Introdução
1.1 Motivação
1.2 Definição
Rádios cognitivos se baseiam no conceito de rádio definido por software (software defined radio, SDR), em que a maior parte das funções do dispositivo de comunicação sem fio são realizadas por software rodando em circuitos eletrônicos de uso geral.
Rádios cognitivos adaptativos podem permitir o uso de técnicas como o compartilhamento dinâmico do espectro, em que os dispositivos localizam faixas de frequência não utilizadas compartilhando canais baseados em sua capacidade livre.
Topo
2. Funcionalidades Propostas
As funcionalidades propostas para rádios cognitivos têm como objetivo imediato possibilitar o compartilhamento dinâmico do espectro de radiofrequências. Um rádio cognitivo deve ser capaz de sensoriar o ambiente (capacidade cognitiva ou sensoriamento do espectro), analisar informações sensoriadas (capacidade de gerenciamento espectro) e adaptar-se às condições do ambiente (capacidade de reconfiguração ou mobilidade do espectro). A seguir estão algumas propostas sendo estudadas atualmente: [8]
Sensoriamento do Espectro
Um rádio cognitivo pode sensoriar o espectro e detectar oportunidades ou “buracos” (“spectrum holes”), faixas de frequência que não estão sendo utilizadas pelos usuários licenciados e que apresentam baixa interferência com eles.
Localização
Ser capaz de determinar sua localização e de outros dispositivos transmissores e selecionar os parâmetros de operação apropriados de acordo com essas informações. Em frequências como aquelas usadas para recepção de satélites, que são somente receptoras e não transmitem sinal, técnicas de localização podem solucionar o problema da interferência, já que somente o sensoriamento não permite a localização de dispositivos receptores próximos.
Seleção Dinâmica de Frequência
Um rádio cognitivo deve ser capaz de mudar sua frequência de operação, baseado nas informações recolhidas no sensoriamento do espectro. A decisão quanto às mudanças pode utilizar sensoriamento do espectro, monitoramento da posição geográfica, entre outros fatores.
Modulação Adaptativa
Técnicas de modulação adaptativa podem modificar características e formas de onda de transmissão para melhorar o acesso ao espectro e minimizar interferências com outros usuários não licenciados ou licenciados. Um rádio cognitivo pode também selecionar um tipo de modulação da transmissão para permitir interoperabilidade entre sistemas diferentes.
Controle de Potência de Transmissão
Controlar a potência de transmissão dinamicamente durante a transmissão de dados permite um dispositivo utilizar os limites máximos apenas quando necessário, em geral reduzindo a potência para permitir o compartilhamento do espectro interferindo minimamente na comunicação dos outros dispositivos no meio.
Topo
.1 OFDM/OFDMA (Orthogonal Frequency Division Multiplexing / Multiple Access)
3.2 Vetor de Alocação
3.3 Detecção de Acessos ao Espectro
O conceito de compartilhamento do espectro, também chamado de spectrum pooling, utiliza rádios cognitivos para permitir acesso público a bandas de frequência já licenciadas. Basicamente propõe a aglomeração de faixas do espectro eletromagnético de diferentes proprietários ou concessionários em uma chamada pool comum. Dessa pool de espectro, usuários não licenciados podem utilizar temporariamente faixas de frequência durante períodos de inatividade de usuários licenciados. A vantagem principal da proposta é que o sistema dos usuários licenciados não precisa de nenhuma alteração. O equipamento existente deve poder operar como se não houvesse outro sistema presente na mesma faixa de frequência. A técnica de modulação OFDM, utilizadas pelos sistemas de comunicação sem fio IEEE 802.11a, g e n, do Institute of Electrical and Electronics Engineers e HIPERLAN/2, do Intituto Europeu de Padrões de Telecomunicações (European Telecommunications Standards Institute, ETSI), proporciona facilidades de implementação de um sistema de compartilhamento do espectro e é explicada a seguir
Desafios
4.1 Modelo do Usuário Licenciado
4.2 Handoff
4.3 Algoritmos de Escalonamento
O impacto do sistema licenciado na camada física do sistema secundário pode ser representeado por múltiplos terminais interferindo em faixas estreitas de banda. Após a fase de detecção, essa representação é reduzida a um vetor binário de alocação do espectro. Para a camada de acesso ao meio (MAC) do sistema não licenciado, só o numero total de subportadoras disponíveis para transmissão de dados é necessário para tarefas como formação de quadros (frames) e gerenciamento de recursos como banda passante disponível
Conclusão
A proposta de Rádios Cognitivos é um tema muito recente, com muita pesquisa ainda a ser feita para que haja implementações utilizáveis. De qualquer forma, não há dúvidas quanto aos benefícios que essa tecnologia tem a trazer, como resolver o problema da escassez de espectro de radiofrequência, melhorar o potencial de desempenho das comunicações sem fio em geral e minimizar a interferência entre dispositivos de rádio, cada vez mais presentes no cotidiano de todos. A proposta mais ampla, de Joseph Mitola, a ser perseguida a longo prazo, promete ainda mais benefícios aos usuários e deve ser pesquisada conforme os avanços tecnológicos permitem ou facilitam sua implementação.
