, namely, DAIL that allocates a single channel to a timeslot combination to each sensor to diminish inter-WBAN interference and to yield better schedules of the medium access within each WBAN. The second is called Channel Hopping for Interference Mitigation, namely, CHIM, which generates a predictable interference free transmission schedule for all sensors within a WBAN. CHIM applies the channel switching only when a sensor experiences interference to save the power resource. Furthermore, we present an analytical model that derives bounds on collision probability and throughput for sensors transmissions. (...)