The parameters of physical layer radio frame for 5th generation (5G) mobile cellular systems are expected to be flexibly configured to cope with diverse requirements of different scenarios and services. This paper presents a frame structure and design, which is specifically targeting Internet of Things (IoT) provision in 5G wireless communication systems. We design a suitable radio numerology to support the typical characteristics, that is, massive connection density and small and bursty packet transmissions with the constraint of low-cost and low complexity operation of IoT devices. We also elaborate on the design of parameters for random access channel enabling massive connection requests by IoT devices to support the required connection density. The proposed design is validated by link level simulation results to show that the proposed numerology can cope with transceiver imperfections and channel impairments. Furthermore, the results are also presented to show the impact of different values of guard band on system performance using different subcarrier spacing sizes for data and random access channels, which show the effectiveness of the selected waveform and guard bandwidth. Finally, we present system-level simulation results that validate the proposed design under realistic cell deployments and inter-cell interference conditions.INDEX TERMS 5G, frame structure, Internet of Things, random access channel.

Hot spots in a wireless sensor network emerge as locations under heavy traffic load. Nodes in such areas quickly deplete energy resources, leading to disruption in network services. This problem is common for data collection scenarios in which Cluster Heads (CH) have a heavy burden of gathering and relaying information. The relay load on CHs especially intensifies as the distance to the sink decreases. To balance the traffic load and the energy consumption in the network, the CH role should be rotated among all nodes and the cluster sizes should be carefully determined at different parts of the network. This paper proposes a distributed clustering algorithm, Energy-efficient Clustering (EC), that determines suitable cluster sizes depending on the hop distance to the data sink, while achieving approximate equalization of node lifetimes and reduced energy consumption levels. We additionally propose a simple energy-efficient multihop data collection protocol to evaluate the effectiveness of EC and calculate the end-to-end energy consumption of this protocol; yet EC is suitable for any data collection protocol that focuses on energy conservation. Performance results demonstrate that EC extends network lifetime and achieves energy equalization more effectively than two wellknown clustering algorithms, HEED and UCR.

In this paper, we present a novel packet delivery mechanism called Multi-path and Multi-Speed Routing Protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, reliability and timeliness. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. All these for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates the local decision inaccuracy as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements.

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Abstract-The recent forecast of billions of devices, all connected to the Internet and generating low-rate monitoring, measurement, or automation data that many end-users/applications frequently request, signifies the need for applying in-network caching techniques to Internet-of-Things (IoT) traffic. Although time delay is not critically important for small-sized IoT content, the expected total traffic load on the Internet from a large number of devices is significant. However, the main challenge as opposed to the typically cached content at content routers, e.g. multimedia files, is that IoT data are transient and therefore require different caching policies. This paper studies in-network caching of IoT data at content routers in the Internet. An IoT data item is uniquely defined not only by its time and location tags, but also a time-range value set by end-users/applications. We provide a model for the trade-off between multihop communication costs and the freshness of a transient data item. Results show that the model can successfully capture the effect of data transiency and can accurately represent the expected gains of a caching system: considerable savings in terms of reduction of network load, especially for highly requested data items.