Mathematical models for radio signals dynamic range prediction in space-scattered mobile radiocommunication networks

Abstract

A computer tool for generating test radio signals in the space of one repeat as an amplitude-modulated mix of composite waves of the radio signal transmitted in time space, and take into account repeat ability -as an amplitude-modulated mix of radio signals transmitted along the time axis of the k-th repeats.The developed computer tool provides a verification procedure the correct operation of the software of radio computer systems by generating test radio signals according to the specified parameters with high correctness of their reproduction and taking into account the properties of repeat ability and stochasticity.

On node density - outage probability tradeoff in wireless networks

“…1 illustrates this. The distribution functions of g a in various scenarios have been given in [12] [13].…”

“…Transmitter i produces the average power P ai = P t g a (R i ) at the receiver input. We define the interference-to-noise ratio (INR) d a , also known as dynamic range [11]- [13], in the ensemble of the interfering signals via the most powerful signal at the Rx input 5 , where P 0 is the noise level and, without loss of generality, we index the transmitters in the order of decreasing Rx power, P a1 ≥ P a2 ≥ ... ≥ P aN , and N is the number of transmitters. The most powerful signal is coming from the transmitter located at the minimum distance r 1 , P a1 = P t g a (r 1 ).…”

“…To overcome this difficulty, we adopt a different approach: instead of relying on the total interference power as a performance indicator, we use the power of the nearest (dominant) interferer and follow the approach originally proposed in [11]- [13]. As a result, closed-form analytical performance evaluation becomes straightforward and significant insight can be obtained using this method, including the scenarios where nearest interferers are cancelled, either via linear or nonlinear filtering techniques, and/or when interfering signals are subject to a broad class of fading processes, including all popular fading models.…”

The impact of fading and interference cancelation on node density - Outage probability tradeoff in wireless networks

“…the beneficial effect of cancelling is slightly offset by fading (since Γ(km/ν + 1) is an increasing function of k) but otherwise follows the same tendency as without fading (see (10)). Since the INR is the scaled interference power, the later will follow the same distribution as in (21) (up to a constant) and, thus, Pr {P sk > x} is a function of regular variation so that Theorem 2 applies, i.e.…”

“…Theorem 2: Consider the outage probability in (10). At the low outage region, it converges to the outage probability defined via the total interference power, i.e.…”