2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT)
The typical traffic models proposed in literature can be considered as heuristic models since the... more The typical traffic models proposed in literature can be considered as heuristic models since they only reflect the stochastic characteristic of the generated traffic. In this paper, we propose a model for M2M communications that generates the traffic. Therefore, the proposed model is able to capture a wider picture than the state-of-the-art traffic models. The proposed model illustrates the behaviour of M2M uplink communication in a network with multiple-access limited information capacity shared channels. In this paper, we analyzed the number of transmitted packets using the traffic model extracted from our proposed communication model and compared it with the state-ofthe-art traffic models using simulations. The simulation results show that the proposed model has a significantly higher accuracy in estimating the number of transmitted packets compared with the liteature model.
This study focuses on improving the sustainability of electrical supply in the healthcare system ... more This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simu...
The race for the 6th generation of wireless networks (6G) has begun. Researchers around the world... more The race for the 6th generation of wireless networks (6G) has begun. Researchers around the world have started to explore the best solutions for the challenges that the previous generations have experienced. To provide the readers with a clear map of the current developments, several review papers shared their vision and critically evaluated the state of the art. However, most of the work is based on general observations and the big picture vision, and lack the practical implementation challenges of the Internet of Things (IoT) use cases. This paper takes a novel approach in the review, as we present a sample of IoT use cases that are representative of a wide variety of its implementations. The chosen use cases are from the most research-active sectors that can benefit from 6G and its enabling technologies. These sectors are healthcare, smart grid, transport, and Industry 4.0. Additionally, we identified some of the practical challenges and the lessons learned in the implementation ...
— In order to enhance the Long Term Evolution (LTE) network performance, the Third Generation Par... more — In order to enhance the Long Term Evolution (LTE) network performance, the Third Generation Partnership Project (3GPP) introduced Coverage and Capacity Optimisation (CCO) in the context of Self Organising Network (SON). Antenna parameters (i.e. azimuth, electrical tilt etc.) play a key role in CCO and have a significant impact on the users' Quality of Service (QoS). In this paper, a novel metric, to evaluate the cells performance, that consider several performance indicators, is introduced. Furthermore, a distributed CCO algorithm is proposed which has three distinct phases. The first phase is to determine the target cell, the second phase adjust the antenna parameters for the target and neighbouring cells and in the last phase the optimum antenna parameters for the target and neighbouring cells is determined. The simulation results show significant improvement in the overall network performance with the proposed CCO algorithm. In particular, the target cell average performance can be improved by 16.75%.
— Traditional wireless and mobile network focuses on higher throughout, coverage and larger capac... more — Traditional wireless and mobile network focuses on higher throughout, coverage and larger capacity. In future, energy efficiency is of vital importance for wireless networks due to a large number of connected and battery constrained mobile devices. In Long Term Evolution Advanced (LTE-Advanced), Carrier Aggregation (CA) is proposed to increase the transmission bandwidth and hence data rate. This paper studies the effect of CA on the total power transmitted by the LTE-Advanced eNodeB based on the Orthogonal Frequency Division Multiple Access (OFDMA) downlink while taking the users Quality of Service (QoS) constraints into consideration. The numerical analysis and results show that by using CA a reduction in total power consumption can be achieved. Keywords— Energy-efficient mobile network; LTE-A; OFDMA downlink; Carrier Aggregation ; QoS.
— The 3 rd Generation Partnership Project (3GPP) introduced Long Term Evolution (LTE) in release ... more — The 3 rd Generation Partnership Project (3GPP) introduced Long Term Evolution (LTE) in release 8, and afterwards it was updated significantly in later releases (referred to as LTE-Advanced). LTE and LTE-Advanced (LTE-A) aim to achieve higher spectral efficiency, higher data rates, robustness and flexibility. Intelligent channel-aware radio resource scheduling is one of the key features of LTE-A. A number of schedulers proposed in the literature rely on the feedback sent from the Users Equipment (UE) without considering the presence of feedback delay. In this paper, we analyse the effect of the uplink delay on the cell performance of existing schedulers, in terms of throughput and the users' fairness. We then propose an adaptive hybrid scheduler to overcome the effect of the uplink delay on the scheduler performance. The simulation results show that our proposed scheduling algorithm outperforms the existing schedulers in the presence of uplink feedback delay.
