High Quality Of Service Requirements Research Articles

Developing capacity sharing strategy for vehicular networks with integrated use of licensed and unlicensed spectrum

A widely deployed cellular network, supported by direct connections, can offer a promising solution that supports new services with strict requirements on access availability, reliability, and end-to-end (E2E) latency. The communications between vehicles can be made using different radio interfaces: One for cellular communication (i.e., cellular communication over the cellular network based on uplink (UL)/downlink (DL) connections) and the other for direct communication (i.e., D2D-based direct communications between vehicles which allows vehicular users (V-UEs) to communicate directly with others). Common cellular systems with licensed spectrum backed by direct communication using unlicensed spectrum can ensure high quality of service requirements for new intelligent transportation systems (ITS) services, increase network capacity and reduce overall delays. However, selecting a convenient radio interface and allocating radio resources to users according to the quality of service (QoS) requirements becomes a challenge. In this regard, let’s introduce a new radio resource allocation strategy to determine when it’s appropriate to establish the communication between the vehicles over a cellular network using licensed spectrum resources or D2D-based direct connections over unlicensed spectrum sharing with Wi-Fi. The proposed strategy aims at meeting the quality of service requirements of users, including reducing the possibility of exceeding the maximum delay restrictions and enhancing network capacity utilization in order to avoid service interruption. The proposed solution is evaluated by highlighting different conditions for the considered scenario, and it is demonstrated that the proposed strategy improves network performance in terms of transmitted data rate, packet success rate, latency, and resource usage

X2-Based Signalling Mechanisms for Downlink Uplink Decoupling in Next Generation Communication Systems

Cell selection in cellular networks is an important aspect that impacts the quality of service. The traditional cell selection mechanism is based on downlink received power. Despite the dense deployment of macrocells, mobile network operators are still confronting the daunting challenge of providing capacity and coverage. Deployment of a large number of small cells has emerged as a promising solution towards addressing this problem. However, this success expands the heterogeneous cellular networks where there is a significant disparity in the transmit power of the different base station types. Downlink and Uplink Decoupling (DUDe) can improve efficiency by associating the downlink cell based on the downlink received power and the uplink based on the pathloss. While the higher layer signalling has not been proposed in detail for the DUDe mechanism yet, we aim to propose a solution for the problem. This work addresses four different signalling mechanisms to realise decoupled up/downlinks connections in the radio access network for the next-generation communication systems with handling mobility. Our proposed signalling mechanisms cover uplink decoupling, downlink coupling, downlink decoupling, and uplink coupling scenarios. We analyse the proposed signalling mechanisms using ns3 simulation and present the impact of applying the DUDe mechanism, which mainly shows improvements for the uplink. For the selected mobility scenario, delay and lost packets are reduced by 30% and 26%, respectively. Delay and lost packets are reduced by 36% and 27% for the fix location scenario, respectively. The improvements imply that it reaches particular demand considering next-generation communication systems, with a massive number of smart devices demanding high quality of service requirements.

Power Minimization Using Rate Splitting With Statistical CSI in Cloud-Radio Access Networks

Minimizing the power consumption in mobile communication networks while ensuring a minimum quality of service (QoS) for applications is essential in light of the unprecedented expected increase in the number of connected devices and the associated data traffic beyond the fifth generation of wireless networks (B5G). This paper considers a cloud-radio access network (C-RAN) model where a central processor (CP) is connected to the base stations (BSs) via limited capacity fronthaul links. In the context of our C-RAN setting, we consider the practical case where the CP has only statistical knowledge of channel state information (CSI). While conventional wireless systems adopt the treating interference as noise (TIN) strategy to deal with the interference in the network, this paper instead considers that the CP applies the rate splitting (RS) strategy by dividing each user’s message into two parts: a private part to be decoded by the intended user only and a common part to be decoded by a subset of users, for the sole reason of interference mitigation in the network. To best account for the channel estimation errors, this paper addresses the problem of transmit power minimization under minimum QoS constraints on the achievable ergodic rate per user, so as to determine the beamforming vectors of the private and common messages as well as the rate allocated to all the users. The considered problem is of stochastic, complex, and non-convex nature. This paper addresses the problem intricacies through an iterative approach that leverages both the sample average approximation (SAA) technique and the weighted minimum mean squared error (WMMSE) algorithm to obtain a stationary point of the optimization problem in the asymptotic regime. The numerical results demonstrate the gain achieved with the RS strategy as compared to TIN, especially under high QoS requirements.

User selection and dynamic power allocation in the SWIPT-NOMA relay system

Non-orthogonal multiple access (NOMA) technology provides an effective solution to massive access with a high data rate demand in new-generation mobile networks. The paper combinations with NOMA and simultaneous wireless information and power transfer (SWIPT) relay to maximize the sum rate in the downlink system. To that end, it is critical how to select effectively users access system and power allocation for the access user. This paper proposes a user selection and dynamic power allocation (USDPA) scheme in the NOMA-SWIPT relay system based on neural network because traditional optimization methods have difficulty solving nonlinear and non-convex problems. We establish a user selection network utilizing a deep neural network (DNN) and propose a power allocation network using deep reinforcement learning. The simulation results show that the proposed scheme achieves better performance than other related schemes, especially for high quality of service requirements.

