Index Modulation (IM) techniques enable a significant Spectral Energy (SE) and/or Energy Efficiency (EE) enhancement. In this paper, a novel Filter IM domain is being explored, where a novel scheme Filter Shape Index Modulation (FSIM) is proposed. In contrast to most existing Single-Input Single-Output (SISO) IM systems, the proposed scheme achieves a higher SE/EE gain since it exploits all available time and frequency resources. The FSIM system transmits any conventional modulation (QAM, PSK,…) while conveying additional information bits by the index of pulse shaping filter shape. The optimal joint Maximum Likelihood detector is presented, and a low complexity optimal detector is proposed. In addition, an Inter-Symbol Interference (ISI) estimation and cancellation technique is developed to enable the usage of non-Nyquist filters. Finally, the results reveal that FSIM has a similar performance with the two proposed detectors, and it achieves an important performance gain of up to 6 dB compared to equivalent schemes of the same SE in AWGN and frequency selective channels.

A novel domain for Index Modulation (IM) named “Filter Domain” is proposed. This new domain generalizes many existing modulations and IM domains. In addition, a novel scheme “Filter Shape Index Modulation” (FSIM) is proposed. This FSIM scheme allows a higher Spectral Efficiency (SE) gain than the time and frequency IM dimensions in Single-Input Single-Output (SISO) systems. In the FSIM system, the bit-stream is mapped using an Amplitude Phase Modulation (APM) as QAM or PSK, and an index of a filter-shape changing at the symbol rate. This filter shape, being changed at each symbol, enables a SE gain in SISO system without sacrificing any time or frequency resources. Compared to an equivalent 8QAM and 16QAM schemes and at the same SE, the FSIM with QPSK using 2 and 4 non-optimal filter shapes achieves a gain of 3.8 dB and 1.7 dB respectively at BER= 10-4, and this superiority is maintained in frequency selective fading channel compared to equivalent SISO-IM schemes. A low complexity detection scheme, approaching the maximum likelihood detector performance, is proposed along with a full performance characterization in terms of theoretical probability of filter index error and BER lower bound. Finally, FSIM can achieve better spectral and energy efficiencies when a filter bank and an ISI cancellation technique are optimally designed.

Multiple-Input Multiple-Output (MIMO) technique with Index Modulation (IM) over sub-TeraHertz (sub-THz) bands represent a promising solution to design new wireless ultrahigh data rate systems. However, the system design over sub-THz bands suffers from many technological limitations and severe RF-impairments such as low output power, limited resolution of high-speed low-power Analog-to-Digital Converters and important Phase Noise (PN) introduced by the Local Oscillator (LO). In this paper, different modulations schemes with Generalized Spatial Modulation (GSM) are compared from different perspectives while considering the sub-THz impairments. The effect of PN has been investigated for these modulation schemes in sub-THz channels using uniform linear and rectangular antenna arrays. The obtained results reveal that QPSK-GSM system is the best combination compared to GSM systems with any other Mary modulation scheme (e.g. PSK, DPSK, QAM, PAM). Compared to DQPSK-GSM and 4PAM-GSM at 12bpcu, same number of receive and activated transmit antennas, the QPSK-GSM system offers a gain ranging from 3.4 dB up to 5 dB. The results reveals that low to medium residual PN in distributed oscillator architecture can be tolerated when using GSM-QPSK without phase noise mitigation. Thus, enforcing the GSM to be a promising candidate for ultra-high wireless data rate communication in sub-THz bands.

In this paper, we address multiple-input multiple-output (MIMO) communication technique based on generalized spatial modulation (GSM) and dual-polarized (DP) antennas in sub-TeraHertz (sub-THz) bands to improve the Spectral Efficiency (SE) and to reduce the spatial correlation effect, and the space occupancy. The proposed system adds the polarization dimension to the conventional GSM scheme and enhance the SE. Moreover, the joint Maximum Likelihood (ML) detector and a Modified Ordered Block Minimum Mean-Squared Error (MOB-MMSE) detector algorithm is proposed to detect jointly the complex symbols and the virtual bits conveyed by the activated polarization and the transmit antenna combination index. MOB-MMSE can achieve near-ML performance with low complexity. The performance of DP-GSM system over (un)correlated Rayleigh/Rician fading and sub-THz channels has been studied and the results show that DP-GSM system is robust against channel deficiency such as Rician fading and spatial correlation. Moreover, the Dual polarized Spatial Multiplexing (DP-SMX) and the Uni-Polarized GSM (UP-GSM) are compared with the DP-GSM system. The results reveal that DP-GSM with low order modulation schemes as QPSK outperforms the DP-SMX at high spatial correlations, and thus it is a promising candidate for ultra-high wireless data rates communication in sub-THz band.

Wireless terabit-per-second (Tb/s) links will become an urgent requirement within the next 10 years. However, current methodology for high data rate wireless communication that keep increasing the M-ary modulation schemes and the order of MIMO spatial multiplexing cannot reach Tb/s with a low power consumption. Thus, a new methodology is required with a large bandwidth in the millimeter-wave (mm-Wave) and sub-Terahertz (sub-THz) bands above 90GHz. In addition, it must be able to provide an extremely high spectral efficiency with a low energy consumption. Note that this consumption can be reduced by using constant-envelope modulations such as continuous phase modulation (CPM). However, the CPM has a very low spectral efficiency that limits the desired data rate. This paper suggests a new methodology to reach 1 Tb/s with a low power consumption by using power efficient single carrier with Index Modulation (IM). Simulation results under various uncorrelated/correlated fading channels show that the systems with power efficient modulations as CPM or QPSK can achieve Tb/s with a good performance. Moreover, the link budget and power estimation prove that the constant and near-constant envelope modulations require less than 1-3 Watts for 1 Tb/s with 10-4un-coded BER. Finally, this paper shows that conveying most of the information bits using IM to reach an ultra-high data rate is more power efficient than high order MIMO spatial multiplexing with large M-ary QAM as used in LTE.