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%4 Power control
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In previous chapters, we demonstrated that a number of fundamental limitations can be overcome if the licensed (primary) transmitter transmits a perfectly known pilot signal or training sequence to aid detection. This pilot signal has the additional benefit of allowing users to measure the local SNR of the primary signal, which can then be used as a proxy for distance from the primary transmitter. Armed with this information, cognitive radios (secondary users) can approximate their distance from the primary transmitter and adjust their transmit power accordingly. We assume the secondary users can measure their local SNR accurately. Due to random channel fluctuations, this may require multiple measurements [10].
We should note that we use SNR, not SINR, as a metric. Local SNR can be measured by allowing the primary transmitter’s pilot signal to double as a synchronization signal so that the secondary transmitters can periodically all fall silent together and measure their local SNR without interference from other secondaries. Alternatively, SINR could be used if the interference resulting from other secondary users can be determined.
In this chapter we present an example of a power control rule which allows secondary users to aggressively increase their transmit powers while still guaranteeing an acceptable level of aggregate interference at the primary receivers. Of particular concern are the effect of different propagation path losses for different systems, the effect of multiple cognitive users, and the effect of heterogeneous transmit powers among the cognitive users. We demonstrate that none of these issues invalidates cognitive radio’s feasibility.
After a brief review of previous work (4.1) and a description of our model (4.2), we consider a single secondary user sharing spectrum with the primary system. We further divide the single secondary user regime into two subcases. We can think of the secondary users as licensed users constrained to a specific power. This could happen if two distinct property rights were auctioned off for a particular frequency band. For example, company A could purchase the right to transmit up to 10 kW on the 800-900 MHz band anywhere in the US. while company B could purchase the right to transmit up to 1 kW on the same band but only when A is not using it. On the other hand, it seems reasonable to allow a secondary user to use more power if he is further from the primary system.
We examine both these cases in section 4.5, followed by the effects of shadowing/fading in section 4.6. In section 4.7, we extend our analysis to multiple secondary users. We consider first the case in which all the secondary users are bound by the same power constraint. Finally, in section 4.8, we allow the secondary users to be heterogeneous in nature and to increase their transmit power with distance from the primary system. This final viewpoint more closely aligns with the traditional view of cognitive radio [12]. After first allowing the secondary users to increase their power without bound, we observe that practical radios will have a minimum detectable SNR [24], so failure to detect a signal means only that the SNR has fallen below some threshold. This caps a cognitive radio’s transmit power and is explored in section 4.9.
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%4.1 Related work
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The idea that interference is local and frequencies may be reused is not new. Spatial considerations for frequency reuse have been studied extensively in cellular systems [32], [33]. However, these systems differ from the cognitive radio case in a number of significant ways.
Most of the interference in a cellular system is within-system interference, caused by devices the spectrum owner designs. It can therefore be tightly controlled, both in terms of its power and its spectral characteristics.
Cognitive radios, on the other hand, do not just cause out-of-cell interference, they cause out-of-system interference. This interference comes from a sea of heterogeneous devices with varying powers, duty cycles, and even propagation path losses. Previous research into frequency reuse in cellular networks has made the reasonable assumption of user homogeneity [34]-[36]. When considering the interaction between cellular telephones or 802.11 access points, one can assume that in-cell and out-of-cell transmitters use the same power control rules and experience the same propagation path loss.
In the case of cognitive radios, however, these assumptions do not hold. Low-powered cognitive radios may be sharing spectrum with a tall television transmitter. We expect the cognitive radios will be operating at ground level and hence will experience faster signal attenuation [37].
This sea of heterogeneous secondary devices must be able to guarantee service to primary users who are already near the limit of decodability in the no outside-interference case. Cell planners, designing their cell sizes to guarantee an acceptable level of interference, often have the additional advantage of a network of base stations whose locations are fixed and known. For (potentially mobile) cognitive radios, which might lack any sort of regulated infrastructure, we will use locally measured SNR in place of distance.
