Contention-Aware Adaptive Data Rate for Throughput Optimization in LoRaWAN

Abstract

In Long Range Wide Area Network (LoRaWAN), the data rate of the devices can be adjusted to optimize the throughput by changing the spreading factor. However, the adaptive data rate has to be carefully utilized because the collision probability, which directly affects the throughput, is changed according to the use of spreading factors. Namely, the greater the number of devices using the same spreading factor, the greater the probability of collision, resulting in a decrease of total throughput. Nevertheless, in the current system, the only criteria to determine the data rate to be adjusted is a link quality. Therefore, contention-aware adaptive data rate should be designed for the throughput optimization. Here, the number of devices which can use a specific data rate is restricted, and accordingly the optimization problem can be regarded as constrained optimization. To find an optimal solution, we adopt the gradient projection method. By adjusting the data rate based on the retrieved set of optimal data rate, the system performance can be significantly improved. The numerical results demonstrate that the proposed method outperforms the comparisons regardless of the number of devices and is close to the theoretical upper bound of throughput.

A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

“…In this paper, we performed a comprehensive analysis of solutions that have been developed to optimize ADR algorithms. The proposed optimization techniques address specific challenges such as scalability [ 28 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ], throughput [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ] and energy efficiency [ 20 , 46 , 47 , 48 , 49 , 50 , 51 ]. Our analysis distinguished the approaches used and highlighted the challenges and performance in the studies considered.…”

“…ADR schemes that maximize throughput maximizing solutions for the ADR scheme were discussed in [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. The ordered waterfalling technique used in [ 37 ] for even distribution of channel load between the end nodes in the system by equally distributing SFs and then channel utilization.…”

“…This algorithm is designed under the assumption that end nodes transmit with the uniform data rate and payload which is not practical. When we compare it to [ 39 ] which uses the gradient projection method we find that their approach also uses the load balancing approach but factors in the contention issue in optimising ADR making it a better scheme in maximizing throughput. The algorithm in [ 40 ] uses all four transmission parameters to maximize the DER and attempts to fairly allocate data rates.…”

“…A contention-aware ADR scheme, developed by [ 39 ] traces the distribution of end nodes for every SF and seeks to expand the number of gadgets utilizing low SFs. The authors attempt optimization of throughput in networks where the same SF can be used by a huge number of end nodes.…”

High Reliability in LoRaWAN

“…We think that the SNR distribution pattern and parameters estimation as described in Section IV are key for optimized ADR decisions. The ADR algorithm can be replaced by a load-balancing algorithm to minimize contention on a single cell LoRaWAN network [19]. This approach increases overall throughput but this may come at the cost of decreasing the network's reliability.…”