Energy-efficient cross-layer resource allocation scheme for OFDMA systems

Recently, the interest of the telecommunication operators and Internet service providers (ISPs) in energy efficiency (EE) for wireless networks has remarkably increased. The boost in energy prices, the continuous increase of the user numbers, the pervasion of wideband access, and the diffusion of offered services have motivated this interest. The challenge is to minimize the transmitted energy without compromising the quality of service (QoS) and the network performance. In this paper, a new efficient Orthogonal Frequency Division Multiple Access (OFDMA) resource allocation for Long Term Evolution (LTE)-advanced systems based on cross-layer optimization between Physical (PHY) and Medium Access Control (MAC) layers is proposed. A new solution based on Rate Adaptive (RA) principle is presented to achieve better EE resource allocation. The purpose behind the new model is to increase the capacity of the system as much as possible while trying to decrease the total transmit power. Hence, the EE which is equal to the capacity to total transmit power ratio is increased. As reducing the transmit power for the transmission of a given capacity reduces the power consumption, the greenhouse gas (GHG) emission will be then reduced. On the other hand, the service differentiation is highly considered to provide high QoS support. The users are differentiated according to different service classes and different data rates. The proposed cross-layer-based solution has then to allocate the system resources in an optimal way while satisfying the users having high QoS requirements.

Maximizing Sleeping Capacity Based on QoS Provision for Information-Centric Internet of Things

Unlike the IP-address-centric network, heterogeneous devices in the information-centric Internet of Things (IC-IoT) have heterogeneous quality of service (QoS) requirements. Employing sleeping technology in IC-IoT while satisfying the heterogeneous QoS requirements for IoT devices is challenging. In this paper, considering the IoT devices’ heterogeneous QoS requirements, we investigate a sleeping capacity maximizing problem in IC-IoT. First, a content-based heterogeneous network architecture is proposed to empower IC-IoT and decouple the heterogeneous content transmission functions. Specifically, macro base stations (MBSs) are used to guarantee the control coverage and transmit the low QoS requirement services, whereas small base stations (SBSs) are utilized to transmit the high QoS requirement services. The QoS requirement levels are differentiated by the outage constraints which are related to the achievable data rate. Then, an optimization problem is formulated to maximize the sleeping probability and available bandwidth while the outage probability and achievable data rate constraints are guaranteed. In the formulated optimization problem, sleeping probability plays the roles of both an optimization variable and an optimization objective, which makes the optimization problem challenging to be solved. In order to decouple sleeping probability from the optimization values, we first analyze the parameters related to the sleeping probability and the available bandwidth and then propose a bisection-based nonlinear programming algorithm. This algorithm divides the original problem into two subproblems. One is related to the bandwidth reallocation. The other one involves obtaining the optimal sleeping probability. Last but not least, analytical results are concluded due to the simulation results, which indicate the following facts: 1) optimal sleeping probability is linear to the available bandwidth, and inversely proportional to the devices’ density, and; 2) sleeping probability is more sensitive to the changes of channel quality than those of QoS provision.

Transmission-Rate-Adaption Assisted Energy-efficient Resource Allocation with QoS Support in WBANs

With the advances in wearable sensors and wireless technologies, wireless body area network (WBAN) has become a promising network to provide health applications, such as ubiquitous e-Health services and real-time health monitoring. In these WBANs, quality of service (QoS) requirements, including packet loss rate, throughput, and delay, need to be guaranteed for providing reliable and real-time data transmission even under highly dynamic environment due to human mobility and postures. Meanwhile, energy efficiency is another key factor to consider for increasing the network lifetime in such a resource-constrained network. In this paper, a transmission-rate-adaption assisted and energy-efficient resource allocation scheme is proposed in which both constraints of QoS metrics and the characteristics of dynamic links are considered. Specifically, a QoS optimization problem is formulated to optimize the transmission power and time slots for each sensor, which minimizes energy consumption subjected to the QoS constraints. Due to the dynamic link characteristics, the link quality may become poor, and then the QoS requirements of normal packets and emergency packets cannot be satisfied. Besides, the emergency packets should receive more attentions with a high priority and high QoS requirements. To guarantee the QoS requirements when the link is very poor, a transmission rate adaption policy is proposed to carefully adjust the transmission rate at each sensor to assist the QoS optimization problem, and a priority-based retransmission strategy is designed to apply the retransmission strategy to further improve the performances of the emergency packets with a high priority. Numerical results demonstrate the effectiveness of the QoS optimization problem, the proposed transmission rate adaption policy, and the priority-based retransmission strategy.