—Machine Type Communication (MTC) is gaining an enormous interest among communication industry an... more —Machine Type Communication (MTC) is gaining an enormous interest among communication industry and academia all around the world. The variety of services offered by MTC is expected to significantly increase the number of MTC Devices (MTCD) on wireless networks. The huge number of MTCD poses several challenges to cellular network operators such as efficient radio resource management, energy efficiency (EE) etc. Two main radio resource management techniques to support MTC over 4G Long Term Evolution (LTE) were proposed in the literature: Group Based Scheduling (GBS) and Time Granularity Scheduling (TGS). In this paper, we compare the EE of GBS and TGS by formulating a general expression for the downlink transmit power by eNodeB. The numerical results show that the GBS is more energy efficient that TGS under given quality of service constraints. MAC and physical layer functionalities, such as Adaptive Modulation and Coding (AMC), Channel Quality Indicator (CQI) reporting and resource sharing. Later, 3GPP introduced LTE-Advanced (LTE-A) in release 10, which provides additional functionalities such as extended MIMO, heterogeneous networks and Carrier Aggregation (CA) [5]. LTE is a promising solution for H2H communications and able to provide some benefits to MTC such as coverage, mobility support, fully standardised etc. However, it is still far from ideal for MTC due to the RRM and scheduling challenges caused by the unique MTC traffic characteristics. Therefore, in recent years a considerable amount of research effort has been devoted to find ways to adapt LTE network for MTC [4][6][8]. In the literature, GBS and TGS were introduced as RRM techniques to handle MTCD over LTE network [4]. GBS forms group (also known as clusters) of connected MTCDs and treat them as an individual device [6]. On the other hand, TGS exploits the similarity between MTC traffic and Voice over IP (VoIP) traffic to propose a scheduling algorithm for MTC [4][8]. Although, MTC is one of the most active research area, very little effort has been dedicated to investigate the EE of scheduling for MTC over LTE-A. For instance, GBS was introduced and a grouping algorithm was proposed in [6]. Similarly, Antonis et al. [4] enhanced the performance of GBS and TGS and proposed recommendations to adapt LTE network for MTC. However, both [4] and [6] evaluated the MTC RRM performance without paying much attention to the EE of the scheduling algorithms. In this paper, we analyse the EE of the GBS and TGS schemes for MTC over LTE-A. Firstly, we give a brief introduction of the state-of-the-art MTC schedulers for LTE/LTE-A in section II. Our system model is presented in section III. Afterwards, we derive a general expression to evaluate the eNodeB total transmit power needed to provide an acceptable Quality of Service (QoS) in section IV. We evaluate and discuss the EE of both scheduling schemes numerically based on the downlink power transmit by eNodeB and the system model in section V. Finally, section VI conclude this paper.
2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT)
The typical traffic models proposed in literature can be considered as heuristic models since the... more The typical traffic models proposed in literature can be considered as heuristic models since they only reflect the stochastic characteristic of the generated traffic. In this paper, we propose a model for M2M communications that generates the traffic. Therefore, the proposed model is able to capture a wider picture than the state-of-the-art traffic models. The proposed model illustrates the behaviour of M2M uplink communication in a network with multiple-access limited information capacity shared channels. In this paper, we analyzed the number of transmitted packets using the traffic model extracted from our proposed communication model and compared it with the state-ofthe-art traffic models using simulations. The simulation results show that the proposed model has a significantly higher accuracy in estimating the number of transmitted packets compared with the liteature model.
This study focuses on improving the sustainability of electrical supply in the healthcare system ... more This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simu...
The race for the 6th generation of wireless networks (6G) has begun. Researchers around the world... more The race for the 6th generation of wireless networks (6G) has begun. Researchers around the world have started to explore the best solutions for the challenges that the previous generations have experienced. To provide the readers with a clear map of the current developments, several review papers shared their vision and critically evaluated the state of the art. However, most of the work is based on general observations and the big picture vision, and lack the practical implementation challenges of the Internet of Things (IoT) use cases. This paper takes a novel approach in the review, as we present a sample of IoT use cases that are representative of a wide variety of its implementations. The chosen use cases are from the most research-active sectors that can benefit from 6G and its enabling technologies. These sectors are healthcare, smart grid, transport, and Industry 4.0. Additionally, we identified some of the practical challenges and the lessons learned in the implementation ...
— In order to enhance the Long Term Evolution (LTE) network performance, the Third Generation Par... more — In order to enhance the Long Term Evolution (LTE) network performance, the Third Generation Partnership Project (3GPP) introduced Coverage and Capacity Optimisation (CCO) in the context of Self Organising Network (SON). Antenna parameters (i.e. azimuth, electrical tilt etc.) play a key role in CCO and have a significant impact on the users' Quality of Service (QoS). In this paper, a novel metric, to evaluate the cells performance, that consider several performance indicators, is introduced. Furthermore, a distributed CCO algorithm is proposed which has three distinct phases. The first phase is to determine the target cell, the second phase adjust the antenna parameters for the target and neighbouring cells and in the last phase the optimum antenna parameters for the target and neighbouring cells is determined. The simulation results show significant improvement in the overall network performance with the proposed CCO algorithm. In particular, the target cell average performance can be improved by 16.75%.
