In the context of 5'th Generation (5G) New Radio (NR), new transmission procedures are currently studied for supporting the challenging requirements of Ultra-Reliable Low-Latency Communication (URLLC) use cases. In particular, grant free (GF) transmissions have the potential of reducing the latency with respect to traditional grant-based (GB) approaches as adopted in Long Term Evolution (LTE) radio standard. However, in case a shared channel is assigned to multiple users for GF transmissions, the occurrence of collisions may jeopardize the GF potential. In this paper, we perform a system analysis in a large urban macro network of several transmission procedures for uplink GF transmission presented in recent literature. Specifically, we study K-Repetitions and Proactive schemes along with the conventional HARQ scheme referred to as Reactive. We evaluated their performance against the baseline GB transmission as a function of the load using extensive and detailed system level simulations. Our findings show that GF procedures are capable of providing significant lower latency than GB at the reliability level of 1 − 10 −5 , even at considerable network loads. In particular, the GF Reactive scheme is shown to achieve the latency target while supporting at least 400 packets per second per cell.

Floating car data (FCD) has been used to collect traffic state information from a set of individual vehicles. Vehicles are equipped with On Board Units (OBU) that collect different measurements and the vehicle position and transmit the data to a remote control center. In current implementations of FCD systems, vehicle fleets use cellular connections for data transmission. In this paper we consider an IEEE 802.11p-based Road Side Unit (RSU) infrastructure for FCD collection. Installing RSUs in order to acquire perfect coverage may prove to be a costly solution, while gaps between the coverage areas will force data buffering at OBUs. This might be a viable solution for delay-tolerant, but not for safety-critical applications that require high data delivery ratio. The goal of this paper is to study the trade-offs between the size of the gaps between RSUs and other system parameters such as data delivery ratio, data collection update interval and size of measured data. We have proposed some heuristics that can be used while deciding on the distance between neighboring RSUs.

In this paper we propose a relay selection scheme which uses collected location information together with a path loss model for relay selection, and analyze the performance impact of mobility and different error causes on this scheme. Performance is evaluated in terms of bit error rate by simulations. The SNR measurement based relay selection scheme proposed in [1] is unsuitable for use with fast moving users in e.g. vehicular scenarios due to a large signaling overhead. The proposed location based scheme is shown to work well with fast moving users due to a lower signaling overhead. The required location accuracy was found to be comparable to the accuracy of standard GPS. As the scheme was found to be highly sensitive to NLOS situations with unknown attenuation, knowledge of obstacle locations obtained either by sensing online or from a map of obstacles, was identified as a prerequisite in these situations. As the location-based scheme relies on a path loss model to estimate link qualities and select relays, the sensitivity with respect to inaccurate estimates of the unknown path loss model parameters is investigated. The parameter ranges that result in useful performance were found to be wide enough to allow them to be estimated in practical systems.

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For centralized selection of communication relays, the necessary decision information needs to be collected from the mobile nodes by the access point (centralized decision point). In mobile scenarios, the required information collection and forwarding delays will affect the reliability of the collected information and hence will influence the performance of the relay selection method. This paper analyzes this influence in the decision process for the example of a mobile location-based relay selection approach using a continuous time Markov chain model. The model is used to obtain optimal relay policies via a heuristically reduced brute-force search. Numerical results show how forwarding delays affect these optimal policies.