Antoine Dejonghe

A Distributed Multichannel MAC Protocol for Multihop Cognitive Radio Networks

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.

Turbo synchronization: an EM algorithm interpretation

This paper is devoted to turbo synchronization, that is to say the use of soft information to estimate parameters like carrier phase, frequency offset or timing within a turbo receiver. It is shown how maximum-likelihood estimation of those synchronization parameters can be implemented by means of the iterative expectation-maximization (EM) algorithm [A.P. Dempster, et al., 1977]. Then we show that the EM algorithm iterations can be combined with those of a turbo receiver. This leads to a general theoretical framework for turbo synchronization. The soft decision-directed ad-hoc algorithm proposed in V. Lottici and M. Luise, [2002] for carrier phase recovery turns out to be a particular instance of this implementation. The proposed mathematical framework is illustrated by simulations reported for the particular case of carrier phase estimation combined with iterative demodulation and decoding [S. ten Brink, et al., 1998].

Turbo-equalization for multilevel modulation: an efficient low-complexity scheme

This paper addresses the problem of iterative equalization and decoding (turbo-equalization) when bit-interleaved multilevel modulations are considered. The goal is to propose an efficient low-complexity solution in this context, where optimal turbo-equalization is totally untractable. Therefore, we generalize reduced-complexity soft-in/soft-out (SISO) equalizers based on the minimum mean square error (MMSE) criterion (originally proposed in a BPSK context) to this particular scheme. Performances are illustrated through simulations. We show the influence of the mapping on the signal-to-noise ratio (SNR) threshold and on asymptotic performances, and link the obtained results to iterative demodulation and decoding on an additive white Gaussian noise (AWGN) channel.

Distributed cognitive coexistence of 802.15.4 with 802.11

Thanks to recent advances in wireless technology, a broad range of standards are currently emerging. Interoperability and coexistence between these heterogeneous networks are becoming key issues, which require new adaptation strategies to avoid harmful interference. In this paper, we focus on the coexistence of 802.11 Wireless LAN and 802.15.4 sensor networks in the ISM band. Those networks have very different transmission characteristics that result in asymmetric interference patterns. We propose distributed adaptation strategies for 802.15.4 nodes, to minimize the impact of the 802.11 interference. This interference varies in time, frequency and space and the sensor nodes adapt by changing their frequency channel selection over time. Different distributed techniques are proposed, based on scanning (with increasing power cost) on the one hand, and based on increased cognition through learning on the other hand. These techniques are evaluated both for performance and energy cost. We show that it is possible to achieve distributed frequency allocation approaches that result only in an increase of 20% of the delay performance compared to ideal frequency allocation. Moreover, it is shown that a factor of two in energy consumption can be saved by adding learning to the system

MMSE-based fractional turbo receiver for space-time BICM over frequency-selective MIMO fading channels

Space-time bit-interleaved coded multilevel modulation over frequency-selective multiple-input multiple-output (MIMO) fading channels is considered. The receiver is turbo based. A soft-input soft-output (SISO) space-time fractionally spaced equalizer is designed for the minimum mean square error (MMSE) criterion. Simulation results show the ability of the receiver to account for intersymbol interference, co-antenna interference, and its capability to exploit transmit, multipath, and receive diversity. These results are also compared to a bit-error-rate lower bound.

Future Software-Defined Radio Platforms and Mapping Flows

A software-defined radio (SDR) system is a radio communication system in which physical layer components are implemented on a programmable or reconfigurable platform. The modulation and demodulation is performed in software and thus the radio is able to support a broad ran: of frequencies and functions concurrently. In the ideal SDR transceiver scheme, an analog-to-digital converter (ADC) and a digital-to-analog converter (DAC) are attached to the antenna. This would imply that a digital signal processor (DSP) is connected to the ADC and the DAC, directly performing signal processing for the streams of data from/to antenna. Today, the ideal SDR transceiver scheme is still not feasible and thus some processing has to happen in the reconfigurable analog front end.

Comparison of EM-Based Algorithms for MIMO Channel Estimation

Iterative channel estimation can improve the channel-state information (CSI) with respect to noniterative estimation. New iterative channel estimators based on the expectation-maximization (EM) algorithm are proposed in this paper. A first estimator, called the unbiased EM (UEM), is designed to unbias the EM estimates. A second estimator is then put forward, which is based on the expectation-conditional-maximization (ECM) algorithm, and its complexity is lower than that of the EM. An unbiased ECM (UECM) estimator is also proposed. Although the unbiasedness of the UEM and UECM estimators is not rigorously proved, the use of these names is explained in the paper. The new estimators are compared with well-known ones, such as the EM, the decision-directed (DD), and the data-aided (DA) estimators. Simulations are reported for a turbo receiver operating over frequency-selective multiple-input multiple-output channels. It is shown that the UEM channel estimator outperforms the EM, and that the ECM-based estimators are very close to the EM-based ones

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.

Constructing radio environment maps with heterogeneous spectrum sensors

In this demonstration proposal we describe a prototype of a radio environment map (REM) for storing and reasoning about spectrum data obtained from heterogeneous sources. The architecture of the REM prototype is both modular and extendible, and can be used with very diverse spectrum sensors, ranging from high-fidelity spectrum analyzers to dedicated low-cost embedded solutions. In the proposed demonstration we will illustrate how information such as transmitter locations and estimates of spectrum occupancy over space and time can be inferred and made available through the REM, based on information obtained from a network of different spectrum sensors deployed specifically for the demonstration.

Accumulative Interference Modeling for Cognitive Radios with Distributed Channel Access

A cognitive radio (CR) network should be able to sense its environment and adapt its communication to utilize unused licensed spectrum without interfering with incumbents. Properly modeling the expected interference from the CR network is therefore very important in the definition of coexistence rules to efficiently protect the incumbents. In this paper we model the accumulative interference generated from a large-scale CR network and investigate how this affects the sensing requirements of the CRs to meet an interference constraint. More specifically, our model considers the impact of discrete topology and the impact of the distributed channel access scheme. As an instantiation of our model, we consider a CR network based on the IEEE 802.11 standard. We show that the interference generated is large, since collisions cannot be avoided.