Large Scale Cloudlets Deployment for Efficient Mobile Cloud Computing

Interest in using Mobile Cloud Computing (MCC) for compute intensive mobile devices jobs such as multimedia applications has been growing. In fact, many new research efforts were invested to maximize the mobile intensive jobs offloading to the cloud within the cloud system coverage area. However, a large scale MCC deployment challenges and limitations are not considered. In this paper, a large scale Cloudlet-based MCC system deployment is introduced, aiming at reducing the power consumption and the network delay of multimedia applications while using MCC. The proposed deployment offers a large coverage area that can be used by mobile devices while they are moving from one location to another to reduce broadband communication needs. Practical experimental results and simulated results using show that using the proposed model reduces the power consumption of the mobile devices as well as reducing the communication latency when the mobile device requests a job to be performed remotely while satisfying the high quality of service requirements of mobile users.

An Reliable Transmission Scheme Based on Opportunistic Cooperation for Wireless Body Sensor Networks

Reliable data transmission of wireless body sensor networks with high quality of service requirement has been producing a new challenge. Considering the randomness and network dynamic condition, as well as restriction of system resources. In our paper, the network state information arrays of distance and channel quality were researched at first. Then the complete binay tree of network state and heap initialization were implemented. The optimal relay nodes were selected by heap sort approach. The data transmission scheme of reliable opportunistic cooperation was presented finally. The results of mathematics and simulation make clear that the proposed scheme have higher priority than the traditional transmission schemes in the matter of reliability, real time performance, energy efficiency and lifetime.

Scalable Cloudlet-based Mobile Computing Model

Mobile Cloud Computing (MCC) has been introduced as a feasible solution to the inherited limitations of mobile computing. These limitations include battery lifetime, processing power and storage capacity. By using MCC, the processing and the storage of intensive mobile device jobs will take place in the cloud system and the results will be returned to the mobile device. This reduces the required power and time for completing such intensive jobs. However, connecting mobile devices with the cloud, suffers from the high network latency and the huge transmission power consumption especially when using 3G/LTE connections. On the other hand, multimedia applications are the most common applications in today's mobile devices; such applications require high computing resources. In this paper, a Cloudlet-based MCC system is introduced, aiming at reducing the power consumption and the network delay of multimedia applications while using MCC. The MCC concepts with the proposed Cloudlet framework are integrated and a new scalable framework for the MCC model is proposed. Our practical experimental results using multimedia applications show that using the proposed model reduces the power consumption of the mobile devices as well as reducing the communication latency when the mobile device requests a job to be performed remotely while satisfying the high quality of service requirements.

High level QoS-driven model for Grid applications in a simulated environment

This paper presents a model for high-level Quality of Service (QoS) maintenance within business-context domains and associated simulation results achieved via an expansion of the GridSim toolkit. Grid Computing traditionally has been linked with scientific environments, where heterogeneous resources were networked and employed for carrying out compute-intensive and data-intensive scientific experiments or applications that may have not been possible before. The natural progression is that business-oriented applications will build on this success and utilise the large number of heterogeneous Grid resources, potentially available. The success of introducing these applications into the mainstream is directly related to whether Grid Resource Providers can deliver a suitable level of QoS to the Grid Resource Consumer (GRC) and the ability of the GRC to request high level QoS such as the numbers of CPUs required or the RAM required, on demand. Moreover, we present dynamically calculated metrics for measuring QoS such as reliability, using up-to-date information on resources. We introduce a novel model, Business Grid Quality of Service (BGQoS), for a new generation of commercial and business-oriented Grid applications which may wish to make use of Grid environments. BGQoS allows GRCs to specify varying types of high level QoS requirements which are delivered via querying up-to-date resource information, matchmaking and monitoring operations. In addition, testing is required and this has posed a problem where testing on physical Grid test-beds is either impractical or not viable economically. Simulation is therefore important.

Linear Diversity Combining on Nakagami-0.5 Fading Channels

The Nakagami-0.5 distribution is an important special case of the Nakagami distribution as it represents a worst case fading scenario. This scenario is of particular significance for wireless applications with high quality of service requirements. The bit error probability (BEP) performances of three basic diversity combining schemes in Nakagami-0.5 fading are considered. It is shown that the error rate performances of dual branch equal gain and selection combining (SC) diversity are identical regardless of modulation format. It is also shown that L-branch maximal ratio combining diversity in Nakagami-0.5 fading has the same BEP performance as single branch reception in Nakagami-L/2 fading with L times the transmission power of each branch. A useful upper bound for the BEP of L-branch SC diversity in Nakagami-0.5 fading is also derived. The performance degradation for the worst case Nakagami-0.5 fading relative to Rayleigh fading can be as much as 24.6 dB for a dual-diversity receiver at target BEP of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> . The additional resources required to restore a specified performance level, as increased channel signal-to-noise ratio and as number of additional diversity branches, are quantified. It is concluded that worst case Nakagami channels can result in dramatically poorer performance than Rayleigh channels, making proper system design and evaluation essential to achieve a required transmission quality.