Wi-Fi Teeter-Totter: Overclocking OFDM for Internet of Things

The conventional high-speed Wi-Fi has recently become a contender for low-power Internet-of-Things (IoT) communications. OFDM continues its adoption in the new IoT Wi-Fi standard due to its spectrum efficiency that can support the demand of massive IoT connectivity. While the IoT Wi-Fi standard offers many new features to improve power and spectrum efficiency, the basic physical layer (PHY) structure of transceiver design still conforms to its conventional design rationale where access points (AP) and clients employ the same OFDM PHY. In this paper, we argue that current Wi-Fi PHY design does not take full advantage of the inherent asymmetry between AP and IoT. To fill the gap, we propose an asymmetric design where IoT devices transmit uplink packets using the lowest power while pushing all the decoding burdens to the AP side. Such a design utilizes the sufficient power and computational resources at AP to trade for the transmission (TX) power of IoT devices. The core technique enabling this asymmetric design is that the AP takes full power of its high clock rate to boost the decoding ability. We provide an implementation of our design and show that it can reduce the IoT's TX power by boosting the decoding capability at the receivers

Energy-Aware WiFi Network Selection via Forecasting Energy Consumption

Covering a wide area by a large number of WiFi networks is anticipated to become very popular with Internet-of-things (IoT) and initiatives such as smart cities. Such network configuration is normally realized through deploying a large number of access points (APs) with overlapped coverage. However, the imbalanced traffic load distribution among different APs affects the energy consumption of a WiFi device if it is associated to a loaded AP. This research work aims at predicting the communication-related energy that shall be consumed by a WiFi device if it transferred some amount of data through a certain selected AP. In this paper, a forecast of the energy consumption is proposed to be obtained using an algorithm that is supported by a mathematical model. Consequently, the proposed algorithm can automatically select the best WiFi network (best AP) that the WiFi device can connect to in order to minimize energy consumption. The proposed algorithm is experimentally validated in a realistic lab setting. The observed performance indicates that the algorithm can provide an accurate forecast to the energy that shall be consumed by a WiFi transceiver in sending some amount of data via a specific AP

An analysis of IEEE 802.11 DCF and its application to energy-efficient relaying in multihop wireless networks

Cataloged from PDF version of article.We present an analytical model for the IEEE 802.11 DCF in multihop wireless networks that considers hidden terminals and accurately works for a large range of traffic loads. An energy model, which considers energy consumption due to collisions, retransmissions, exponential backoff and freezing mechanisms, and overhearing of nodes, and the proposed IEEE 802.11 DCF analytical model are used to analyze the energy consumption of various relaying strategies. The results show that the energy-efficient relaying strategy depends significantly on the traffic load. Under light traffic, energy spent during idle mode dominates, making any relaying strategy nearly optimal. Under moderate traffic, energy spent during idle and receive modes dominates and multihop transmissions become more advantageous where the optimal hop number varies with processing power consumed at relay nodes. Under very heavy traffic, where multihopping becomes unstable due to increased collisions, direct transmission becomes more energy efficient. The choice of relaying strategy is observed to affect energy efficiency more for large and homogeneous networks where it is beneficial to use multiple short hops each covering similar distances. The results indicate that a cross-layered relaying approach, which dynamically changes the relaying strategy, can substantially save energy as the network traffic load changes in time. © 2011 IEEE

Distributed Optimal Estimation from Relative Measurements for Localization and Time Synchronization

We consider the problem of estimating vector-valued variables from noisy “relative” measurements. The measurement model can be expressed in terms of a graph, whose nodes correspond to the variables being estimated and the edges to noisy measurements of the difference between the two variables. This type of measurement model appears in several sensor network problems, such as sensor localization and time synchronization. We consider the optimal estimate for the unknown variables obtained by applying the classical Best Linear Unbiased Estimator, which achieves the minimum variance among all linear unbiased estimators.We propose a new algorithm to compute the optimal estimate in an iterative manner, the Overlapping Subgraph Estimator algorithm. The algorithm is distributed, asynchronous, robust to temporary communication failures, and is guaranteed to converges to the optimal estimate even with temporary communication failures. Simulations for a realistic example show that the algorithm can reduce energy consumption by a factor of two compared to previous algorithms, while achieving the same accuracy

Modeling Energy Consumption in Single-Hop IEEE 802.11 Ad Hoc Networks

This paper presents an analytical model to predict energy consumption in saturated IEEE 802.11 single-hop ad hoc networks under ideal channel conditions. The model we introduce takes into account the different operational modes of the IEEE 802.11 DCF MAC, and is validated against packetlevel simulations. In contrast to previous works that attempted to characterize the energy consumption of IEEE 802.11 cards in isolated, contention-free channels (i.e., single sender/receiver pair), this paper investigates the extreme opposite case, i.e., when nodes need to contend for channel access under saturation conditions. In such scenarios, our main findings include: (1) contrary to what most previous results indicate, the radio's transmit mode has marginal impact on overall energy consumption, while other modes (receive, idle, etc.) are responsible for most of the energy consumed; (2) the energy cost to transmit useful data increases almost linearly with the network size; and (3) transmitting large payloads is more energy efficient under saturation conditions

Energy consumption evaluation on the MAC layer of PRCSMA

En este proyecto se realizará un estudio de los actuales modelos de consumo energético para comunicaciones inalámbricas. El objetivo del trabajo es evaluar y optimizar el consumo de energía de un protocolo de acceso al medio diseñado para comunicaciones cooperativas: PRCSMA. Este protocolo está basado en el estándar IEEE 802.11 para redes de área local. La meta principal es identificar las condiciones bajo las que los esquemas de cooperación pueden resultar beneficiosos en términos de ahorro de energía consumida

Energy consumption evaluation on the MAC layer of PRCSMA

En este proyecto se realizará un estudio de los actuales modelos de consumo energético para comunicaciones inalámbricas. El objetivo del trabajo es evaluar y optimizar el consumo de energía de un protocolo de acceso al medio diseñado para comunicaciones cooperativas: PRCSMA. Este protocolo está basado en el estándar IEEE 802.11 para redes de área local. La meta principal es identificar las condiciones bajo las que los esquemas de cooperación pueden resultar beneficiosos en términos de ahorro de energía consumida