Safdar Nawaz Khan Marwat

Influence of future M2M communication on the LTE system

Machine-to-Machine (M2M) communications is one of the latest research areas. This technology aims to enable machines to communicate with each other, mainly, without human intervention. M2M traffic is envisaged to play a big role within the coming years; lots of research projects and standardization bodies around the world have already started paying attention to the rising M2M communication. Current cellular mobile networks, such as LTE, are designed and optimized for traffic characteristics of human-based communication, but M2M traffic is different: Packet sizes are small, but transmitted periodically by numerous endpoints. In this paper, we focus on how LTE cellular networks will handle the massive deployment of M2M devices. In order to do so, the authors specified an M2M traffic model that represent a possible logistical scenario in the future. Besides M2M traffic, also regular LTE traffic is present in the network and the influence of the increasing M2M traffic is investigated. The results of the simulations show that M2M traffic will influence regular, human-based traffic. In particular the file upload time for regular LTE traffic experiences a considerable increase.

Performance evaluation of bandwidth and qos aware LTE uplink scheduler

A Long Term Evolution (LTE) eNodeB Medium Access Control (MAC) uplink scheduler is proposed in this paper for Single Carrier Frequency Division Multiple Access (SC-FDMA) as the uplink transmission scheme. Uplink scheduling algorithms available in literature commonly do not consider all the essential features of the LTE uplink. The proposed scheduler is shown to provide efficient allocation of radio resources to User Equipments (UEs) according to Quality of Service (QoS) of various traffic classes and the instantaneous channel conditions. The scheduler functionality is divided into Time Domain Packet Scheduling (TDPS) and Frequency Domain Packet Scheduling (FDPS). The proposed scheduler also supports multi-bearer UEs. The performance of the proposed scheduler is compared with common TDPS schedulers like Blind Equal Throughput (BET), Maximum Throughput (MT) and Proportional Fair (PF). The results show that the proposed scheduler guarantees provision of QoS to UEs and achieves an acceptable performance in terms of throughput.

Design and performance analysis of bandwidth and QoS aware LTE uplink scheduler in heterogeneous traffic environment

Long Term Evolution (LTE) uses Single Carrier Frequency Division Multiple Access (SC-FDMA) as the uplink transmission scheme. The Quality of Service (QoS) provision is one of the primary objectives of the wireless network operators. In this paper, the end-to-end QoS performance of Bandwidth and QoS Aware (BQA) scheduler for LTE uplink is evaluated in heterogeneous traffic environment. The BQA scheduler is designed to provide efficient allocation of radio resources to users according to the QoS requirements of various traffic classes and the instantaneous channel conditions. The user QoS provision is ensured by using dynamic QoS weights. Additionally, the delay sensitive traffic is facilitated by employing delay thresholds. The BQA scheduler algorithm supports multi-bearer users. The end-to-end QoS performance of the scheduler is analyzed in several simulation scenarios. The results show that the proposed scheduler guarantees provision of QoS to users.

Addressing the Challenges of E-Healthcare in Future Mobile Networks

Machine-to-Machine (M2M) communication is expected to play a major role within the coming years towards the development of e-healthcare applications. The design of cellular networks, such as Long Term Evolution (LTE), is optimized to serve the data traffic of human-based communication with broadband requirements. E-healthcare traffic has different characteristics such as small packet sizes, narrowband requirements and huge number of devices. The focus of this work is to investigate the impact of e-healthcare traffic on LTE cellular networks. We develop a possible future scenario of electrocardiography (ECG) devices performing remote monitoring of patients with mobility support in our LTE simulation model. Regular LTE traffic is also deployed in the network and the influence of the varying ECG traffic is examined. The simulation results indicate that the e-healthcare related data traffic has a drastic influence on regular LTE traffic.

Machine-to-Machine Sensor Data Multiplexing Using LTE-Advanced Relay Node for Logistics

Machine-to-Machine (M2M) communication is one of the emerging fields today and expected to play a major role in interconnecting various types of devices for different applications, such as logistics. Mobile communication standards, such as Long Term Evolution Advanced (LTE-A), have high data rate capability and are designed to provide broadband services to the human-based communication. M2M devices in logistics usually transmit small amount of data depending on the application scenario. LTE-A can be optimized to provide better performance of M2M devices in logistics. This paper studies a Relay Node (RN) based solution in LTE-A to integrate M2M devices in mobile cellular networks. Different M2M scenarios are developed for logistics along with normal LTE-A users in our LTE-A simulation model implemented in OPNET Modeler. The simulation results show that the data traffic performance of LTE-A network improves significantly if RN is utilized for aggregation and multiplexing of M2M data traffic in logistics.

