No description available.

Abstract Wideband-CDMA (WCDMA) is a kind of third-generation wireless communication system. It can provide multi-rate services and fast transmission with wideband technology. To improve the solution of no enough wireless bandwidth currently, the 3G communication systems have been researched and developed in several leading countries recently. WCDMA adopts a kind of new spreading codes named Orthogonal Variable Spreading Factor codes (OVSF codes) that have advantages of dynamically variable rates and keeping orthogonality. OVSF codes can provide different data transmission rates by assigning codes with different lengths. By building a code tree, we can discuss some better schemes to assign available data rate. In this paper, we propose an efficient channel assignment scheme that can decrease the call blocking rate and complexity of channel reassignment procedure. Based on the properties of the binary code tree, we use code merge scheme to decrease channel reassignment rate and call blocking rate. This will efficiently improve the performance of channel assignment and spectral efficiency. Simulation results show that the proposed scheme has expected results.

This dissertation presents and develops the Intelligent Picocell as a solution for high bit rate, efficient bandwidth indoor wireless communication. The research has examined different aspects of the indoor radio propagation environment and system implementation in order to highlight key benefits of the proposed architecture. Explosive growth in demand for indoor wireless communications motivates research into this novel radio architecture. The architecture should be capable of tailoring capacity and coverage to the needs of the specific indoor environment, while maximising spectral efficiency. The Intelligent Picocell is based on an evolution of the distributed antenna concept to provide macrodiversity, microdiversity and interference cancellation. The architecture is fully scalable to large numbers of users and can provide plug-and-play operation, with no need for detailed system planning beyond the antenna locations. The research examines different aspects of picocell system performance and design, including: Investigation on the indoor radio environment. Through measurements, the effects of building features on path loss and shadowing are analysed and propagation models are proposed for simulating picocell systems. Analysis of the Intelligent Picocell architecture, two algorithms are proposed for interference reduction, one based on a distributed narrowband optimum combiner and the other on a dynamic channel assignment and allocation scheme. Through simulation, it was demonstrated that the mobile transmitted power for an Intelligent Picocell is lower than the power required in a distributed antennas system. It was also shown that the capacity of the system depends on the number of antennas distributed in the building. Key words: Intelligent picocell, adaptive antennas, diversity, distributed antennas, dynamic channel allocation, propagation measurements.

In this thesis, we investigate several radio resourcemanagement (RRM) techniques and concepts in an indoorenvironment with a dense infrastructure. Future wireless indoorcommunication networks will very likely be implemented atplaces where the user concentration is very high. At these hotspots, the radio resources must be used efficiently. The goalis to identify efficient RRM techniques and concepts that aresuitable for implementation in an indoor environment. Handling the high level of co-channel interference is shownto be of paramount importance. Several investigations in thethesis point this out to be the key problem in an indoorenvironment with a dense infrastructure. We show that a locallycentralized radio resource management concept, the bunchconcept, can give a very high performance compared to othercommonly used RRM concepts. Comparisons are made withdistributed systems and systems using channel selection schemeslike CSMA/CA. The comparisons are primarily made by capacityand throughput analysis which are made by system levelsimulations. Results show that the centralized concept can give85 percent higher capacity and 70 percent higher throughputthan any of the compared systems. We investigate several RRM techniques to deal with thechannel interference problem and show that beamforming cangreatly reduce the interference and improve the systemperformance. Beamforming, especially sector antennas, alsoreduce the transmitter powers and the necessary dynamic range.A comparison is made between the use of TD/CDMA and pure TDMAwhich clearly shows the performance benefits of usingorthogonal channels that separates the users and reduces theco-channel interference. Different channel selection strategiesare studied and evaluated along with various methods to improvethe capability of system co-existence. We also investigate several practical measures to facilitatesystem implementation. Centralized RRM is suitable forguaranteeing QoS but is often considered too complex. With thestudied centralized concept the computational complexity can bereduced by splitting the coverage area into smaller pieces andcover them with one centralized system each. This reduces thecomplexity at the prize of lost capacity due to theuncontrolled interference that the different systems produce.Our investigations show that sector antennas can be used toregain this capacity loss while maintaining high reduction incomplexity. Without capacity loss, the computational complexitycan be reduced by a factor of 40 with sectoring. Theimplementation aspects also include installation sensitivity ofthe indoor architecture and the effect of measurement errors inthe link gains. The robustness against installation errors ishigh but the bunch concept is quite sensitive to largemeasurement errors in the studied indoor environment. Thiseffect can be reduced by additional SIR-margins of the radiolinks. The studied bunch concept is shown to be promising for usein future wireless indoor communication systems. It provideshigh performance and is feasible to implement. Keywords:Radio resource management, indoorcommunication, the bunch concept, centralized RRM, dynamicchannel allocation, channel selection, co-channel interference,power control, feasibility check, capacity, throughput, qualityof service, beamforming, downtilting, sector antennas,co-existence, computational complexity, sensitivity analysis,measurement errors, infrastructure, system implementation,WLAN, HiperLAN/2, IEEE 802.11.

