The use of large-scale antenna arrays grants considerable benefits in energy and spectral efficiency to wireless systems due to spatial resolution and array gain techniques. By assuming a dominant line-of-sight environment in a massive multiple-input multiple-output scenario, we derive analytical expressions for the sum-capacity. Then, we show that convenient simplifications on the sum-capacity expressions are possible when working at low and high signal-to-noise ratio regimes. Furthermore, in the case of low and high signal-to-noise ratio regimes, it is demonstrated that the Gamma probability density function can approximate the probability density function of the instantaneous channel sum-capacity as the number of served devices and base station antennas grows, respectively. A second important demonstration presented in this work is that a Gamma probability density function can also be used to approximate the probability density function of the summation of the channel’s singular values as the number of devices increases. Finally, it is important to highlight that the presented framework is useful for a massive number of Internet of Things devices as we show that the transmit power of each device can be made inversely proportional to the number of base station antennas.
We derive exact closed-form expressions for Long Range (LoRa) bit error probability and diversity order for channels subject to Nakagami-m, Rayleigh and Rician fading. Analytical expressions are compared with numerical results, showing the accuracy of our proposed exact expressions. In the limiting case of the Nakagami and Rice parameters, our bit error probability expressions specialize into the non-fading case.
This paper presents the results and analysis of diffraction measurements around a building corner at 10 GHz. Radio channel measurement setup contains a 4-port vector network analyzer and two virtual antenna arrays. Angle of arrival analysis is carried out to distinguish the diffracted path from the other multipath components in the impulse response. Results are analyzed with respect to the Fresnel diffraction parameter and diffraction angle, and compared with the knife edge diffraction (KED) and absorbing screen diffraction losses, respectively. The absorbing screen approach is concluded to give reasonable fit for the measurements in the shadow region, but a poor fit near to the shadow boundary and in the illuminated region. The analysis of the corner diffraction shows that a building corner can be modeled by the KED-theory at 10 GHz.
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