Impact of Machine-to-Machine Traffic on LTE Data Traffic Performance

Machine-to-machine (M2M) communication is an emerging paradigm in which trillions of intelligent devices are expected to communicate without or with small human intervention. The increasing M2M devices have severe impact on long-term evolution (LTE) data traffics. Moreover, the behavior of M2M traffic also differs from traditional mobile traffic. In future, logistics and transportations are considered to be the main M2M application areas. These applications disparately demand more efficient M2M traffic modeling to reduce end-to-end (E2E) delay between various interconnected machines. This paper investigates several traffic models and highlights the impact of M2M traffic in logistics and transportation on LTE data traffic. We evaluate the overall LTE network performance in terms of E2E delays for file transfer, voice, and video users.

Novel Schemes for Component Carrier Selection and Radio Resource Allocation in LTE-Advanced Uplink

The LTE (Long Term Evolution) provides mobile users high throughput and low latency. In order to meet the requirements of future mobile data traffic, the 3rd Generation Partnership Project (3GPP) has introduced advanced features to the LTE system, including Carrier Aggregation (CA), enhanced MIMO (Multiple Input Multiple Output), and coordinated multipoint (CoMP). The enhanced system is called LTE-Advanced (LTE-A) system. This paper investigates Component Carrier Selection (CCS) and radio resource scheduling for uplink in LTE-A. In this work, a CCS algorithm depending on the pathloss and the slow fading of the radio signals is developed. Based on the channel conditions and the Quality of Service (QoS) requirements of the users, a Channel and QoS Aware (CQA) uplink scheduler is also designed, which is time and frequency domain decoupled. The simulation results demonstrate that the proposed schemes provide a good QoS and throughput performance as compared to other reference schemes.

Interdisciplinary Perspective on Knowledge Management in Logistics

Logistics services are increasingly complex and knowledge intensive in today’s dynamic competitive environment. Knowledge assets have become critical for logistics enterprises to attain performance goals. Thus, it is crucial to implement the knowledge management (KM) for developing sustainable competitive advantages. KM research and implementation have grown rapidly in recent years. So far, various disciplines have studied KM from their own perspectives. However, there is only limited systematic effort to study the interfaces and the collaboration of KM from an interdisciplinary perspective. The goal of this paper is to identify the interface of KM in logistics from the perspectives of these disciplines: business studies and economics, production engineering, computer and information technology. For each discipline, the difference of the concepts as well as three key aspects of KM namely knowledge representation, acquisition and application will be described by means of literature review. Furthermore, this paper introduces a four stage model, which applies the collaborative KM in logistics and presents the connection from an interdisciplinary perspective. The connection shows that different disciplines can cooperate together in KM process, from objective setting, planning and execution to feedback phase. This paper will stimulate more discussions of KM from multidisciplinary viewpoints and implicates the importance of collaboration in KM practice. The model gives a guideline to logistic enterprises to apply their KM, for different functions, departments, and business processes, as a collaborative project with perspectives of different disciplines.

Analysis of Radio Resource Allocation in LTE Uplink

Long term evolution (LTE) uses orthogonal frequency division multiple access (OFDMA) and single carrier frequency division multiple access (SC-FDMA) as the downlink and uplink transmission schemes respectively. The Quality of Service (QoS) provision to users is one of the key objectives of the wireless network operators. This paper analyses an uplink LTE radio scheduler, called bandwidth and QoS aware (BQA) scheduler and evaluates its QoS performance. The BQA uplink scheduler is designed to provide efficient and fair allocation of the radio resources to users according to: the QoS of various traffic classes and the instantaneous channel conditions. The scheduler functionality is divided into time domain packet scheduling (TDPS) and frequency domain packet scheduling (FDPS). In this paper, an innovative feature, that is user QoS provisioning with dynamic QoS weights, is employed for the BQA scheduler along with multi-bearer users support. The QoS performance of the BQA scheduler is analyzed in several simulation scenarios using heterogeneous traffic environment. The results show that the BQA scheduler guarantees provision of QoS to users.

Poster Abstract: Performance Evaluation of Machine-to-Machine Communication on Future Mobile Networks in Disaster Scenarios

Long Term Evolution (LTE) is the recent standard of wireless communication developed by the Third Generation Partnership Project (3GPP). As the future mobile network, it is currently being rolled out to numerous areas world-wide. Besides other objectives such as enhancing the spectral efficiency and reducing latency for broadband services, LTE has been designed as a pure packet switched system. Hence, it targets the data volume requirements of cellular mobile users by increasing the peak-user data throughput to up to 100 Mbit/s [1]. However, legacy circuit switched services are no longer supported by this technology. Contrary to the existing, wide-spread GSM network, this implies that the support of voice calls and Short Message Service (SMS) have to be realized by voice and SMS via the IP Multimedia Subsystem (IMS). In other words, voice calls are no longer separated from pure data traffic and hence influence each other.