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.NET There are similarities between some aspects of .NET and the Java technologies. This is more a consequence of convergent evolution of software than it is copying. In the world of software, it is relatively easy for developers to pick up a good idea and adapt and enhance it in some new context. As an example, Microsoft s original ODBC was a smart way of providing database-neutral source code, a concept that reappears in later offerings like JDBC (and it is almost certain that Microsoft s .NET model for web client/web server interaction will be mimicked in future Java offerings). With .NET, Java-like features include:

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the temporal drop of interference from the macrocell below a given threshold allows the users in the microcell to communicate; one speaks from an opportunistic transmission or interference window Therefore, the microcell user reports the experienced macrocell interference level to the microcell base station, which transmits packets only during opportunistic transmission windows The temporal duration of such opportunistic windows depends on many factors, however, most notably on the: temporal characteristics of the macrocell interference; PHY layer used in the mircocell As for the macrocell interference, it is caused by the macrocell base stations adjacent to the microcell hot spot Three of them, BS0-BS2, have been depicted in Figure 109; however, there are clearly more interfering tiers Their transmission power is known to vary in time due to the closed-loop power control to their associated mobile terminals.

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The frequency of change of the power control commands clearly depends on the macrocell propagation environment and the speed of the macrocell mobile terminals; ie if shadowing and fading are severe then the dynamic range of power control can be very large (10 20 dB in the downlink) and if the majority of the terminals moves very fast then the temporal variations are high (within ms) A typical example temporal evolution of such an interference power due to 17 macrocell base stations, as observed in a given location within the microcell, is shown in Figure 1010 The depicted interference power variations follow a Gaussian distribution in dB We will use the Gaussian property to facilitate some closed form mathematical analysis for the purpose of cell planning; however, it ought to be noted that the interference power is by no means guaranteed to be Gaussian distributed.

Indeed, it has been observed that the distribution differs from Gaussianity, particularly under heavy macrocell load We will utilise the Gaussian assumption, nonetheless, because it yields some good performance indicators We clearly observe from the figure that, at a given interference threshold, opportunistic transmission windows occur They are random and can be statistically described by a frequency and duration of occurrence We will deal with their description below, but will confine for the moment to the observation that the higher the threshold, the longer the opportunistic window In Figure 1010, thresholds IThr 1 and IThr 2 have been depicted, where IThr 1 > IThr 2 These thresholds are associated with two given PHY mechanisms (modulation + coding), ie PHY1 and PHY2 Clearly,.

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