An Energy Efficient Semi-static Power Control and Link Adaptation Scheme in UMTS HSDPA

High speed downlink packet access (HSDPA) has been successfully applied in commercial systems and improves user experience significantly. However, it incurs substantial energy consumption. In this paper, we address this issue by proposing a novel energy efficient semi-static power control and link adaptation scheme in HSDPA. Through estimating the EE under different modulation and coding schemes (MCSs) and corresponding transmit power, the proposed scheme can determine the most energy efficient MCS level and transmit power at the Node B. And then the Node B configure the optimal MCS level and transmit power. In order to decrease the signaling overhead caused by the configuration, a dual trigger mechanism is employed. After that, we extend the proposed scheme to the multiple input multiple output (MIMO) scenarios. Simulation results confirm the significant EE improvement of our proposed scheme. Finally, we give a discussion on the potential EE gain and challenge of the energy efficient mode switching between single input multiple output (SIMO) and MIMO configuration in HSDPA.Comment: 9 pages, 11 figures, accepted in EURASIP Journal on Wireless Communications and Networking, special issue on Green Radi

Improving Energy Efficiency Through Multimode Transmission in the Downlink MIMO Systems

Adaptively adjusting system parameters including bandwidth, transmit power and mode to maximize the "Bits per-Joule" energy efficiency (BPJ-EE) in the downlink MIMO systems with imperfect channel state information at the transmitter (CSIT) is considered in this paper. By mode we refer to choice of transmission schemes i.e. singular value decomposition (SVD) or block diagonalization (BD), active transmit/receive antenna number and active user number. We derive optimal bandwidth and transmit power for each dedicated mode at first. During the derivation, accurate capacity estimation strategies are proposed to cope with the imperfect CSIT caused capacity prediction problem. Then, an ergodic capacity based mode switching strategy is proposed to further improve the BPJ-EE, which provides insights on the preferred mode under given scenarios. Mode switching compromises different power parts, exploits the tradeoff between the multiplexing gain and the imperfect CSIT caused inter-user interference, improves the BPJ-EE significantly.Comment: 19 pages, 10 figures, EURASIP Journal on Wireless Communications and Networking; EURASIP Journal on Wireless Communications and Networking (2011) 2011:20

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.acceptedVersio