Flexible resource allocation for joint optimization of energy and spectral efficiency in OFDMA multi-cell networks

The radio resource allocation problem is studied, aiming to jointly optimize the energy efficiency (EE) and spectral efficiency (SE) of downlink OFDMA multi-cell networks. Different from existing works on either EE or SE optimization, a novel EE-SE tradeoff (EST) metric, which can capture both the EST relation and the individual cells’ preferences for EE or SE performance, is introduced as the utility function for each base station (BS). Then the joint EE-SE optimization problem is formulated, and an iterative subchannel allocation and power allocation algorithm is proposed. Numerical results show that the proposed algorithm can exploit the EST relation flexibly and optimize the EE and SE simultaneously to meet diverse EE and SE preferences of individual cells.<br/

Physics-based trade-off curves to develop a control access product in set-based concurrent engineering environment

Purpose This paper aims to present a process to generate physics-based trade-off curves (ToCs) to facilitate lean product development processes by enabling two key activities of set-based concurrent engineering (SBCE) process model that are comparing alternative design solutions and narrowing down the design set. The developed process of generating physics-based ToCs has been demonstrated via an industrial case study which is a research project. Design/methodology/approach The adapted research approach for this paper consists of three phases: a review of the related literature, developing the process of generating physics-based ToCs in the concept of lean product development, implementing the developed process in an industrial case study for validation through the SBCE process model. Findings Findings of this application showed that physics-based ToC is an effective tool to enable SBCE activities, as well as to save time and provide the required knowledge environment for the designers to support their decision-making. Practical implications Authors expect that this paper will guide companies, which are implementing SBCE processes throughout their lean product development journey. Physics-based ToCs will facilitate accurate decision-making in comparing and narrowing down the design-set through the provision of the right knowledge environment. Originality/value SBCE is a useful approach to develop a new product. It is essential to provide the right knowledge environment in a quick and visual manner which has been addressed by demonstrating physics knowledge in ToCs. Therefore, a systematic process has been developed and presented in this paper. The research found that physics-based ToCs could help to identify different physics characteristics of the product in the form of design parameters and visualise in a single graph for all stakeholders to understand without a need for an extensive engineering background and for designers to make a decision faster

Knowledge creation and visualisation by using trade-off curves to enable set-based concurrent engineering applications

Inefficiencies that could be avoided during the product development process account for a large percentage of the manufacturing cost. To introduce innovative, high-quality products in a time- and cost-efficient manner, companies need to improve the performance of their product development processes. Set-based concurrent engineering (SBCE) has the capability of addressing this issue if the right knowledge-environment is provided. Trade-off curves (ToCs) are effective tools to provide this environment through knowledge creation and visualisation. However, there are several challenges that designers face during their product development activities such as rework, inaccurate decisions, and failure in design performance, which eventually cause waste. Therefore, the aim of this thesis is to eliminate waste by developing a systematic approach for generating and using ToCs. These then serve as a guide for designers to support their decision-making and achieve an efficient product development performance in an SBCE environment. To achieve this aim, qualitative research methods were employed. Following an extensive literature review, industrial field study and industrial applications, three processes were developed to generate ToCs and validated with five industrial case studies. The process for generating knowledge-based ToCs describes how to create and visualise knowledge that is obtained from historical data and/or experience. This process facilitates the reuse of knowledge about existing products, in order to reduce the requirement for resources (e.g. product development time). The process for generating physics-based ToCs describes an approach to creating knowledge that is obtained from understanding the physics and functionality of the product under development. Thus, the practitioners gain sufficient confidence for identifying a compromise between conflicting design parameters. Finally, the process for using ToCs within the SBCE process model presents a technique to use generated knowledge-based and physics-based ToCs in order to enable key SBCE activities. These activities are (1) Identifying the feasible design area, (2) Developing a design-set, (3) Comparing possible design solutions, (4) Narrowing down the design-set and (5) Achieving the final optimal design solution. For validation, the developed processes were applied in five industrial case studies, and two expert judgements were obtained. Findings showed that ToCs are essential tools in several aspects of new product development, specifically by reducing the lead time through enabling more confident and accurate decisions. Additionally, it was found that through ToCs, the conflicting relationships between the characteristics of the product can be understood and communicated effectively among the designers. This facilitated the decision-making on an optimal design solution in a remarkably short period of time. The design performance of this optimal design increased by nearly 60% in a case study of a surface jet pump. Furthermore, it was found that ToCs have the capability of storing useful data for knowledge creation and reusing the created knowledge for the future projects

