Sezgirligini (Rx), antennaning daromadini

LoRaWAN-da qamrov doirasini optimallashtirish strategiyalari
LoRaWAN texnologiyasi bilan tarmoqdagi diapazonni yaxshilash uchun quyidagi fikrlarni hisobga olish kerak:

1. 
   Gateway joylashuvi: Tx va Rx antennalari o'rtasida optik ko'rinishni o'rnating. Antennalar orasidagi optik ko'rinishga ega bo'lish uchun antennalarning balandligini oshiring. Ichkarida ishlatishdan ko'ra tashqi antennalardan foydalanish har doim yaxshiroqdir.
   
2. 
   Antennani tanlash: an'anaviy rodli antennalar energiyani gorizontal tekislikda to'playdi. Antenna yaqinidagi to'siqlardan qoching. Bundan tashqari, ularni har doim binoning yon tomoniga emas, balki ustunga joylashtirish yaxshiroqdir. Antenna ehtiyotkorlik bilan tanlansa va antennaning egilishi va belgilangan maksimal daromadi bir-biriga nisbatan optimal tarzda sozlangan bo'lsa, diapazon yaxshilanishi kerak.
   
3. 
   Ulanish materialini tanlash: sifatli konnektorlardan (N-tipli ulagichlar) va kabeldan foydalaning (LMR 400 yoki ekvivalenti, 100 m uchun 1,5 dB dan kam yo'qotish bilan). Ulanish apparatidagi yo'qotishlarni kamaytirish uchun stansiya va antennalar o'rtasidagi ulanishning davomiyligini imkon qadar qisqa tutish ham muhimdir.
   
4. 
   Boshqa radio jihozlariga yaqin joyda o'rnatish: kuchli shovqinlardan saqlaning, masalan, atrofdagi GSM yoki UMTS stantsiyalari. Iltimos, ishlab chiqaruvchining foydalanish bo'yicha ko'rsatmalariga qarang (odatda "birgalikda joylashish " atamasi ostida topiladi).
   
5. 
   Umuman olganda, LoRaWAN shlyuzining o'rnatilishi etarli kuchlanish va chaqmoqlardan himoya bilan birga bo'lishi kerakligini qisqacha aytib o'tish kerak.
   

Abstract—As LoRaWAN networks are actively being deployed in the field, it is important to comprehend the limitations of this Low Power Wide Area Network technology. Previous work has raised questions in terms of the scalability and capacity of LoRaWAN networks as the number of end devices grows to hundreds or thousands per gateway. Some works have modeled LoRaWAN networks as pure ALOHA networks, which fails to capture important characteristics such as the capture effect and the effects of interference. Other works provide a more comprehensive model by relying on empirical and stochastic techniques. This work uses a different approach where a LoRa error model is constructed from extensive complex baseband bit error rate simulations and used as an interference model. The error model is combined with the LoRaWAN MAC protocol in an ns-3 module that enables to study multi channel, multi spreading factor, multi gateway, bi-directional LoRaWAN networks with thousands of end devices. Using the lorawan ns-3 module, a scalability analysis of LoRaWAN shows the detrimental impact of downstream traffic on the delivery ratio of confirmed upstream traffic. The analysis shows that increasing gateway density can ameliorate but not eliminate this effect, as stringent duty cycle requirements for gateways continue to limit downstream opportunities. Index Terms—LPWAN, LoRa, LoRaWAN, scalability, ns-3, simulation.

The LoRaWAN ns-3 module includes the “lorawan-tracingexample.cc“ example which was used for all simulations discussed in this section. It enables automation of simulations from a CLI by setting simulation parameters and outputting ns-3 tracing results to csv files. The simulations focused on a number of different scenarios, which are detailed in the subsections below. All simulations consist of one, two or four gateways and a configurable number of end devices deployed in a disc with a 6 100m radius 2 . All gateways and end devices are configured to use the same 125kHz LoRaWAN channel (868.100MHz), with the exception of the high power RW2 channel at 869.525MHz which lies in a sub-band with a 10% RDC restriction. This single upstream channel scenario is similar to that of a “the things gateway” as sold by The Things Networks. End devices employ Activation By Personalisation and as such no network join messages are exchanged. The gateways are deployed at fixed positions, which depend on the number of gateways in the simulation. In case of one gateway, it is positioned in the origin of the disc. In case of two gateways, they are positioned one radius apart on a diameter line of the disc. In case of four gateways, they are positioned on the corners of a square which is centered on the disc origin and which has a diagonal equal to the disc radius. The gateway positions are visualized in figure 7. The end devices are uniformly distributed in the disc (using the UniformDiscPositionAllocator in ns3) and have a fixed position during the simulation. For all experiments the default propagation loss model was used in ns-3. This model, named ’LogDistancePropagationLoss‘, has a 3.0 exponent at a 46.6777 dB reference loss at one meter. Simulation scenarios are run for three different upstream data generation periods: 600, 6 000 and 60 000 seconds. Each simulation is run for a simulation time equal to hundred times the upstream data generation period. For every end device, the transmission time of the first upstream packet is picked from a random variable uniformly distributed between zero and the upstream period. Subsequent upstream packets are periodically generated according to the data generation period. Upstream packets have an application payload of 8 bytes, which implies a PHY payload of 21 bytes.
Area Network (LPWAN) protocols such as NB-IoT [7], Sigfox [23], and many others. LoRaWAN is a suitable solution for those applications that require communication over a long range with low data rate and low power requirements like smart city, agriculture, smart health center, and many more. The deployment of the LoRaWAN network is happening all over the world [5]. For example, in UK, Southampton city deployed with LoRaWAN test bed to evaluate LoRaWAN network functionality for large scale deployment [10]. The performance of LoRaWAN network highly depends on network design parameters. We can significantly enhance the network performance in terms of scalability (network capacity) and packet success probability by appropriate selection of network designing parameters like cell radius (R) and radio resources like Spreading Factors (SF), Bandwidth (BW), Transmission Power (TP), Code Rate (CR), etc. In literature, many researchers have contributed towards optimal spreading factor allocation [15], [12], [9], [30] to improve the overall system performance of a LoRaWAN network. As the LoRaWAN network suffers from scalability and throughput issues, it is preferable to conduct a network designing based study before deploying any IoT application network.