<p>In this thesis, we investigate several radio resourcemanagement (RRM) techniques and concepts in an indoorenvironment with a dense infrastructure. Future wireless indoorcommunication networks will very likely be implemented atplaces where the user concentration is very high. At these hotspots, the radio resources must be used efficiently. The goalis to identify efficient RRM techniques and concepts that aresuitable for implementation in an indoor environment.</p><p>Handling the high level of co-channel interference is shownto be of paramount importance. Several investigations in thethesis point this out to be the key problem in an indoorenvironment with a dense infrastructure. We show that a locallycentralized radio resource management concept, the bunchconcept, can give a very high performance compared to othercommonly used RRM concepts. Comparisons are made withdistributed systems and systems using channel selection schemeslike CSMA/CA. The comparisons are primarily made by capacityand throughput analysis which are made by system levelsimulations. Results show that the centralized concept can give85 percent higher capacity and 70 percent higher throughputthan any of the compared systems.</p><p>We investigate several RRM techniques to deal with thechannel interference problem and show that beamforming cangreatly reduce the interference and improve the systemperformance. Beamforming, especially sector antennas, alsoreduce the transmitter powers and the necessary dynamic range.A comparison is made between the use of TD/CDMA and pure TDMAwhich clearly shows the performance benefits of usingorthogonal channels that separates the users and reduces theco-channel interference. Different channel selection strategiesare studied and evaluated along with various methods to improvethe capability of system co-existence.</p><p>We also investigate several practical measures to facilitatesystem implementation. Centralized RRM is suitable forguaranteeing QoS but is often considered too complex. With thestudied centralized concept the computational complexity can bereduced by splitting the coverage area into smaller pieces andcover them with one centralized system each. This reduces thecomplexity at the prize of lost capacity due to theuncontrolled interference that the different systems produce.Our investigations show that sector antennas can be used toregain this capacity loss while maintaining high reduction incomplexity. Without capacity loss, the computational complexitycan be reduced by a factor of 40 with sectoring. Theimplementation aspects also include installation sensitivity ofthe indoor architecture and the effect of measurement errors inthe link gains. The robustness against installation errors ishigh but the bunch concept is quite sensitive to largemeasurement errors in the studied indoor environment. Thiseffect can be reduced by additional SIR-margins of the radiolinks.</p><p>The studied bunch concept is shown to be promising for usein future wireless indoor communication systems. It provideshigh performance and is feasible to implement.</p><p><b>Keywords:</b>Radio resource management, indoorcommunication, the bunch concept, centralized RRM, dynamicchannel allocation, channel selection, co-channel interference,power control, feasibility check, capacity, throughput, qualityof service, beamforming, downtilting, sector antennas,co-existence, computational complexity, sensitivity analysis,measurement errors, infrastructure, system implementation,WLAN, HiperLAN/2, IEEE 802.11.</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. 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>