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%4.2 Model
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In our model, we assume a band already potentially assigned to a single-transmitter system. We are particularly interested in long-range primary transmissions such as television, but for the sake of comparison we also present examples involving a shorter-range primary such as a 802.11 wireless access point. Within some protected radius of the primary transmitter, all unshadowed primary receivers must be guaranteed reception, even when the cognitive radios are operating. All transmissions are assumed to be omnidirectional.
In Chapter 2 we showed that secondary users must be able to coherently detect a known pilot signal or training sequence from the primary transmitter. If a training sequence is transmitted as part of the primary transmission, its SNR will be the same as the SNR of the data portion of the transmission. We will make this assumption throughout this chapter.
However, the pilot signal case is more complicated. First of all, the pilot signal may be significantly weaker than the primary’s data signal, perhaps 20 dB or more down. This will have the same result as insurmoutable shadowing (section 4.6), forcing secondary users to detect a 20 dB weaker signal. This effect will be clearly seen if the pilot is sent in a separate frequency band or time slot from the primary transmission. However, if the pilot signal and the primary data signal are sent in the same band, there will be a non-linear effect on the pilot signal’s SNR due to interference from the data signal. Near the primary transmitter, the data signal will dominate the noise experienced by pilot signal detectors, making pilot signal SNR a poor proxy for distance. However, in this high SNR regime, the optimal detector (Chapter 3) is a radiometer, not a coherent detector of a weak signal. The SNR of the entire primary transmission, not just the SNR of the pilot signal, would therefore be an appropriate proxy for distance. For secondary users far from the primary transmitter, especially in the middle of nowhere, the noise from the primary data signal will be significantly attenuated and be much weaker than the ambient noise. This non-linear effect will be addressed in future work.
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%4.3 SNR as a proxy for distance
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The primary system has a minimum required SINR to successfully decode at its target rate R. In the absence of interference, this fldec occurs at a radius rdec from the transmitter. The idea is to guarantee service to primary users within some protected radius (rp) by defining an additional “no-talk radius” (rn) within which secondary users must be quiet (Figure 4.1). At distances from the primary transmitter greater than rn, secondary users might be allowed to transmit. Ideally, these “no-talk regions” would be centered on each of the primary system’s receivers, but we assume that the cognitive radios have no way of knowing these locations.
If there is uncertainty in the noise power, then we can choose rdec first and set oe2 to the maximum tolerable noise at that radius. If the noise power crosses this threshold with the cognitive radios transmitting, then protected users at rp could experience an outage. However, this noise event would cause an outage for primary users at rdec even without the cognitive radios. We also assume that this oe2 is preprogrammed into the cognitive radio, so it does not need to be continually estimated. Designing radios to compensate for changing noise floors is a topic for future research.
Since we are using locally measured SNR as a proxy for distance, it is convenient to represent rdec, rp, and rn in terms of the SNR in dB measured at those points. We assume we are coherently detecting a known signal of the same power as the primary data signal, and that ambient noise is the only source of noise, as in the case of a training sequence. In this case, locally measured SNR can be used straightforwardly as a proxy for distance from the primary transmitter. However, if a primary receiver is a TV antenna on a roof, it might measure an SNR of 0 dB at one location, while a cognitive radio on the ground at the same location might measure -10 dB. Therefore we must specify who is measuring the SNR at each distance. We consider fldec and flp to be measured by a primary receiver, while fln is by a secondary transmitter. Denoting the power of the primary transmitter as P1, and the power of the noise at the primary receiver oe2, we define:
(…)
For example, if the minimum decodable SNR for the primary receiver is 10 dB and a secondary transmitter measures an SNR of -5 dB at rn, then B. We also define to be the margin between fldec and the local SNR measured by a particular secondary user.
As in [38], we represent the propagation-related power attenuation between two users a distance r apart as a function g(r) defined on [0; 1]. We require g(r) to be continuous with 0 < g(r) 0, ffl > 0. We allow different gain functions g11(r), the propagation path loss between the primary transmitter and primary receiver, g12(r), between the primary transmitter and secondary receiver, and g21(r), between the secondary transmitter and primary receiver. Throughout this paper, our examples will be g11(r) = g12(r) = r and g21(r) = r.
