Mobile communications are increasingly contributing to global energy consumption. In this article, a holistic approach for energy efficient mobile radio networks is presented. The matter of having appropriate metrics and evaluation methods that allow assessing the energy efficiency of the entire system is discussed. The mutual supplementary saving concepts comprise component, link and network levels. At the component level the power amplifier complemented by a transceiver and a digital platform supporting advanced power management are key to efficient radio implementations. Discontinuous transmission by base stations, where hardware components are switched off, facilitate energy efficient operation at the link level. At the network level, the potential for reducing energy consumption is in the layout of networks and their management, that take into account slowly changing daily load patterns, as well as highly dynamic traffic fluctuations. Moreover, research has to analyze new disruptive architectural approaches, including multi-hop transmission, ad-hoc meshed networks, terminal-to-terminal communications, and cooperative multipoint architectures.

Advances in low-power and low-cost sensor networks have led to solutions mature enough for use in a broad range of applications varying from health monitoring to building surveillance. The development of those applications has been stimulated by the finalization of the IEEE 802.15.4 standard, which defines the medium access control (MAC) and physical layer for sensor networks. One of the MAC schemes proposed is slotted carrier sense multiple access with collision avoidance (CSMA/CA), and this paper analyzes whether this scheme meets the design constraints of those low-power and low-cost sensor networks. The paper provides a detailed analytical evaluation of its performance in a star topology network, for uplink and acknowledged uplink traffic. Both saturated and unsaturated periodic traffic scenarios are considered. The form of the analysis is similar to that of Bianchi for IEEE 802.11 DCF only in the use of a per user Markov model to capture the state of each user at each moment in time. The key assumptions to enable this important simplification and the coupling of the per user Markov models are however different, as a result of the very different designs of the 802.15.4 and 802.11 carrier sensing mechanisms. The performance predicted by the analytical model is very close to that obtained by simulation. Throughput and energy consumption analysis is then performed by using the model for a range of scenarios. Some design guidelines are derived to set the 802.15.4 parameters as function of the network requirements.

Nowadays, a lot of effort is spent on developing inexpensive orthogonal frequency-division multiplexing (OFDM) receivers. Especially, zero intermediate frequency (zero-IF) receivers are very appealing, because they avoid costly IF filters. However, zero-IF front-ends also introduce significant additional front-end distortion, such as IQ imbalance. Moreover, zero-IF does not solve the phase noise problem. Unfortunately, OFDM is very sensitive to the receiver nonidealities IQ imbalance and phase noise. Therefore, we developed a new estimation/compensation scheme to jointly combat the IQ imbalance and phase noise at baseband. In this letter, we describe the algorithms and present the performance results. Our compensation scheme eliminates the IQ imbalance based on one OFDM symbol and performs well in the presence of phase noise. The compensation scheme has a fast convergence and a small residual degradation: even for large IQ imbalance, the overall system performance for an OFDM-wireless local area network (WLAN) case study is within 0.6 dB of the optimal case. As such, our approach greatly relaxes the mismatch specifications and thus enables low-cost zero-IF receivers.

A cognitive radio (CR) network should be able to sense its environment and adapt communication to utilize the unused licensed spectrum without interfering with licensed users. In this paper, we look at CR-enabled networks with distributed control. As CR nodes need to hop from channel to channel to make the most use of the spectrum opportunities, we believe distributed multichannel medium access control (MAC) protocols to be key enablers for these networks. In addition to the spectrum scarcity, energy is rapidly becoming one of the major bottlenecks of wireless operations and has to be considered as a key design criterion. We present here an energy-efficient distributed multichannel MAC protocol for CR networks (MMAC-CR). Simulation results show that the proposed protocol significantly improves performance by borrowing the licensed spectrum and protects primary users (PUs) from interference, even in hidden terminal situations. Sensing costs are evaluated and shown to contribute only 5% to the total energy cost.

Long-range wireless connectivity technologies for sensors and actuators open the door for a variety of new Internet of Things (IoT) applications. These technologies can be deployed to establish new monitoring capabilities and enhance efficiency of services in a rich diversity of domains. Low energy consumption is essential to enable battery-powered IoT nodes with a long autonomy. This paper explains the challenges posed by combining low-power and long-range connectivity. An energy breakdown demonstrates the dominance of transmit and sleep energy. The principles for achieving both low-power and wide-area are outlined, and the landscape of available networking technologies that are suited to connect remote IoT nodes is sketched. The typical anatomy of such a node is presented, and the subsystems are zoomed into. The art of designing remote IoT devices requires an application-oriented approach, where a meticulous design and smart operation are essential to grant a long battery life. In particular we demonstrate the importance of strategies such as “think before you talk” and “race to sleep”. As maintenance of IoT nodes is often cumbersome due to being deployed at hard to reach places, extending the battery life of these devices is critical. Moreover, the environmental impact of batteries further demonstrates the need for a longer battery life in order to reduce the number of batteries used.