Nos últimos anos, as redes de comunicação móveis se tornaram de fundamental importância para a infraestrutura dos sistemas de comunicação. Uma das áreas de maior crescimento é a computação móvel. Realizada através de sinais de rádio, a quantidade de canais disponíveis raramente é suficiente para atender a crescente demanda. Este trabalho apresenta uma solução para a questão da alocação de canais, um tópico desafiador dentro da área de redes móveis. A implementação de alocação dinâmica com uso de técnicas computacionais clássicas melhora a utilização dos recursos disponíveis,mas necessita de ajustes periódicos para se adequar a novos cenários. Para a construção de um sistema mais flexível e adaptável, a abordagem escolhida utiliza técnicas de Inteligência Artificial. O modelo proposto combina Teoria Nebulosa, Redes Neurais Artificiais e Sistemas Multi-Agentes. As características de cada técnica foram analisadas e identificamos as partes do sistema que poderiam ser beneficiadas por cada uma. O sistema é resultado da combinação coordenada das três técnicas, e constitui um método eficiente e flexível para gerenciamento de recursos de rádio. Após o detalhamento do modelo, realizamos uma simulação de uma rede celular com o sistema proposto e seu comportamento é comparado com uma rede de referência, para verificação das diferenças e melhorias alcançadas. Por fim, apresentamos a situação atual da pesquisa e os possíveis caminhos para aprimoramento do sistema. / In the last years, mobile networks became more important for communication systems’ infrastructure. One area of great growth is mobile computation, which is performed through radio signals. The amount of available channels rarely is enough to attend the increasing demand. This work presents a solution for the channel allocation topic, a challenging topic inside mobile networks area. The implementation of dynamic allocation using classic computational techniques improves the use of available resources, but it needs periodic and frequent adjustments for new scenarios. The construction of a more flexible and adaptable system was achieved using Artificial Intelligence techniques. Proposed model combines Fuzzy Logic, Artificial Neural Networks and Multi-Agents Systems. Features of each technique had been analyzed and we identified the system modules which could be benefited by them. The system is the result of coordinated combination of these three techniques, and constitutes an efficient and flexible method for radio resources management. After model detailing, we executed a cellular network simulation using proposed system, and its behavior is compared with a reference network, presenting reached differences and improvements. Finally, we present current situation of this research and possible ways for system improvement.

Nos últimos anos, as redes de comunicação móveis se tornaram de fundamental importância para a infraestrutura dos sistemas de comunicação. Uma das áreas de maior crescimento é a computação móvel. Realizada através de sinais de rádio, a quantidade de canais disponíveis raramente é suficiente para atender a crescente demanda. Este trabalho apresenta uma solução para a questão da alocação de canais, um tópico desafiador dentro da área de redes móveis. A implementação de alocação dinâmica com uso de técnicas computacionais clássicas melhora a utilização dos recursos disponíveis,mas necessita de ajustes periódicos para se adequar a novos cenários. Para a construção de um sistema mais flexível e adaptável, a abordagem escolhida utiliza técnicas de Inteligência Artificial. O modelo proposto combina Teoria Nebulosa, Redes Neurais Artificiais e Sistemas Multi-Agentes. As características de cada técnica foram analisadas e identificamos as partes do sistema que poderiam ser beneficiadas por cada uma. O sistema é resultado da combinação coordenada das três técnicas, e constitui um método eficiente e flexível para gerenciamento de recursos de rádio. Após o detalhamento do modelo, realizamos uma simulação de uma rede celular com o sistema proposto e seu comportamento é comparado com uma rede de referência, para verificação das diferenças e melhorias alcançadas. Por fim, apresentamos a situação atual da pesquisa e os possíveis caminhos para aprimoramento do sistema. / In the last years, mobile networks became more important for communication systems’ infrastructure. One area of great growth is mobile computation, which is performed through radio signals. The amount of available channels rarely is enough to attend the increasing demand. This work presents a solution for the channel allocation topic, a challenging topic inside mobile networks area. The implementation of dynamic allocation using classic computational techniques improves the use of available resources, but it needs periodic and frequent adjustments for new scenarios. The construction of a more flexible and adaptable system was achieved using Artificial Intelligence techniques. Proposed model combines Fuzzy Logic, Artificial Neural Networks and Multi-Agents Systems. Features of each technique had been analyzed and we identified the system modules which could be benefited by them. The system is the result of coordinated combination of these three techniques, and constitutes an efficient and flexible method for radio resources management. After model detailing, we executed a cellular network simulation using proposed system, and its behavior is compared with a reference network, presenting reached differences and improvements. Finally, we present current situation of this research and possible ways for system improvement.