mended as possible allocations for SRD use: the 870-876 MHz and 915-921 MHz bands. The use of the latter one would mean a great improvement in terms of world-wide harmonization of SRD frequency bands, since 902-928 MHz band is widely used internationally [16]. It is worth noting that though spectrum harmonization efforts are being made, it is a highly difficult – and in some cases not possible – objective to achieve. The benefits of international spectrum harmonization are significant: not only would it allow for economies of scale in the manufacturing of SRDs, but it would also be highly bene- ficial for certain types of applications – the best example is RFID, since RFID-tagged goods can travel around the globe. Currently, the two proposed frequency bands are mostly not being used, totally or par- tially (they are being used as guard bands in mobile communication systems) or being used for military applications [14], which is why they constitute possible candidates for SRD spectrum allocation.
Table 3.2: Reference requirements of selected SRD applications.
Application DC Transmitted
power
Reliability Latency Main techni- cal reference Smart Meter-
ing & Smart Grid
2.5% 100 mW high low to
medium
ETSI TR
102 886
M3N 1.25% 100 mW to
500 mW
high low to
medium
ETSI TR
103 055 Alarm Sys-
tems
<1% (includes periodic net- work checks)
not defined very high (PLR
<0.1%)
medium to high
ETSI TR
103 056 Home &
Building Automation
1% not defined medium to high small to
medium
ETSI TR
102 649-2
from big power plants to distributed micro generators. Smart Grid solutions provide centralized control of a distributed energy production network.
Smart Metering implies the placement of sensors in residential/building resource meters (e.g. water, electricity, gas). Besides the obvious operational efficiencies gained by energy distributors in the process of registering the meter value (which is mostly done manually nowadays), there is also demand for these solutions from end users, since it enables them to monitor their consumption – ever-increasing concern about the efficiency of resource utilization due to environmental and economical reasons drives the need for smarter consumption monitoring solutions [17].
Cellular networks nowadays can provide connectivity for many devices in urban areas, such as parking meters. However, new applications using low cost sensors require a different and more economical means of communication, since the cost and high energy consumption of a cellular module are not viable in such devices. Organizing the devices in a mesh topology, where they can communicate with neighbour nodes at low range and using asynchronous channel access schemes, offers an economic and energy-efficient solution. Being a general term,M3N networksare no more than a network of connected Machine-to-machine (M2M) SRDs (more specifically, sensors and actuators). Devices do not need to be directly connected to a network gateway – instead, some sensors act as routers, passing the information from neighbour nodes towards the gateway. M3N fit directly into the Smart Cities concept, enabling the automation and centralization of monitoring and control functions. Examples of applications are the control of city lighting, distributed measurement of air pollution of temperature, Smart Meter and Smart Grid. Presently, M3N applications fall into the non-specific SRD category – and must use the frequency bands and designated rules accordingly. Currently, the 863-870 MHz band does not provide sufficient
bandwidth for the growth in implementation of M3N, mainly due to the need for the expected higher duty cycle values, transmission power and sensor density. The request for additional bandwidth to cover present and future needs of M3N applications is introduced in [18].
Alarm systemshave the purpose of detecting an event (be it a fire, smoke or an intrusion, for instance) and report it to a central unit and/or spread the message through the network. In terms of data traffic, alarm systems are said to be event-driven, which means it is an external event that triggers a peak in the amount of generated data. Specific alarm applications slightly differ in their requirements. In general, however, they are characterised by the need for high reliability and large latency – while, for instance, a false or missed alarm message would not be acceptable, a delay of several seconds is not a problem in this context. Alarms have a very low duty cycle, since they do not produce a significant amount of information when there are no events to report. However, when an event does occur, the message must be imperatively delivered. This is why, even if not being a high traffic generating application, alarms have limited ability to coexist with other applications and need exclusive frequency bands in order to guarantee this high reliability.
Home and Building Automation systems (also known as smart home systems) allow the control and automatic interaction between several devices such as household appliances, lights, air conditioning, electrical windows and doors. This application implies a medium to high reliability as well as a small latency (since users expect immediate action upon a given control, such as the light turning on when someone enters a room). Different types of alarms and smart metering can be integrated into the system.
While in previous years these devices would be used in a stand-alone fashion (i.e. controlled individu- ally), new smart home systems incorporate them into one intelligent system that coordinate the sensors and actuators in the network. As smart and automated homes become a market trend, demand for such solutions will grow significantly in the next decade.
Finally, the driver for extending theRFIDsub-band to a 915-921 MHz sub-band lies mainly in the near- worldwide harmonization of this band for RFID systems simplifying, for instance, logistics of traded goods across countries. Note that in the case of the other SRD applications presented in this section, the need for more bandwidth is instead driven by system performance. RFID has very specific characteristics that set it apart from other SRDs, namely the fact that DC values are usually quite high (up to 100%) and distance ranges are very low (down to a few centimetres). Since RFID systems are out of the scope of the present work, their requirements are not listed in Table 3.2.
Chapter 4
Simulation of Channel Access Schemes
Given the complexity of radio access schemes and the great variety of parameters on which they are dependent upon, analytical analysis is either very limited due to a number of necessary simplifications or not feasible at all. The performance of the channel access schemes was therefore analysed through a Monte Carlo simulation.
A simulator was developed using the C programming language in order to model the behaviour of a sen- sor network. This chapter firstly presents the simulation scenarios and some parameter values from the literature that were used to model the mentioned scenarios, followed by the description of the simulator’s structure and implementation.