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The LoRa physical layer is one of the most promising Low Power Wide-AreaNetwork (LPWAN) technologies for future Internet of Things (IoT) applications.It provides a flexible adaptation of coverage and data rate by allocatingdifferent Spreading Factors (SFs) and transmit powers to end-devices. We focuson improving throughput fairness while reducing energy consumption. Whereasmost existing methods assume perfect SF orthogonality and ignore the harmfuleffects of inter-SF interferences, we formulate a joint SF and power allocationproblem to maximize the minimum uplink throughput of end-devices, subject toco-SF and inter-SF interferences, and power constraints. This results into amixed-integer non-linear optimization, which, for tractability, is split intotwo sub-problems: firstly, the SF assignment for fixed transmit powers, andsecondly, the power allocation given the previously obtained assignmentsolution. For the first sub-problem, we propose a low-complexity many-to-onematching algorithm between SFs and end-devices. For the second one, given itsintractability, we transform it using two types of constraints approximation: alinearized and a quadratic version. Our performance evaluation demonstratesthat the proposed joint SF allocation and power optimization enables todrastically enhance various performance objectives such as throughput, fairnessand power consumption, and that it outperforms baseline schemes.

Joint Allocation Strategies of Power and Spreading Factors with Imperfect Orthogonality in LoRa Networks