For example, for the gain function g11(r) = r-3.5, \Delta = 165 corresponds to a transmitter with about a 52 km range:
(…)
Further, consider u = 1dB and v = 0:01dB as potential operating margins. In this case, rdec – rp = 3300m, while rn – rdec = 34m. Because of the large protected radius, very small increments in dB correspond to large physical distances. This is important, because it means that the necessary operating margins can be quite small. Unless otherwise specified, we will assume u = 1 for our plots.
Our assumption of a 52 km decodability radius is actually quite conservative. KRONTV in San Francisco has an effective service radius of approximately 120 km [39], [40]. Furthermore, attenuation is slower than r-4, which causes small SNR margins to correspond to even greater distances. The magnitude of these differences makes it clear that an accurate model will be essential when designing practical cognitive systems.
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%4.4 Out-of-system interference
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The interference from the secondary systems will be greatest to a user at the edge of the protected radius rp.
That primary user has a maximum amount of out-of-system interference that it can tolerate. We examine the maximum allowable power for a secondary system while still guaranteeing decodability (SINR >= dec) to a user on the protected border. Q1 and Q2 denote the primary and aggregate secondary transmitters’ powers at the primary receiver, i.e. Q1 = P1g11(rp) for a receiver on the edge of the protected region. A guarantee of reception can therefore be expressed as:
(…)
We can express Q1 on the protected border in terms of SNR:
(…)
Substituting into equation (4.2), we see that the secondary system must guarantee:
(…)
This is a fundamental constraint for any secondary system.
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%4.5 Single secondary transmitter
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A one-size-fits-all power constraint must consider a primary receiver and secondary transmitter as close as possible, with the primary on the edge of the protected zone and the secondary on the edge of the no-talk zone. (4.4) implies:
(…)
A more interesting case occurs when the single secondary transmitter is allowed to vary its power depending on its proximity to the protected region. We simply replace the worst case distance rn in equation (4.5) by the secondary’s actual distance r2 from the primary transmitter. We observe that this new power schedule is strictly better than the “one-sizefits all” power limit because a secondary user on the edge of the no-talk region is now a worst case scenario. Since these distances are not known to the cognitive radio, we perform our calculations in terms of SNR.
First, we write rp, the protected radius, in terms of SNR.
(…)
Next, we solve for the distance r2 of the secondary transmitter, in terms of his local SNR.
(…)
Equations (4.6) and (4.7) let us write (4.5), the maximum allowable power for a secondary transmitter, in SNR terms.
(…)
For our example gain functions g11(r) = g12(r) = r-ff1 and g21(r) = r-ff2 this gives us:
(…)
The first term describes how aggressively the primary user is transmitting, i.e. how far a user can travel from the primary transmitter and still decode the signal. Increasing the primary transmitter’s rate without increasing its power decreases \Delta and therefore requires the secondary transmitter to quiet down. The second term represents how tolerant the protected primary receivers are to interference. The final term represents how far the secondary transmitter is from the protected receivers. Also note that if = -u the secondary transmitter is in the protected region and must be silent.
Figure 4.3 shows the effects of the margin \Delta between the primary transmitter and the decodability radius, and also the margin u between the protected radius and the decodbility radius. We observe a few interesting effects.
First, assuming the cognitive radios wish to transmit at -10 dbW, a small \Delta presents a problem (Figure 4.3a,b). This requires a large margin (far in excess of 30 dB). Secondary users must therefore be far more sensitive than the primary users.
For small u (Figure 4.3a,c), the maximum allowable power for the secondary transmitter jumps from zero to possibly health-endangering levels as soon as the secondary transmitter is outside the protected radius. If the secondary users are low powered devices then they only need to know when they are slightly outside the protected region. Therefore, the cognitive radio does not need to be significantly more sensitive than the users of the primary system, which are capable of receiving a signal all the way out to the decodability radius. Because the increase in allowable power is so rapid, any sensitivity beyond that hardly buys the secondary user anything.
A larger margin u allows secondary transmitters to transmit geographically much closer to the protected region. Not only does this allow much greater reuse of physical space, but more powerful secondary transmitters (an 802.11g access point is ss -10 dBW) can also have far less sensitive detectors (Figure 4.3d). This tradeoff cannot be resolved technically; a policy decision needs to be made.
The figures also illustrate the effect of different decay rates ff1 and ff2. If ff2 > ff1, i.e. the secondary user’s transmissions attenuate faster with distance than the primary transmissions do, we see the secondary user can use more power than he could if both systems experienced the same path loss. This is likely to be the case, for example, if the primary transmitter is a tall TV antenna while the secondary users are located on the ground. The significance of the case in which ff1 > ff2 will become apparent in section 4.7.
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%4.6 Single secondary transmitter with shadowing/fading
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We now extend our model to the case in which the secondary transmitter may lie in a shadow (signal loss of fi dB) with respect to the primary signal. A secondary transmitter must now measure a margin of * + fi to be certain that he is outside the no-talk zone.
Adjusting equation (4.9) to account for shadowing, we get:
(…)
Because a secondary transmitter can never assume it is unshadowed, we see that shadowing results in a pure shift of the curve in Figure 4.4. As an aside, we are assuming the gain functions are deterministic, but since we are using local SNR as our distance metric, this result can be extended to a dynamically fading channel by treating a multipath fade as additional shadowing [41].
However, one distinction is worth noting. While multipath fading can be nearly independent between nearby users, shadowing is likely to be highly correlated. This is actually a problem with our model. We have assumed there is no “local continuity” to shadowing, i.e. that a shadowed secondary user could sit right next to an unshadowed primary user. In practical environments, however, if a user is deeply shadowed, other users within a few meters are most likely also deeply shadowed. Since we are only interested in protecting primary users who can decode a signal in the first place, a secondary user shadowed deeply enough that he cannot decode the primary signal could predict that he is likely to be a few meters away from any primary receiver.
This knowledge could potentially confer a benefit (in addition to those discussed in Chapter 2) on a secondary user with the ability to determine whether he is shadowed with respect to the primary transmitter. More importantly, however, is that 10 dB of shadowing will no longer result in exactly a 10 dB shift of the allowable power graph. A shadowed secondary user transmitting inside the protected region has less potential to cause severe interference if local continuity implies an implicit buffer zone around him.
For the sake of simplicity, we ignore this benefit in our model. Considering it would greatly complicate things because our model treats multipath fading and shadowing the same way. However, multipath has no local continuity. A secondary user in a deep multipath fade cannot assume that the users around him are similarly faded.
Multipath fading and shadowing are therefore not interchangeable. The locally continuous nature of shadowing may have important ramifications for cognitive radio protocols. Among other considerations, future techniques to improve detection (such as cooperation among cognitive radios) may be more effective against multipath fading than against shadowing [10].
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%4.7 Multiple licensed secondary transmitters
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Suppose now that we are no longer limited to a single interferer. Outside of the no-talk circle of radius rn, we assume there exists a sea of secondary transmitters, each with power P2. We further assume that there is a limit to how densely these transmitters are packed. Each secondary transmitter uniquely occupies a footprint of area A, so this “secondary sea” has a power density D = P2A . Integrating over this sea gives the aggregate power of the secondary transmissions at a primary receiver on the edge of the protected region.
As in the case of the single licensed transmitter, we assume a constant power density outside the no-talk zone. Later, in section 4.8, we will consider the case in which secondary users are allowed to increase the power of their transmissions as they venture further from the protected region.
We first assume that the secondary transmission power decays as g21(r) = r-ff2, ff2 > 2. We also assume rp AE rn – rp, the distance between the primary receivers and the secondary transmitters. For a primary receiver on the edge of the protected region, the “coast” of the secondary sea can be approximated by a line a distance of rn – rp away. We examine the quality of this approximation in a later calculation (4.14).
(…)
The entire sea of secondary transmitters behaves like a single transmitter of power D * K(ff2), located a distance rn – rp away (i.e. at the coast of the sea), but with a new decay exponent of -ff2 + 2.
For small rn -rp, the majority of the interference comes from the few secondaries closest to the vulnerable primary receiver. As the secondary sea moves further away, more of the sea becomes “visible” to the receiver, explaining why the decay is now as r-ff2+2. The effect of increasing the secondary decay exponent by two is illustrated in Figure 4.3.
This approximation, however, understates the interference caused by the secondary sea in Figure 4.5a. We can upperbound the interference by considering the case where a primary receiver is completely surrounded by a secondary sea a distance rn – rp away. Using our generalized gain functions:
(…)
Specifically, for our example gain functions, we have
(…)
Again, this bound claims that the sea behaves like a single transmitter of power located a distance rn – rp away but with a new decay exponent -ff2 + 2.
Figure 4.6 shows that the straight line approximation is quite good. Having multiple secondary users does change the decay rate of the aggregate interference, but we have already seen that the limits on the allowable transmit power can still be quite generous for large \Delta primaries (TV). For systems (802.11) with smaller \Delta , the change in decay rate could be compensated for with either a larger SNR margin * between the protected radius and the no-talk zone, or a larger SNR margin u to the decodability limit.
