In this paper, we present results of a study of the data rate fairness among nodes within a LoRaWAN cell. Since LoRa LoRaWAN supports various data rates, we firstly derive the fairest ratios of deploying each data rate within a cell for a fair collision probability. LoRa LoRaWAN, like other frequency modulation based radio interfaces, exhibits the in which only the stronger signal of colliding signals will be extracted. This leads to unfairness, where far nodes or nodes experiencing higher attenuation are less likely to see their packets received correctly. Therefore, we secondly develop a transmission power control algorithm to balance the received signal powers from all nodes regardless of their distances from the gateway for a fair data extraction. Simulations show that our approach achieves higher fairness in data rate than the state-of-art in almost all network configurations.
Low power wide area networks are gaining interest to connect thousands of nodes to the internet of things. However, because the link budget in these networks is huge, nodes suffer from a near-far effect. Nodes far from the base station cannot send to the base station succesfully when closer nodes are transmitting, causing destructive collisions. LoRa, the considered technology in this paper, is a spread spectrum technology. It is known that spread spectrum is also sensitive to this effect. This paper presents a scheme to efficiently optimize the packet error rate fairness inside a LoRaWAN cell. This is achieved by optimizing the power and spreading factor for each node while avoiding near-far problems by allocating distant users to different channels. Simulations show that the packet error rate can be decreased up to 50 for edge nodes in a moderate contention scenario where 1 node per 1000m2 transmits every 10 minutes. There is a fundamental tradeoff between power consumption, data transmission rates, and congestion levels in a wireless network. These three elements influence the performance of rate and power control strategies, and they need to be coordinated judiciously. This paper proposes dynamic rate and power control algorithms for distributed wireless networks that also account for the congestion levels in a network. The design is pursued by formulating state-space models with and without uncertain dynamics and by determining control signals that help meet certain performance criteria (such as robustness and desired levels of signal-to-interference ratio). Simulation results illustrate the performance of the proposed control schemes. In cellular wireless communication systems, transmitted power is regulated to provide each user an acceptable connection by limiting the interference caused by other users. Several models have been considered including: (1) fixed base station assignment where the assignment of users to base stations is fixed, (2) minimum power assignment where a user is iteratively assigned to the base station at which its signal to interference ratio is highest, and (3) diversity reception where a user's signal is combined from several or perhaps all base stations. For the above models, the uplink power control problem can be reduced to finding a vector p of users' transmitter powers satisfying p spl ges I(p) where the jth constraint p sub j spl ges I sub j (p) describes the interference that user j must overcome to achieve an acceptable connection. This work unifies results found for these systems by identifying common properties of the interference constraints. It is also shown that systems in which transmitter powers are subject to maximum power limitations share these common properties. These properties permit a general proof of the synchronous and totally asynchronous convergence of the iteration p(t+1)=I(p(t)) to a unique fixed point at which total transmitted power is minimized. >