— Traditional wireless and mobile network focuses on higher throughout, coverage and larger capac... more — Traditional wireless and mobile network focuses on higher throughout, coverage and larger capacity. In future, energy efficiency is of vital importance for wireless networks due to a large number of connected and battery constrained mobile devices. In Long Term Evolution Advanced (LTE-Advanced), Carrier Aggregation (CA) is proposed to increase the transmission bandwidth and hence data rate. This paper studies the effect of CA on the total power transmitted by the LTE-Advanced eNodeB based on the Orthogonal Frequency Division Multiple Access (OFDMA) downlink while taking the users Quality of Service (QoS) constraints into consideration. The numerical analysis and results show that by using CA a reduction in total power consumption can be achieved. Keywords— Energy-efficient mobile network; LTE-A; OFDMA downlink; Carrier Aggregation ; QoS.
— The 3 rd Generation Partnership Project (3GPP) introduced Long Term Evolution (LTE) in release ... more — The 3 rd Generation Partnership Project (3GPP) introduced Long Term Evolution (LTE) in release 8, and afterwards it was updated significantly in later releases (referred to as LTE-Advanced). LTE and LTE-Advanced (LTE-A) aim to achieve higher spectral efficiency, higher data rates, robustness and flexibility. Intelligent channel-aware radio resource scheduling is one of the key features of LTE-A. A number of schedulers proposed in the literature rely on the feedback sent from the Users Equipment (UE) without considering the presence of feedback delay. In this paper, we analyse the effect of the uplink delay on the cell performance of existing schedulers, in terms of throughput and the users' fairness. We then propose an adaptive hybrid scheduler to overcome the effect of the uplink delay on the scheduler performance. The simulation results show that our proposed scheduling algorithm outperforms the existing schedulers in the presence of uplink feedback delay.
—Machine Type Communication (MTC) is gaining an enormous interest among communication industry an... more —Machine Type Communication (MTC) is gaining an enormous interest among communication industry and academia all around the world. The variety of services offered by MTC is expected to significantly increase the number of MTC Devices (MTCD) on wireless networks. The huge number of MTCD poses several challenges to cellular network operators such as efficient radio resource management, energy efficiency (EE) etc. Two main radio resource management techniques to support MTC over 4G Long Term Evolution (LTE) were proposed in the literature: Group Based Scheduling (GBS) and Time Granularity Scheduling (TGS). In this paper, we compare the EE of GBS and TGS by formulating a general expression for the downlink transmit power by eNodeB. The numerical results show that the GBS is more energy efficient that TGS under given quality of service constraints. MAC and physical layer functionalities, such as Adaptive Modulation and Coding (AMC), Channel Quality Indicator (CQI) reporting and resource sharing. Later, 3GPP introduced LTE-Advanced (LTE-A) in release 10, which provides additional functionalities such as extended MIMO, heterogeneous networks and Carrier Aggregation (CA) [5]. LTE is a promising solution for H2H communications and able to provide some benefits to MTC such as coverage, mobility support, fully standardised etc. However, it is still far from ideal for MTC due to the RRM and scheduling challenges caused by the unique MTC traffic characteristics. Therefore, in recent years a considerable amount of research effort has been devoted to find ways to adapt LTE network for MTC [4][6][8]. In the literature, GBS and TGS were introduced as RRM techniques to handle MTCD over LTE network [4]. GBS forms group (also known as clusters) of connected MTCDs and treat them as an individual device [6]. On the other hand, TGS exploits the similarity between MTC traffic and Voice over IP (VoIP) traffic to propose a scheduling algorithm for MTC [4][8]. Although, MTC is one of the most active research area, very little effort has been dedicated to investigate the EE of scheduling for MTC over LTE-A. For instance, GBS was introduced and a grouping algorithm was proposed in [6]. Similarly, Antonis et al. [4] enhanced the performance of GBS and TGS and proposed recommendations to adapt LTE network for MTC. However, both [4] and [6] evaluated the MTC RRM performance without paying much attention to the EE of the scheduling algorithms. In this paper, we analyse the EE of the GBS and TGS schemes for MTC over LTE-A. Firstly, we give a brief introduction of the state-of-the-art MTC schedulers for LTE/LTE-A in section II. Our system model is presented in section III. Afterwards, we derive a general expression to evaluate the eNodeB total transmit power needed to provide an acceptable Quality of Service (QoS) in section IV. We evaluate and discuss the EE of both scheduling schemes numerically based on the downlink power transmit by eNodeB and the system model in section V. Finally, section VI conclude this paper.
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