M-ary Aggregate Spread Pulse Modulation in LPWANs for IoT applications

Abstract

<div><div><div><p>In low-power wide-area networks (LPWANs), various trade-offs among the bandwidth, data rates, and energy per bit have different effects on the quality of service under different propagation conditions (e.g. various types of fading), interference scenarios, multi-user requirements, and design constraints. Such compromises, and the manner in which they are implemented, fur- ther affect other technical aspects, such as system’s computational complexity and power efficiency. At the same time, this difference in trade-offs also adds to the technical flexibility in addressing a broader range of the Internet of Things (IoT) applications. This paper addresses a physical layer LPWAN approach based on the Aggregate Spread Pulse Modulation (ASPM) and provides a brief assessment of its properties in an additive white Gaussian noise (AWGN) channel. In the binary ASPM, the control of the quality of service is performed through the change in the spectral efficiency, i.e., the data rate at a given bandwidth. Implementing M-ary encoding in ASPM further enables controlling service quality through changing the energy per bit (in about an order of magnitude range) as an additional trade-off parameter. Such encoding is especially useful for improving the ASPM’s energy per bit performance, thus increasing its range and overall energy efficiency, and making it more attractive for use in LPWANs.</p></div></div></div>

M-Ary Aggregate Spread Pulse Modulation for Robust and Scalable Low-Power Wireless Networks

“…For both noncoherent LoRa and noncoherent M-ASPM, the bit error probability P b in AWGN channel can be expressed as [8]…”

“…One approach to addressing this LoRa scalability limitation is to design a physical layer (PHY) modulation scheme that retains most, if not all, LoRa's advantages, including in the energy consumption and robustness, while providing the ability to better sustain the network capacity when extending its range. The M-ary Aggregate Spread Pulse Modulation (M-ASPM) [8] is an example of such modulation. In this paper, we present an overview of the M-ASPM, and provide an assessment of its suitability and advantages for use in LPWANs.…”

“…The description of M-ary ASPM was previously provided only in [8], where we evaluate the bit error probability for coherent and noncoherent M-ASPM links in an AWGN channel. Thus many of the promising features of this modulation have not yet been explored and/or quantified.…”

“…In the Aggregate Spread Pulse Modulation (ASPM) [8], 232 [9], [10], the information is encoded in the amplitudes A j 233 and/or the ''arrival times'' k j of the pulses in a digital ''pulse 234 train'' x[k] with only relatively small fraction of samples 235 having non-zero values:…”

“…Additive white Gaussian noise (AWGN) is only a ''back-459 ground'' noise component in the congested spectrum of most 460 IoT applications. Nevertheless, assessment of the M-ASPM 461 properties in an AWGN channel provides a suitable bench-462 mark for the subsequent evaluation of the M-ASPM perfor-463 mance under various more realistic propagation conditions 464 and interference scenarios, and such assessment is given 465 in [8]. For example, in an AWGN channel, the uncoded bit 466 error rates (BER) performance of the coherent binary ASPM 467 (M = 2) is identical to that of the binary phase-shift keying 468 (BPSK) modulation.…”