Gregory Lenoir

Smart MIMO: an energy-aware adaptive MIMO-OFDM radio link control for next-generation wireless local area networks

Multiantenna systems and more particularly those operating on multiple input and multiple output (MIMO) channels are currently a must to improve wireless links spectrum efficiency and/or robustness. There exists a fundamental tradeoff between potential spectrum efficiency and robustness increase. However, multiantenna techniques also come with an overhead in silicon implementation area and power consumption due, at least, to the duplication of part of the transmitter and receiver radio front-ends. Although the area overhead may be acceptable in view of the performance improvement, low power consumption must be preserved for integration in nomadic devices. In this case, it is the tradeoff between performance (e.g., the net throughput on top of the medium access control layer) and average power consumption that really matters. It has been shown that adaptive schemes were mandatory to avoid that multiantenna techniques hamper this system tradeoff. In this paper, we derive smartMIMO: an adaptive multiantenna approach which, next to simply adapting the modulation and code rate as traditionally considered, decides packet-per-packet, depending on the MIMO channel state, to use either space-division multiplexing (increasing spectrum efficiency), space-time coding (increasing robustness), or to stick to single-antenna transmission. Contrarily to many of such adaptive schemes, the focus is set on using multiantenna transmission to improve the link energy efficiency in real operation conditions. Based on a model calibrated on an existing reconfigurable multiantenna transceiver setup, the link energy efficiency with the proposed scheme is shown to be improved by up to 30% when compared to nonadaptive schemes. The average throughput is, on the other hand, improved by up to 50% when compared to single-antenna transmission.

Energy-scalable OFDM transmitter design and control

Orthogonal frequency division multiplexing (OFDM) is the modulation of choice for broadband wireless communications. Unfortunately, it comes at the cost of a very low energy efficiency of the analog transmitter. Numerous circuit-level and signal processing techniques have been proposed to improve that energy efficiency. However more disruptive improvement can be achieved at system-level, capitalizing on energy-scalable design and circuit reconfiguration to match the user requirements and operation environment. We describe the design of such an energy-scalable reconfigurable transmitter as well as its control strategy. Based on measurement carried out on the physical realization of this transmitter, the benefit of system-level energy management is shown. Energy-efficiency scalability ranges over 30%, which translates in an average system-level energy improvement of up to 40% compared to a non-scalable system

Energy-scalability enhancement of wireless local area network transceivers

Next generation wireless local area networks (WLANs) have to cope with energy budgets severely constrained by portability, autonomy and high integration requirements. Practical power management approaches currently implemented aim at reducing the transceiver duty cycle. However, recently developed energy-aware link adaptation techniques, which trade off dynamically performance versus energy consumption, potentially bringing a factor-10 consumption reduction, promise to be more effective. Yet, to enable a meaningful trade-off, systems must present sufficient energy-scalability, i.e., energy consumption benefit when reducing the performance requirements or the environment constraints. This is not the case in current WLAN transceivers for which we show that duty cycle-based power management strategies are more effective. To make effective energy-aware link adaptation possible in future WLAN transceivers, we present techniques aiming at increasing their energy-scalability. Results show that a up to 7-fold energy consumption scalability can be achieved, providing significant margin to get energy consumption reduction by adapting to the user requirements.

Modelling Energy Consumption of an ASIC MPEG-4 Simple Profile Encoder

In wireless video streaming, it is desirable to minimize the energy consumption of mobile devices while achieving target video quality. For this purpose, it is essential to model (i.e., estimate) the energy cost of the streaming system, including both video encoder and wireless transmission energy, under different system settings. In this paper, an energy consumption model is proposed for a MPEG-4 simple profile encoder implemented in ASIC. Our proposed model consists of three major steps: 1) compute the encoder energy consumption through power simulations; 2) empirically model the impact of configuration parameters through curve fitting; and 3) online updating of model coefficients. Experimental results show that our proposed model works well for different types of video, and the average estimation error is below 6%.