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%4.8 Multiple dynamic secondary transmitters
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We now consider the case in which secondary users are allowed to increase the power of their transmissions as they move further from the protected region. Clearly, the rule we pick to govern D(r) will determine the impact of the secondary sea on the primary receivers. Noting that 1g21(r) is an increasing function, we assume the power density to be governed by a rule of the form:
(…)
where ae is a constant that determines how aggressively the power density D(r) should increase with r. This rule can be expressed in terms of local SNR, , in (4.20).
To determine the aggregate interference at a primary receiver on the edge of the protected region, we use the straight line approximation for the coast of the sea. For a particular ae:
(…)
If ae > 2, i.e. D(r2) grows sufficiently slower than g21(r2), then the integral converges.
(…)
With this particular rule for the power density, the sea of secondary transmitters behaves like a single transmitter located rn – rp from the protected radius, with power K(ae) * D0(ae) and gain function g21(r) = r-ae+2. We can plug our expression straight into (4.8) to get an bound on D0(ae).
(…)
From (4.6) and (4.7) we can express r in terms of SNR:
(…)
With (4.18) and (4.19) we can express (4.15) as a function of :
(…)
This equation gives the the allowable power density for secondary transmitters as a function of distance, measured in dB, from the protected region. The more aggressively the secondary transmitters increase their power with distance, the quieter the secondary transmitters near the primary system must become. An example of the allowable density for secondary users interfering with a digital TV station (\Delta = 165) is depicted in Figure 4.7a. This particular plot uses a margin of u = 1, so there must be a margin of at least 11 dB (compensating for 10 dB of possible shadowing) between the protected radius and the secondary users before they are allowed to transmit at all. Figure 4.7b shows that if the margins are too small (i.e. secondary users are allowed to transmit too close to the protected receivers) secondary users everywhere will be crippled by the power density limits.
The primary receivers have a certain margin u of tolerable interference that through policy decisions can be allocated to users at different distances. The more aggressively (smaller ae) the secondary transmitters increase their power with distance, the quieter the secondary transmitters near the primary system must become.
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%4.9 Minimum detectable SNR
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In the preceding sections we mentioned an implicit cap on the transmit powers of the secondary users. Many factors contribute to this upper limit on power, including safety or hardware limitations. It is also affected by a radio’s sensitivity:
As a secondary transmitter moves away from the protected radius, its allowable power increases exponentially. At some distance rmax, however, the local SNR at the secondary transmitter will drop below its minimum detectable SNR, flmin [23]. From this point outwards, the secondary receiver cannot assume it is more than a distance rmax away from the transmitter, no matter what its actual distance. As a result, there is an absolute cap on the secondary transmit power. This in turn changes the aggregate interference at a primary transmitter on the border of the protected region.
(…)
We can express rmax in terms of flmin.
(…)
We can use (4.22), (4.23), and (4.4) to find a bound on D0. Alternatively, we could solve this expression for flmin. If a manufacturer wanted to build cognitive radios that avoid interfering with legacy systems, flmin represents how sensitive his radios’ detection hardware must be.
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%Arquitetura Proposta
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%Visão Geral
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%2. SPECTRUM OPPORTUNITY AND INTERFERENCE CONSTRAINT: DEFINITIONS AND IMPLICATIONS
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In this section, we provide definitions of spectrum opportu-nity and interference constraint.
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%2.1. Spectrum Opportunity
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Intuitively, a channel can be considered as an opportunity ifit is not currently used by primary users. In a network with geographically distributed primary transmitters and receivers,however, the concept of spectrum opportunity is more involved than it at first may appear.
With the help of Figure 1, we identify conditions for achannel to be considered as an opportunity. Consider a pair of secondary users where A is the transmitter and B its in-tended receiver. A channel is an opportunity to A and B ifthey can communicate successfully over this channel while limiting the interference to primary users below a prescribedlevel determined by the regulatory policy. This means that receiver B will not be affected by primary transmitters andtransmitter A will not interfere with primary receivers.
To illustrate the above conditions, we consider monotonicand uniform signal attenuation and omnidirectional antennas. In this case, a channel is an opportunity to A and B if no pri-mary users within a distance of rtx from A are receiving andno primary users within a distance of rrx from B are trans-mitting over this channel (see Figure 1). Clearly, rtx is de-termined by the secondary users’ transmission power and the maximum allowable interference to primary users, while rrxis determined by the primary users’ transmission power and the secondary users’ interference tolerance. They are gener-ally different.
