Low Power Wide Area (LPWA) networks are known to be highly vulnerable to external in-band interference in terms of packet collisions which may substantially degrade the system performance. In order to enhance the performance in such cases, the telegram splitting (TS) method has been proposed recently. This approach exploits the typical burstiness of the interference via forward error correction (FEC) and offers a substantial performance improvement compared to other methods for packet transmissions in LPWA networks. While it has been already demonstrated that the TS method benefits from knowledge on the current interference state at the receiver side, corresponding practical receiver algorithms of high performance are still missing. The modeling of the bursty interference via Markov chains leads to the optimal detector in terms of a-posteriori symbol error probability. However, this solution requires a high computational complexity, assumes an a-priori knowledge on the interference characteristics and lacks flexibility. We propose a further developed scheme with increased flexibility and introduce an approach to reduce its complexity while maintaining a close-to-optimum performance. In particular, the proposed low-complexity solution substantially outperforms existing practical methods in terms of packet error rate and therefore is highly beneficial for practical LPWA network scenarios.

In the context of the Internet-of-Things (IoT), wireless connectivity of wide spread sensor networks for infrastructure and environment monitoring is one of the essential factors for implementation. Low-power wide-area networks (LPWAN) are cost-effective solutions for such applications. Their high maximum coupling loss makes them also appealing for deep indoor-to-outdoor applications. However, no suitable channel models for these scenarios are available, especially taking the long-term effects of stationary transmitters and receivers into account. Such long-term effects are e.g. generated by the opening or closing of doors. The consideration of these long-term effects are important for LPWAN as many use-cases only require a single successful transmission per day. To develop a suitable channel model we performed extensive long-term measurements in a suburban, a commercial and an industrial area. For these we used up to 50 special transmitters that enabled us to measure the channel characteristics over a period of several weeks with a temporal resolution of five minutes. Using thousands of measurement data we developed a generic indoor-to-outdoor channel model for LPWANs operated in license-exempt frequency bands based on statistical analyses of the obtained data.

Low PowerWide Area (LPWA) networks are known to be very vulnerable to external in-band interference in terms of packet collisions, which may substantially degrade the system performance. In order to improve the performance under collisions, the so-called telegram splitting (TS) method has been proposed recently. This approach is based on the assumption of a bursty behavior of the interference, which can be efficiently accounted for by forward error correction. In this paper, we assume that all interferers have the same structure in terms of packet duration and signal variance, which are assumed to be known to the receiver. However, the number of simultaneously active interfering transmissions and their scheduling are unknown. Hence, the amount of interference observed in each symbol interval can vary which needs to be accounted for by the receiver in order to increase the reliability of transmission. For this scenario, we develop the optimal signal detection strategy. We also show that the proposed method substantially outperforms a baseline scheme in terms of packet error rate.

This paper proposes an analytical framework for the prediction of decoding error probabilities in heterogeneous wireless environments, where transmissions from various radio nodes with distinct Poisson-arrival rates and packet lengths populate the channel. Random channel access without feedback is assumed, where partial packet collisions can lead to the loss of packets. The analysis is based on the modeling of the collision length distribution between competing nodes. With recent results from information theory in the finite block length regime, we provide bounds on achievable decoding error probabilities for a given interference scenario. The new framework enables jointly considering inter- and intra-system interference, which is an important aspect in unlicensed radio bands. The framework's applicability to optimize system designs is demonstrated for a typical low-power wide area network scenario. We study the tradeoff between reliability and code rate for a point-to-point link and present achievable throughput regions. The analysis reveals the superior performance of coded time-hopping spread spectrum systems. They reach very low error probability even under strong interference for wide ranges of practically relevant load regions.

This paper analyzes the reliability and throughput of the telegram-splitting concept in the presence of inter-system and intra-system interference. Using telegram splitting, the data of one telegram is split into multiple sub-packets, which are then transmitted with temporal spacing. As a result, collisions with other telegrams destroy only some sub-packets that can be recovered using forward error correction. Consequently, the reliability of the data transmission in case of inter- and intra-system interference - a significant problem in license-exempt bands - is highly improved. In this paper, probabilities for the resulting telegram error rate of random media access systems using telegram splitting are derived. Furthermore, the achievable throughput is analyzed. The theoretical considerations in addition to simulation results prove the significant gain of the telegram-splitting concept for telemetry systems.