4 research outputs found
Performance Analysis of Clustered LoRa Networks
In this paper, we investigate the uplink transmission performance of low-power wide-area (LPWA) networks with regards to coexisting radio modules. We adopt the long-range (LoRa) radio technique as an example of the network of focus, even though our analysis can be easily extended to other situations. We exploit a new topology to model the network, where the node locations of LoRa follow a Poisson cluster process while other coexisting radio modules follow a Poisson point process. Unlike most of the performance analysis based on stochastic geometry, we take noise into consideration. More specifically, two models, with a fixed and a random number of active LoRa nodes in each cluster, respectively, are considered. To obtain insights, both the exact and simple approximated expressions for coverage probability are derived. Based on them, area spectral efficiency and energy efficiency are obtained. From our analysis, we show how the performance of LPWA networks can be enhanced by adjusting the density of LoRa nodes around each LoRa receiver. Moreover, the simulation results unveil that the optimal number of active LoRa nodes in each cluster exists to maximize the area spectral efficiency
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Analysis of millimeter wave ad hoc networks
Over the coming few years, the next-generation of wireless networks will be standardized and defined. Ad hoc networks, which operate without expensive infrastructure, are desirable for use cases such as military networks or disaster relief. Millimeter wave (mmWave) technology may enable high speed ad hoc networks. Directional antennas and building blockage limit the received interference power while the huge bandwidth enables high data rates. For this reason, understanding the interference and network performance of mmWave ad hoc networks is crucial for next-generation network design.
In my first contribution, I derive the SINR complementary cumulative distribution function (CCDF) for a random single-hop mmWave ad hoc network. These base results are used to further give insights in mmWave ad hoc networks. The SINR distribution is used to compute the transmission capacity of a mmWave ad hoc network using a Taylor bound. The CDF of the interference to noise ratio (INR) is also derived which shows that mmWave ad hoc networks are line-of-sight interference limited. I extend my work in the second contribution to include general clustered Poisson point processes to derive insights in the effect of different spatial interference patterns. Using the developed framework, I derive the ergodic rate of both spatially uniform and cluster mmWave ad hoc networks. I develop scaling trends for the antenna array size to keep the ergodic rate constant. The impact of beam alignment is computed in the final part of the contribution. Finally, I account for the overhead of beam alignment in mmWave ad hoc networks. The final contribution leverages the first two contributions to derive the expected training time a mmWave ad hoc network must perform before data transmission occurs. The results show that the optimal conditions for minimizing the training time are different than the optimal conditions for maximizing rate.Electrical and Computer Engineerin