We make the following remarks regarding the above defi-nition of spectrum opportunity.
<= Spectrum opportunity is a local concept defined withrespect to a particular pair of secondary users. It depends on the location of not only the secondary trans-mitter but also the secondary receiver. For multicast and broadcast, spectrum opportunity is open for inter-pretation, and results in networking tradeoffs.
<= Spectrum opportunity is determined by the communi-cation activities of primary users rather than that of secondary users. Failed communications caused by colli-sions among secondary users do not disqualify a channel from being an opportunity.
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MSN: celinomenezes@pop.com.br
EMAIL: celinomenezes@gmail.com
especialista em textos de medicina, com vários trabalhos publicados no exterior (área de parasitologia) – criptosporidium e giardia). desde 1992
além de medicina também atuo nas áreas de eletrônica, eletricidade, engenharia, etc
Atualmente estou cobrando R$4,50 (4 reais e cinquenta centavos) a página a ser traduzida do inglês para o português e R$9,50(nove reais e cinquenta centavos) do português para o inglês. Por exemplo, se vc tiver 10 páginas para traduzir (10 x R$4,50 = R$45,00) OK. Estou no mercado de traduções técnicas desde 1990 e atualmente estou atingindo a incrível marca de 20 mil páginas traduzidas. Maiores informações entre em contato comigo. Obrigado.
%3. SPECTRUM OPPORTUNITY DETECTION
% ———————————————
In this section, we study the implication of the spectrum op-portunity definition given in Section 2.1 on the spectrum opportunity detection.From the definition of spectrum opportunity illustrated in Figure 1, it is clear that in a general network setting, spectrumopportunity detection needs to be performed jointly by the secondary transmitter and receiver. It thus has both signal processing and networking aspects.
Consider the OSA network example given in Section 1.At the beginning of each slot, a pair of communicating secondary users need to determine whether a chosen channel isan opportunity in this slot. Ignore for now the contention among secondary users. One approach to opportunity de-tection is as follows [6]. The transmitter first detects the receiving activities of primary users in its neighborhood (seeFigure 1). If the channel is available (no primary receivers nearby), it transmits a short request-to-send (RTS) messageto the receiver. The receiver, upon successfully receiving the RTS, knows that the channel is also available at the receiverside (no primary transmitters nearby since RTS has been successfully received) and replies with a clear-to-send (CTS) mes-sage. A successful exchange of RTS-CTS completes opportunity detection and is followed by data transmission.
What remains to be solved is the detection of the receiv-ing activities of primary users by the secondary transmitter.
Without assuming cooperation from primary users, primaryreceivers are much harder to detect than primary transmitters. For the application of secondary wireless services op-erating in the TV bands, Wild and Ramchandran [7] proposed to exploit the local oscillator leakage power emitted by theRF front end of TV receivers to detect the presence of primary receivers. The difficulty of this approach lies in its shortdetection range and long detection time to achieve accuracy.
Another approach is to transform the problem of detect-ing primary receivers to detecting primary transmitters. Let Rp denote the transmission range of primary users, i.e., pri-mary receivers are within Rp distance to their transmitters.A secondary transmitter can thus determine that a channel is available if no primary transmitters are detected within a dis-tance of Rp + rtx as illustrated in Figure 2. This approach is,however, is conservative that may lead to overlooked opportunities. As shown in Figure 2, the transmission activities ofprimary nodes X and Y may prevent A from accessing an op-portunity even though the intended receivers of X and Y areoutside the interfering range rtx of A. Note that by adjustingthe detection range with Rp + rtx being the most conserva-tive, we reach tradeoffs between the throughput of secondary users and interference to primary users.
This approach reduces spectrum opportunity detection toa classic signal processing problem. As discussed in [8], based on the secondary user’s knowledge of the signal characteris-tics of primary users, three traditional signal detection techniques can be employed: matched filter, energy detector (radiometer), and cyclostationary feature detector.