Cross-layer optimization for multi-user video streaming over IEEE 802.11E HCCA wireless networks

In this paper, we propose a cross-layer optimization scheme for multi-user video streaming over the uplink of IEEE 802.11e HCCA wireless network. The objective is to minimize the energy consumption of all users, including both video encoder energy and wireless transmission energy, while delivering desired video quality for each user. In our proposed scheme, both cross-layer optimization of individual mobile terminal and inter-user resource allocation are carried out, so that the video encoder and wireless transmitter configurations can be jointly steered. Experimental results show that when compared to the transmission system without cross-layer optimization, our proposed scheme is able to reduce total energy consumption from 35% up to 80%, while satisfying the same video quality target.

Energy-aware radio link control for OFDM-based WLAN

Next generation wireless local area network (WLAN) terminals have to cope with increasing performance requirements while energy budgets are more and more constrained by portability. Next to low power circuit and architecture design, system-level power management is a key technology to fill this gap. Recently, radio link control techniques have been proposed, not only as a way to maximize performance but also to reach energy awareness. Transmit rate and power are adapted to meet exactly the user requirements while minimizing the average power consumption. However, schemes proposed so far do not exploit the characteristics of the specific modulation scheme considered in most recent WLAN standards: orthogonal frequency division multiplexing (OFDM). In this paper, we design a practical energy aware radio link control scheme, optimized for OFDM transceivers and compatible with current standards. Simulation results depict up to 80% transceiver power reduction when compared with throughput maximizing schemes.

SmartMIMO: Energy-Aware Adaptive MIMO-OFDM Radio Link Control for Wireless Local Area Networks

Multiple-antenna techniques (MIMO) have been proposed to improve wireless links spectrum efficiency and/or robustness. There exists a fundamental tradeoff between potential spectrum efficiency and robustness increase. But these multiple-antenna techniques come with an overhead in power consumption due to the duplication of part of the transmitter and receiver front-ends. From a system perspective, one has to focus on performance versus power consumption tradeoff. In this paper, we derive SmartMIMO: an adaptive energy-aware link adaptation approach which, next to the modulation and code rate, decides on using either space-division multiplexing (increasing spectrum efficiency) or space-time coding (increasing robustness) to transmit a given packet on a given MIMO channel. Energy-efficiency is shown to be improved by up to 30% when compared to non-adaptive techniques while the average rate is improved by up to 50% when compared to single-antenna transmission

Energy-efficient transmission of H.264 Scalable Video over IEEE 802.11E

Achieving low energy consumption is one of the main challenges for wireless video transmission on battery-limited devices. Moreover, the bandwidth is scarce and must be shared efficiently among users. The focus in this paper is on the timely delivery of multiple delay-sensitive video flows over a distributed access wireless LAN with minimal energy cost. This is done taking into consideration the Enhanced Distributed Channel Access (EDCA) mode and the Scalable Video Codec (SVC). In this context, a method is presented for energy-efficient resource allocation across the physical layer and medium access layer, by properly leveraging transmission modes and the available prioritization mechanisms. Global energy savings around 60% are achieved with respect to state-of-the-art EDCA under a wide range of network loads.

Channel-Aware Rate Adaptation for Energy Optimization and Congestion Avoidance

Achieving low energy consumption is one of the main challenges for wireless video transmission on battery limited devices. Moreover, the bandwidth is scarce and needs to be properly shared amongst different users. Congestion in the network can result in packet losses, with a significant impact on video quality. In this paper we propose the use of a channel-adaptive rate control mechanism in a multi-user WLAN up-link scenario. The benefit is twofold: the communication energy is reduced and congestion is strongly alleviated allowing an increase of the video quality or a network capacity increase for a similar quality.

Low-power SDRs through cross-layer control: concepts at work

Wireless access schemes was implemented on software defined radios (SDRs) in the future. In mobile terminals, SDRs should couple a high functional flexibility to low power operation. A two-step approach is advocated in this context. First, energy-scalability is introduced in the SDR design. Secondly, intelligent run-time cross-layer control is introduced to enable low power operation, by exploiting this scalability as well as the dynamics in the system. As a result, SDRs can be realized achieving a power consumption which can be comparable with dedicated radios, both in standby/idle mode or when transmitting or receiving data. This concept is validated on a transaction-level model (TLM) of our SDR platform, showing architectural integration and paving the way towards chip instantiation.