Impact of Machine-to-Machine (M2M) Communications on Disaster Management in Future Mobile Networks

Machine-to-Machine (M2M) communications is one of the main new areas of future mobile networks. There are many applications of M2M communications such as intelligent transport systems, smart metering and monitoring, and health care. These applications use a large number of mobile devices which can generate a huge amount of traffic along with different QoS requirements. Due to the mobility, most of the data has to be transmitted over wireless networks. Broadband transmission has to be performed through the mobile communication systems which are widely available and deployed. Long Term Evolution (LTE) and LTE-advanced are the main promising broadband mobile technologies in current and future mobile communications. Current traffic demand for regular mobile applications along with different service requirements is growing exponentially. Mobile technologies such as LTE and LTE-advanced which are based on Orthogonal Frequency Division Multiplexing (OFDM) technology provide promising capabilities to cater per such demands. Adding M2M communications with various Quality of Service (QoS) requirements to the regular mobile services has a significant impact on the overall system and end-to-end performance. The current wireless systems might run out of capacity in the near future and the mobile traffic may not be transmitted efficiently. Enabling a large number of devices to communicate in the mobile system causes many challenges to the mobile operators in distributing the resources effectively among the mobile devices to meet their QoS requirements. Key issues such as prioritization and classification of a large number of devices, coordination of multiple providers to communicate with different devices, and provision of data and system security are challenging over the packetized paradigm. M2M communications generates both small and large sized messages to communicate among the devices. Small sized message communication is costly in terms of spectral efficiency in mobile communications. Some applications such as health care require stringent delay requirements whereas others need data integrity as the basic priority measures. For example, during disaster situations or any other emergency case, a large amount of traffic is generated towards base stations by not only the M2M devices but also the regular mobile users. In case of fire or flood, the building and vehicle alarms would simultaneously trigger resource requests. Currently, avoiding such congestion situations at the mobile networks is practically impossible for several mobile network operators. While using numerous machine-based devices in future mobile networks, similar situations can be expected to arise more frequently in day-to-day normal operations. When car-to-car communication is considered, congestion on a highway with multiple lanes occurs due to accidents. Many cars and mobile users in the region start simultaneous communication producing a huge amount of traffic in the network. Therefore, future mobile communication needs to address these considerations and design mobile networks accordingly. The LTE radio scheduler is one of the key entities which should be designed with great care to effectively manage and coordinate radio resources at the base stations. Designing an effective radio scheduler to optimize the scarce radio resources among the mobile devices, while guaranteeing QoS demands efficiently, is a great challenge in current research. In modern mobile communications, multiple-input and multiple-output (MIMO) antennas and beam forming technologies provide higher capacity over the radio interface. LTE systems use OFDM technology based scheduling both in the uplink and the downlink directions. Uplink scheduling scheme for LTE is the Single Carrier Frequency Division Multiple Access (SC-FDMA) and has much more limitations compared to the downlink from capacity, power and complexity point of view. Therefore within this framework, design challenges of uplink scheduling for future mobile communications are taken as the main consideration. Keywords-component; SC-FDMA; uplink; scheduling; bandwidth; QoS