2D Proactive Uplink Resource Allocation Algorithm for Event Based MTC Applications

We propose a two dimension (2D) proactive uplink resource allocation (2D-PURA) algorithm that aims to reduce the delay/latency in event-based machine-type communications (MTC) applications. Specifically, when an event of interest occurs at a device, it tends to spread to the neighboring devices. Consequently, when a device has data to send to the base station (BS), its neighbors later are highly likely to transmit. Thus, we propose to cluster devices in the neighborhood around the event, also referred to as the disturbance region, into rings based on the distance from the original event. To reduce the uplink latency, we then proactively allocate resources for these rings. To evaluate the proposed algorithm, we analytically derive the mean uplink delay, the proportion of resource conservation due to successful allocations, and the proportion of uplink resource wastage due to unsuccessful allocations for 2D-PURA algorithm. Numerical results demonstrate that the proposed method can save over 16.5 and 27 percent of mean uplink delay, compared with the 1D algorithm and the standard method, respectively.Comment: 6 pages, 6 figures, Published in 2018 IEEE Wireless Communications and Networking Conference (WCNC

Spatial Wireless Channel Prediction under Location Uncertainty

Spatial wireless channel prediction is important for future wireless networks, and in particular for proactive resource allocation at different layers of the protocol stack. Various sources of uncertainty must be accounted for during modeling and to provide robust predictions. We investigate two channel prediction frameworks, classical Gaussian processes (cGP) and uncertain Gaussian processes (uGP), and analyze the impact of location uncertainty during learning/training and prediction/testing, for scenarios where measurements uncertainty are dominated by large-scale fading. We observe that cGP generally fails both in terms of learning the channel parameters and in predicting the channel in the presence of location uncertainties.\textcolor{blue}{{} }In contrast, uGP explicitly considers the location uncertainty. Using simulated data, we show that uGP is able to learn and predict the wireless channel

Resource Allocation and Mobility Prediction Algorithms for Multimedia Wireless Cellular Networks

Among the issues the telecommunication industry is the demand for multimedia applications with Quality of Service (QoS) in wireless/mobile networks. In the face of this increasingly complex traffic mix, where each service imposes different requirements, QoS provisioning and guarantee for multimedia services have become increasingly important. This is partially due to the users' requirements and poses a difficult challenge for network service providers. The tasks are more challenging than those in the wired networks due to the shortage of resources and the mobility present in wireless networks. The mobility factor causes severe fluctuations of resource usage. In this research, the QoS provisioning and resource utilization for multimedia services in wireless/mobile networks aspects are addressed. The first proposed scheme is called Adaptive Multi-Class Services Controller scheme (AMCSC). This scheme harnesses the combinations of Call Admission Control (CAC), an Adaptive Bandwidth Allocation (ABA) algorithm with micro-Acceptable Bandwidth Level (micro-ABL) and the Connection Management Table (CMT). The specific objective in designing the AMCSC Scheme is to reduce the New Connection Blocking Probability (NCBP) and the Handoff Connection Dropping Probability (HCDP) by managing resource allocation to address. The insufficient resource problem is experienced by the MTs. This scheme supports multiple classes of non-adaptive and adaptive multimedia services with diverse QoS requirements. The second proposed scheme is a bandwidth reservation scheme based on Mobility Prediction Scheme (MPS). Two proposed MPSs are deployed to predict the mobility movement of mobiles. The first MPS obtains the user mobility information by Received Signal Strength (RSS) which also includes the direction of the MT. This is enhanced based also on the position of the MT within a sector and zones of the cell. The second MPS obtains the user mobility information using the road map information of the cell and the integrated RSS and Global Position System (GPS) measurements. The simulation results show that the proposed scheme enhances the estimation of the target cell. This shown by the reduction of the signalling traffic in wireless cellular networks, reduction of the number of terminated ongoing calls of non-real time traffic and reduction of the number of cancelled reservation due to false reservation. The third proposed framework is an integration of the AMCSC scheme and the bandwidth reservation done based on the MPS. This integration is used to achieve the ideal balance between the users' QoS guarantee of multiple classes of wireless multimedia and maximizing the bandwidth utilization. The performance result of the proposed framework has proven to improve the achieved performance metrics. The performances analysis in this research is discrete simulation. The proposed schemes have proven to enhance the performance in terms of NCBP and HCDP for each type of traffic, management the resource for multiple traffics with diverse requirement, bandwidth utilization and predicting the target cell in the right time and place