Traffic-Driven Energy Efficient Operational Mechanisms in Cellular Access Networks

Recent explosive growth in mobile data traffic is increasing energy consumption in cellular networks at an incredible rate. Moreover, as a direct result of the conventional static network provisioning approach, a significant amount of electrical energy is being wasted in the existing networks. Therefore, in recent time, the issue of designing energy efficient cellular networks has drawn significant attention, which is also the foremost motivation behind this research. The proposed research is particularly focused on the design of self-organizing type traffic-sensitive dynamic network reconfiguring mechanisms for energy efficiency in cellular systems. Under the proposed techniques, radio access networks (RANs) are adaptively reconfigured using less equipment leading to reduced energy utilization. Several energy efficient cellular network frameworks by employing inter-base station (BS) cooperation in RANs are proposed. Under these frameworks, based on the instantaneous traffic demand, BSs are dynamically switched between active and sleep modes by redistributing traffic among them and thus, energy savings is achieved. The focus is then extended to exploiting the availability of multiple cellular networks for extracting energy savings through inter-RAN cooperation. Mathematical models for both of these single-RAN and multi-RAN cooperation mechanisms are also formulated. An alternative energy saving technique using dynamic sectorization (DS) under which some of the sectors in the underutilized BSs are turned into sleep mode is also proposed. Algorithms for both the distributed and the centralized implementations are developed. Finally, a two-dimensional energy efficient network provisioning mechanism is proposed by jointly applying both the DS and the dynamic BS switching. Extensive simulations are carried out, which demonstrate the capability of the proposed mechanisms in substantially enhancing the energy efficiency of cellular networks

Design and Development of Smart Brain-Machine-Brain Interface (SBMIBI) for Deep Brain Stimulation and Other Biomedical Applications

Machine collaboration with the biological body/brain by sending electrical information back and forth is one of the leading research areas in neuro-engineering during the twenty-first century. Hence, Brain-Machine-Brain Interface (BMBI) is a powerful tool for achieving such machine-brain/body collaboration. BMBI generally is a smart device (usually invasive) that can record, store, and analyze neural activities, and generate corresponding responses in the form of electrical pulses to stimulate specific brain regions. The Smart Brain-Machine-Brain-Interface (SBMBI) is a step forward with compared to the traditional BMBI by including smart functions, such as in-electrode local computing capabilities, and availability of cloud connectivity in the system to take the advantage of powerful cloud computation in decision making. In this dissertation work, we designed and developed an innovative form of Smart Brain-Machine-Brain Interface (SBMBI) and studied its feasibility in different biomedical applications. With respect to power management, the SBMBI is a semi-passive platform. The communication module is fully passive—powered by RF harvested energy; whereas, the signal processing core is battery-assisted. The efficiency of the implemented RF energy harvester was measured to be 0.005%. One of potential applications of SBMBI is to configure a Smart Deep-Brain-Stimulator (SDBS) based on the general SBMBI platform. The SDBS consists of brain-implantable smart electrodes and a wireless-connected external controller. The SDBS electrodes operate as completely autonomous electronic implants that are capable of sensing and recording neural activities in real time, performing local processing, and generating arbitrary waveforms for neuro-stimulation. A bidirectional, secure, fully-passive wireless communication backbone was designed and integrated into this smart electrode to maintain contact between the smart electrodes and the controller. The standard EPC-Global protocol has been modified and adopted as the communication protocol in this design. The proposed SDBS, by using a SBMBI platform, was demonstrated and tested through a hardware prototype. Additionally the SBMBI was employed to develop a low-power wireless ECG data acquisition device. This device captures cardiac pulses through a non-invasive magnetic resonance electrode, processes the signal and sends it to the backend computer through the SBMBI interface. Analysis was performed to verify the integrity of received ECG data

QoS-aware Adaptive Resource Management in OFDMA Networks

PhDOne important feature of the future communication network is that users in the network are required to experience a guaranteed high quality of service (QoS) due to the popularity of multimedia applications. This thesis studies QoS-aware radio resource management schemes in different OFDMA network scenarios. Motivated by the fact that in current 4G networks, the QoS provisioning is severely constrained by the availability of radio resources, especially the scarce spectrum as well as the unbalanced traffic distribution from cell to cell, a joint antenna and subcarrier management scheme is proposed to maximise user satisfaction with load balancing. Antenna pattern update mechanism is further investigated with moving users. Combining network densi fication with cloud computing technologies, cloud radio access network (C-RAN) has been proposed as the emerging 5G network architecture consisting of baseband unit (BBU) pool, remote radio heads (RRHs) and fronthaul links. With cloud based information sharing through the BBU pool, a joint resource block and power allocation scheme is proposed to maximise the number of satisfi ed users whose required QoS is achieved. In this scenario, users are served by high power nodes only. With spatial reuse of system bandwidth by network densi fication, users' QoS provisioning can be ensured but it introduces energy and operating effciency issue. Therefore two network energy optimisation schemes with QoS guarantee are further studied for C-RANs: an energy-effective network deployment scheme is designed for C-RAN based small cells; a joint RRH selection and user association scheme is investigated in heterogeneous C-RAN. Thorough theoretical analysis is conducted in the development of all proposed algorithms, and the effectiveness of all proposed algorithms is validated via comprehensive simulations.China Scholarship Counci

Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure