This paper deals with a cloud radio access network (CRAN)<br>architecture for the LoRa system. In the suggested design,<br>the gateway embeds a limited remote radio head (RRH),<br>including the analog radio-frequency (RF) analog part, the<br>digital-to-analog and analog-to-digital conversion, and a<br>digital front-end (DFE). The other LoRa network functions,<br>including the physical (PHY) layer, the LoRaWAN medium<br>access control (MAC) layer, and the application and customer<br>servers are implemented as cloud resources. The<br>presented approach leads to a flexible RAN that is robust<br>to the variations of capacity needs. Furthermore, it allows<br>us to test very specific LoRa features, such as the detection<br>or demodulation, while bypassing the other ones including<br>the hardware RRH. The methodology and tools we<br>used to deploy a LoRa cloud RAN are detailed, and results<br>concerning the performance indicator (CPU load, memory<br>consumption) are provided as well.
This paper deals with multipath channel estimation and equalization in LoRa. It is suggested to take advantage of the cyclic property of the symbols in the LoRa frame preamble to obtain an interference-free version of the symbols in the frequency domain. Then, estimation methods used in multicarrier systems can be applied, such as the least square (LS), and the minimum mean square error (MMSE) estimators. It is shown that the cyclic property in LoRa is inherently independent of the length of the channel, making these estimation techniques robust to any frequency-selective channel. In addition the frequency domain zero-forcing (ZF) equalizer is used, and an original phase equalizer is introduced, taking advantage of the constant modulus property of LoRa symbols in the frequency domain. The performance of the investigated estimators and equalizers is shown through simulations, and applications to the presented results are further discussed.
Integrated Access and Backhaul (IAB) allows to ease the deployment of gNodeBs (gNBs) in a 5G network by connecting them using cellular connectivity. The radio frequencies to achieve such a result can be the same as the ones used to connect User Equipment (UE) (in-band) or specific ones can be reserved (out-of-band). Both sub 6 GHz and millimeter wave (mmWave) frequencies can be used. IAB is relatively new and several contributions have been studying the lower layers (i.e. physical and link) in order to improve performance in scheduling and resource allocation. However, performance results are also very dependent on how the routing is implemented at the network layer which is an aspect that is not much studied in the state of the art. In this paper, we evaluate the performance of several IAB topologies against a topology without IAB-nodes. Results confirm the conclusions of the state of the art by showing that adding IABnodes significantly improve performance in terms of delay (more than 90 ms shorter delay) and Packet Delivery Ratio (PDR) (by up to 15%), and also allows to extend the coverage area. These results reveal the high potential of IAB that could be improved even more using efficient routing.
This paper deals with a general and complete analysis of the frame error rate in LoRa system, not only considering the payload error rate, but also the sync word (carrying network information) and the header (carrying control information) error rates. It is proved that, in the high signal-to-noise ratio (SNR) range, it is more likely to reject a LoRa frame due to an erroneous sync word estimation rather than an erroneous header or payload decoding, due to the fact that it is not coded. The theoretical results are then verified through simulations.
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