% ———————————————
Desconto especial e novo preço das traduções – Tradutor de Inglês
O preço da tradução agora é só R$4,50 – Tradutor de inglês Técnico
Aproveitando agora a época das Férias, estou reduzindo o preço das traduções de inglês para português, o preço agora é de apenas R$4,50. Se vc possuir 10 páginas para traduzir inglês>português, o preço será de 45 reais. O preço da tradução de português para inglês é de apenas R$9,50, se vc tiver 10 páginas para traduzir português> inglês, o preço será de 95 reais. Este preço é imbatível, esta bem abaixo de qualquer tabela oficial do mercado de tradução. Se vc precisar de tradução técnica de inglês. Entre em contato antes comigo para que vc tenha um trabalho rápido, eficiente e de qualidade e por um preço bem acessivel que não vai pesar no seu bolso. Lembrando sempre que estou no mercado de traduções desde 1990! Obrigado!
tradução de inglês técnico
TRADUTOR DE INGLÊS TÉCNICO
celinomenezes@pop.com.br
tradução de inglês -technical english translator -
sou TRADUTOR DE INGLÊS celinomenezes@pop.com.br ou celinomenezes@gmail.com para todas as áreas universitárias inglês/português – português/inglês. também espanhol/português e espanhol/inglês. Orçamento a combinar -Maiores informações ligue: (35) 9945-8512
SKYPE: celinomenezes
MSN: celinomenezes@pop.com.br
EMAIL: celinomenezes@gmail.com
especialista em textos de medicina, com vários trabalhos publicados no exterior (área de parasitologia) – criptosporidium e giardia). desde 1992
além de medicina também atuo nas áreas de eletrônica, eletricidade, engenharia, etc
Atualmente estou cobrando R$4,50 (4 reais e cinquenta centavos) a página a ser traduzida do inglês para o português e R$9,50(nove reais e cinquenta centavos) do português para o inglês. Por exemplo, se vc tiver 10 páginas para traduzir (10 x R$4,50 = R$45,00) OK. Estou no mercado de traduções técnicas desde 1990 e atualmente estou atingindo a incrível marca de 20 mil páginas traduzidas. Maiores informações entre em contato comigo. Obrigado.
%4. TRANSMISSION POWER CONTROL
% ———————————————
Transmission power control of secondary users is a complexissue. To illustrate the basic parameters that affect power control, we ignore shadowing and fading and focus on a single secondary user. Consider first that the secondary transmitter A is able to detect the presence of primary receivers within adistance of d (see Figure 1 with rtx replaced by d).
The trans-mission power Ptx of A should ensure that the signal strengthat d away from A is below the maximum allowable interfer-ence level \Theta . This leads to Ptx <= \Theta d\Theta , where \Theta is the path attenuation factor. The above equation in-dicates how the maximum transmission power of a secondary user depends on the detection range d of its spectrum detec-tor, the prescribed maximum interference level \Theta , and the pathloss factor \Theta .
When the secondary user can only detect the presence ofprimary transmitters within a distance of d (see Figure 2 with Rp + rtx = d), we have, Ptx <= \Theta (d português, o preço será de 45 reais. O preço da tradução de português para inglês é de apenas R$9,50, se vc tiver 10 páginas para traduzir português> inglês, o preço será de 95 reais. Este preço é imbatível, esta bem abaixo de qualquer tabela oficial do mercado de tradução. Se vc precisar de tradução técnica de inglês. Entre em contato antes comigo para que vc tenha um trabalho rápido, eficiente e de qualidade e por um preço bem acessivel que não vai pesar no seu bolso. Lembrando sempre que estou no mercado de traduções desde 1990! Obrigado!
tradução de inglês técnico
TRADUTOR DE INGLÊS TÉCNICO
celinomenezes@pop.com.br
tradução de inglês -technical english translator -
sou TRADUTOR DE INGLÊS celinomenezes@pop.com.br ou celinomenezes@gmail.com para todas as áreas universitárias inglês/português – português/inglês. também espanhol/português e espanhol/inglês. Orçamento a combinar -Maiores informações ligue: (35) 9945-8512
SKYPE: celinomenezes
MSN: celinomenezes@pop.com.br
EMAIL: celinomenezes@gmail.com
especialista em textos de medicina, com vários trabalhos publicados no exterior (área de parasitologia) – criptosporidium e giardia). desde 1992
além de medicina também atuo nas áreas de eletrônica, eletricidade, engenharia, etc
Atualmente estou cobrando R$4,50 (4 reais e cinquenta centavos) a página a ser traduzida do inglês para o português e R$9,50(nove reais e cinquenta centavos) do português para o inglês. Por exemplo, se vc tiver 10 páginas para traduzir (10 x R$4,50 = R$45,00) OK. Estou no mercado de traduções técnicas desde 1990 e atualmente estou atingindo a incrível marca de 20 mil páginas traduzidas. Maiores informações entre em contato comigo. Obrigado.