Statistical delay QoS driven resource allocation and performance analysis for wireless communication networks

Delay quality-of-service (QoS) guarantees play a critical role in enabling delay-sensitive wireless applications. By applying the theory of effective capacity (EC), the maximum arrival rate with a guaranteed delay-outage probability constraint, is analyzed and investigated in terms of delayconstrained resource allocation and link-layer throughput analysis. Firstly, a joint optimization problem of link-layer energy efficiency (EE) and EC in a single-user single-carrier communication system, is proposed and investigated, under a delay violation probability requirement and an average transmit power constraint. Formulated as a normalized multiobjective optimization problem (MOP), the problem is transformed into a weighted single-objective optimization problem (SOP), and then solved. The proposed optimal power value is proved to be sufficient for the Pareto optimal set of the original EE-EC MOP. Secondly, a total EC maximization problem subject to the individual linklayer EE requirement as well as the per-user average transmit power limit, in a multi-user multi-carrier orthogonal frequency-division multiple access (OFDMA) system, is proposed and analyzed. Formulated as a combinatorial integer programming problem, the problem is decoupled into a frequency provisioning problem and an independent per-user multi-carrier EE-EC tradeoff problem. A low-complexity heuristic algorithm is proposed to obtain the subcarrier assignment solution coupled with a per-user optimal power allocation strategy, across frequency and time domains. Finally, the achievable link-layer rate under the per-user delay QoS requirements is studied for a downlink M-user non-orthogonal multiple access (NOMA) network. The impact of the transmit signal-to-noise ratio (SNR) and the delay QoS requirement on the per-user achievable EC and the total link-layer rate is investigated and compared between NOMA and orthogonal multiple access (OMA) networks. All theoretical conclusions and closed-form expressions are confirmed with Monte Carlo results

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Spectral and Energy Efficiency in Cellular Mobile Radio Access Networks

Driven by the widespread use of smartphones and the release of a wide range of online packet data services, an unprecedented growth in the mobile data usage has been observed over the last decade. Network operators recently realised that the traditional approach of deploying more macrocells could not cope with this continuous growth in mobile data traffic and if no actions are taken, the energy demand to run the networks, which are able to support such traffic volumes risks to become unmanageable. In this context, comprehensive investigations of different cellular network deployments, and various algorithms have been evaluated and compared against each other in this thesis, to determine the best deployment options which are able to deliver the required capacity at a minimum level of energy consumption. A new scalable base station power consumption model was proposed and a joint evaluation framework for the relative improvements in throughput, energy consumption,and energy efficiency is adopted to avoid the inherent ambiguity of using only the bit/J energy efficiency metric. This framework was applied to many cellular network cases studies including macro only, small cell only and heterogeneous networks to show that pure small cell deployments outperform the macro and heterogeneous networks in terms of the energy consumption even if the backhaul power consumption is included in the analysis. Interestingly, picocell only deployments can attain up to 3 times increase in the throughput and 2.27 times reduction in the energy consumed when compared with macro only RANs at high target capacities, while it offers 2 times more throughput and reduces the energy consumption by 12% when compared with the macro/pico HetNet deployments. Further investigations have focused on improving the macrocell RAN by adding more sectors and more antennas. Importantly, the results have shown that adding small cells to the macrocell RAN is more energy efficient than adding more sectors even if adaptive sectorisation techniques are employed. While dimensioning the network by using MIMO base stations results in less consumed energy than using SISO base stations. The impact of traffic offloading to small cell, sleep mode, and inter-cell interference coordination techniques on the throughput and energy consumption in dense heterogeneous network deployments have been investigated. Significant improvements in the throughput and energy efficiency in bit/J were observed. However, a decrease in the energy consumption is obtained only in heterogeneous networks with small cells deployed to service clusters of users. Finally, the same framework is used to evaluate the throughput and energy consumption of massive MIMO deployments to show the superiority of massive MIMOs versus macrocell RANs, small cell deployments and heterogeneous networks in terms of achieving the target capacity with a minimum level of energy consumption. 1.6 times reduction in the energy consumption is achieved by massive MIMOs when compared with picocell only RAN at the same target capacity and when the backhaul power consumption is included in the analysis