The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown.

Future 4G cellular systems will address the need for capacity increase for the support of diverse services. It is therefore of fundamental importance to design innovative 4G cellular systems able to support the increase in the traffic demand. This Chapter deals with LTE systems and the design of a new reuse scheme, called Soft Frequency Reuse (SFR), that is able to increase the cell capacity that is studied, considering the impact of different scheduling schemes and of different user mobility patterns. A consistent SFR scenario has been implemented in both Ns-3 and OMNeT++ environments. An analytical approach is proposed to evaluate the cell capacity with SFR that has been validated by means of Ns-3 simulations. Finally, OMNeT++ simulations have permitted to highlight the significant impact of the scheduling scheme and user mobility on cell capacity; different mobility patterns have been taken into account.for carrying all traffic types, LTE is expected to provide support for IP-based traffic with end-to-end Quality of Service (QoS) [3].In the LTE architecture, E-UTRAN consists of a single node, i.e., the eNode B (eNB) that interfaces with the User Equipment (UE). The protocol architecture of the LTE air interface can be separated between control and user planes. In the user plane, the application creates data packets that are processed by protocols such as TCP, UDP and IP; instead, in the control plane, the Radio Resource Control (RRC) protocol generates the signalling messages (radio resource management, admission control, enforcement of QoS negotiated, ciphering/deciphering of user and control plane data, compression/decompression of downlink/uplink user plane packet headers, etc.) that are exchanged between eNB and UE. In both cases, the information is processed by the Packet Data Convergence Protocol (PDCP), the Radio Link Control (RLC) protocol, and the Medium Access Control (MAC) protocol, before being passed to the physical layer (PHY) for transmissions. IP packet segmentation is performed at the RLC layer.The aim of this Chapter is to analyse a special frequency reuse scheme proposed for LTE and called Soft Frequency Reuse (SFR). The interest is to study SFR with both analysis and simulations in order to determine the configuration that permits us to maximize cell capacity. This work represents a significant improvement with respect to the study carried out in [3], where we have adopted a less accurate modelling of SFR and where we have not conducted a simulation study to validate the analysis proposed. We expect that the present work can help network planners when designing 4G LTE systems based on SFR.

Future 4G cellular systems will address the need for capacity increase for the support of diverse services. It is therefore of fundamental importance to design innovative 4G cellular systems able to support the increase in the traffic demand. This Chapter deals with LTE systems and the design of a new reuse scheme, called Soft Frequency Reuse (SFR), that is able to increase the cell capacity that is studied, considering the impact of different scheduling schemes and of different user mobility patterns. A consistent SFR scenario has been implemented in both Ns-3 and OMNeT++ environments. An analytical approach is proposed to evaluate the cell capacity with SFR that has been validated by means of Ns-3 simulations. Finally, OMNeT++ simulations have permitted to highlight the significant impact of the scheduling scheme and user mobility on cell capacity; different mobility patterns have been taken into account.for carrying all traffic types, LTE is expected to provide support for IP-based traffic with end-to-end Quality of Service (QoS) [3].In the LTE architecture, E-UTRAN consists of a single node, i.e., the eNode B (eNB) that interfaces with the User Equipment (UE). The protocol architecture of the LTE air interface can be separated between control and user planes. In the user plane, the application creates data packets that are processed by protocols such as TCP, UDP and IP; instead, in the control plane, the Radio Resource Control (RRC) protocol generates the signalling messages (radio resource management, admission control, enforcement of QoS negotiated, ciphering/deciphering of user and control plane data, compression/decompression of downlink/uplink user plane packet headers, etc.) that are exchanged between eNB and UE. In both cases, the information is processed by the Packet Data Convergence Protocol (PDCP), the Radio Link Control (RLC) protocol, and the Medium Access Control (MAC) protocol, before being passed to the physical layer (PHY) for transmissions. IP packet segmentation is performed at the RLC layer.The aim of this Chapter is to analyse a special frequency reuse scheme proposed for LTE and called Soft Frequency Reuse (SFR). The interest is to study SFR with both analysis and simulations in order to determine the configuration that permits us to maximize cell capacity. This work represents a significant improvement with respect to the study carried out in [3], where we have adopted a less accurate modelling of SFR and where we have not conducted a simulation study to validate the analysis proposed. We expect that the present work can help network planners when designing 4G LTE systems based on SFR.

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