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The evolution of the LTE standard with Release-14 has introduced several changes in the physical layer with a goal of catering to the needs of Intelligent Transportation Systems (ITS). Some of the changes include the use of SC-FDMA, a modified pilot pattern and improved scheduling. Typical vehicular environments are characterized by a multipath channel that is temporally varying. Such a channel affects the performance of an underlying SC-FDMA system by introducing Inter-Carrier Interference (ICI). Additionally, the channel characteristics are dynamic, resulting in heterogeneous channel conditions with varying degrees of mobility. Channel estimation and equalization schemes are indispensable in overcoming the adverse ramifications of the channel by precisely parameterizing the channel through computationally feasible means. Here, an optimized channel characterization scheme that involves the Rake-Matching Pursuit (RMP) algorithm for the estimation of the so called doubly selective channels and the Least Squares (LS) scheme in low mobility conditions is suggested. A simple and low complex cognitive framework based on the Index of Dispersion is also proposed to switch between the two schemes based on channel conditions. By virtue of its merits, the proposed channel estimation scheme provides good results in heterogeneous channel conditions and with a complexity that remains relevant for consumer hardware. Finally, an evaluation platform in Matlab® that is LTE standard compliant is made available to the research community. (LTE Evaluation Platform: https://git.nt.uni-saarland.de/HiMo/SimTool_LTE.) It includes the proposed schemes for channel estimation along with the cognitive framework.

The PRRT protocol enables applications with strict performance requirements such as Cyber-Physical Systems, as it provides predictably low, end-to-end delay via cross-layer pacing and timely error correction via Hybrid ARQ (HARQ). However, the implemented HARQ uses computationally complex Maximum Distance Separable (MDS) codes to generate redundancy. In this paper we propose code partitioning for the complexity reduction of MDS codes, thereby enabling their deployment on constrained embedded devices.

In order to create cooperating swarms of Unmanned Autonomous Vehicles (UAVs) that also interact with various other systems and devices, open and free communication systems are mandatory. This paper presents an implementation of such a communication system to incorporate the Crazyflie nano-drone as a UAV platform. The protocol stack leverages the open Predictably Reliable Real-time Transport (PRRT) protocol that adds latency-awareness and -predictability to stacks composed of standard Internet protocols. To enable the drone to receive and reply to control commands via Wi-Fi, it has been extended with a Raspberry Pi that runs two variants of the Crazybridge---a software to connect the control board to the network. To evaluate how practical this solution is for the use in control applications, the communication has been analysed with a focus on the latency properties. Our investigations show that despite using the open protocol stack---and hence opting out of specialised implementations---the resulting latencies are in the same order of magnitude (4 to 9 ms) as the latency of the proprietary link.

To analyze the performance of orthogonal matching pursuit (OMP)-based compressed channel estimation (CCE) with deterministic pilot patterns, we propose a mathematical framework by defining four normalized mean square errors ( $\textrm {NMSE}_{\textrm s}$ ): the total NMSE ( $\textrm {NMSE}_{\textrm T}$ ), the NMSE on dominant channel components ( $\textrm {NMSE}_{\textrm D}$ ), the NMSE caused by “lost errors” ( $\textrm {NMSE}_{\textrm L}$ ), and the NMSE caused by “false alarms” ( $\textrm {NMSE}_{\textrm F}$ ). Then, we derive a formula with a closed form for evaluating the upper bound of $\textrm {NMSE}_{\textrm D}$ in the ideal case ( $\textrm {NMSE}_{\textrm {D,UB}}$ ). Using the proposed analytical framework, the main findings include: 1) the $\textrm {NMSE}_{\textrm {D,UB}}$ is determined by the following four parameters: the deterministic pilot pattern, the maximum Doppler shift, the number of dominant multipath components, and the SNR; 2) the $\textrm {NMSE}_{\textrm {D,UB}}$ can be viewed as an approximation of practical ${\textrm {NMSE}_{\textrm T}}$ in the case that the probability of the successes of OMP exceeds a certain threshold, in which both $\textrm {NMSE}_{\textrm L}$ and $\textrm {NMSE}_{\textrm F}$ are neglectable; and 3) using linear regression models, the practical bit-error-rate performance also can be predicted well based on the proposed $\textrm {NMSE}_{\textrm {D,UB}}$ . We believe that the proposed framework provides a useful tool for adaptively optimizing pilot parameters according to rapidly time-varying channel conditions when using OMP-based CCEs in mobile OFDM systems.