Evaluation of the potential for energy saving in macrocell and femtocell networks using a heuristic introducing sleep modes in base stations

In mobile technologies two trends are competing. On the one hand, the mobile access network requires optimisation in energy consumption. On the other hand, data volumes and required bit rates are rapidly increasing. The latter trend requires the deployment of more dense mobile access networks as the higher bit rates are available at shorter distance from the base station. In order to improve the energy efficiency, the introduction of sleep modes is required. We derive a heuristic which allows establishing a baseline of active base station fractions in order to be able to evaluate mobile access network designs. We demonstrate that sleep modes can lead to significant improvements in energy efficiency and act as an enabler for femtocell deployments

On the Energy Efficiency of LT Codes in Proactive Wireless Sensor Networks

This paper presents an in-depth analysis on the energy efficiency of Luby Transform (LT) codes with Frequency Shift Keying (FSK) modulation in a Wireless Sensor Network (WSN) over Rayleigh fading channels with pathloss. We describe a proactive system model according to a flexible duty-cycling mechanism utilized in practical sensor apparatus. The present analysis is based on realistic parameters including the effect of channel bandwidth used in the IEEE 802.15.4 standard, active mode duration and computation energy. A comprehensive analysis, supported by some simulation studies on the probability mass function of the LT code rate and coding gain, shows that among uncoded FSK and various classical channel coding schemes, the optimized LT coded FSK is the most energy-efficient scheme for distance d greater than the pre-determined threshold level d_T , where the optimization is performed over coding and modulation parameters. In addition, although the optimized uncoded FSK outperforms coded schemes for d < d_T , the energy gap between LT coded and uncoded FSK is negligible for d < d_T compared to the other coded schemes. These results come from the flexibility of the LT code to adjust its rate to suit instantaneous channel conditions, and suggest that LT codes are beneficial in practical low-power WSNs with dynamic position sensor nodes.Comment: accepted for publication in IEEE Transactions on Signal Processin

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Analytical characterisation of the terahertz in-vivo nano-network in the presence of interference based on TS-OOK communication scheme

The envisioned dense nano-network inside the human body at terahertz (THz) frequency suffers a communication performance degradation among nano-devices. The reason for this performance limitation is not only the path loss and molecular absorption noise, but also the presence of multi-user interference and the interference caused by utilising any communication scheme, such as time spread ON—OFF keying (TS-OOK). In this paper, an interference model utilising TS-OOK as a communication scheme of the THz communication channel inside the human body has been developed and the probability distribution of signal-to-interference-plus-noise ratio (SINR) for THz communication within different human tissues, such as blood, skin, and fat, has been analyzed and presented. In addition, this paper evaluates the performance degradation by investigating the mean values of SINR under different node densities in the area and the probabilities of transmitting pulses. It results in the conclusion that the interference restrains the achievable communication distance to approximate 1 mm, and more specific range depends on the particular transmission circumstance. Results presented in this paper also show that by controlling the pulse transmission probability and node density, the system performance can be ameliorated. In particular, SINR of in vivo THz communication between the deterministic targeted transmitter and the receiver with random interfering nodes in the medium improves about 10 dB, when the node density decreases one order. The SINR increases approximate 5 and 2 dB, when the pulse transmitting probability drops from 0.5 to 0.1 and 0.9 to 0.5