In this study, the authors consider the utilisation of multicast technology in cellular networks given different arrival patterns for the content requests of mobile users. Traditionally, the performance evaluation of multicast in the literature usually depends on the adoption of temporal Poisson processes for content requests, which is not accurate any more according to many real data measurements. Therefore, to make use of the bursty nature of content requests, they propose a hybrid unicast/multicast strategy where the base station (BS) can perform the unicast or multicast procedure according to its serving status. By modelling the complete process into a circular Markov chain, they derive the average latency of content requests and the average power consumption of BSs under different arrival patterns and serving configurations in theoretical and/or simulative ways. Moreover, the multicast threshold introduced in their strategy can be dynamically adjusted to achieve a joint optimisation between average latency and power consumption when confronted with varied demands. Numerous results show that the proposed strategy can not only reduce the average latency of content requests but also decrease the average power consumption of BSs, especially under the bursty request arrival patterns.

One of the most challenging issues of Internet of Things (IoT) devices is energy consumption. A massive deployment of connected devices is power hungry. Maximizing the energy efficiency of their batteries reduces the maintenance cost and extends their autonomy and then their utility. To address this issue, this paper proposes the introduction of index modulation on single carrier-frequency division multiple access (SC-FDMA) uplink transmissions for cellular IoT and machine-to-machine (M2M) networks. It is shown that the proposed SC-FDMA with index modulation (SC-FDMA-IM) scheme achieves 50% of energy efficiency increase, while improving the bit error rate performance by up to 3.5 dB of Eb/N0for the same spectral efficiency performance. However peak-to average power ratio (PAPR) performance are decreased, and PAPR reduction techniques have to be used for this scheme.

Narrow Band-Internet of Thing (NB-IoT) is a recently proposed technology by 3GPP in Release-13. It provides low energy consumption and wide coverage in order to meet the requirements of its diverse applications that span social, industrial and environmental aspects. Increasing the number of repetitions of the transmission has been selected as a promising approach to enhance the coverage in NB-IoT up to 164 dB in terms of maximum coupling loss for uplink transmissions, which is a significant improvement compared with legacy LTE technologies, especially to serve users in deep coverage. However, a large number of repetitions reduces the system throughput and increases the energy consumption of the IoT devices, which reduces their battery lifetime and increases their maintenance cost. In this work, we propose a new method for enhancing the NB-IoT coverage based on machine learning algorithms. Instead of employing a random spectrum access procedure, dynamic spectrum access can reduce the number of required repetitions, increase the coverage, and reduce the energy consumption.

In this paper, we propose a new adaptive modulation based on the wavelet packet transform, which targets a good resistance against frequency selective channels while avoiding a large PAPR. Classical multi-carrier modulation schemes divide the channel bandwidth into narrowband sub-channels to improve its robustness against frequency selective fading. However, they suffer from the peak-to-average power ratio (PAPR) problem, which occurs due to a random constructive addition of sub-carriers. By contrast, single carrier modulation schemes, where each transmitted symbol fully occupies the bandwidth, are more sensitive to frequency selective environments and less affected by the PAPR problem. In this paper, we show how the bandwidth division can be reconfigurable and adapted to the channel properties, and we provide several examples to prove that the proposed adaptive modulation represents an alternative modulation which is adjustable between two extreme cases: single carrier modulation and classical multi-carrier modulation.

Power control (PC) and discontinuous transmission (DTx) can reduce the power consumption of a base station (BS). When both are used, there is, for each user, a trade-off between service time and transmit power in order to minimize the energy consumption of the base station. In this paper, we analyse this trade-off and we propose a new efficient algorithm for the computation of the optimal service time and transmit power of all users. We show that in most cases, closed-form expressions can be used. For others, we prove that the search for the optimum can be changed into a root-finding problem which can be solved efficiently with the Newton's method. Numerical results show that, compared to the use of DTx only, the proposed strategy allows to save up to 4% (7W) of the total energy consumption.

This paper analyses a scenario where a Device-To-Device (D2D) pair coexists with an Orthogonal Frequency Division Multiplexing (OFDM) based incumbent network. D2D transmitter communicates in parts of spectrum left free by cellular users, while respecting a given spectral mask. The D2D pair is misaligned in time and frequency with the cellular users. Furthermore, the D2D pair utilizes alternative waveforms to OFDM proposed for 5G. In this study, we show that it is not worth synchronising the D2D pair in time with respect to the cellular users. Indeed, the interference injected into the incumbent network has small variations with respect to time misalignment. We provide interference tables that encompass both time and frequency misalignment. We use them to analyse the maximum rate achievable by the D2D pair when it uses different waveforms. Then, we present numerical results showing what waveform should be utilized by the D2D pair according to the time-frequency resources that are not used by the incumbent network. Our results show that the delay induced by linearly convolved waveforms make them hardly applicable to short time windows, but that they dominate OFDM for long transmissions, mainly in the case where cellular users are very sensitive to interference.

Multicarrier modulation systems suffer from large peak-to-average power ratio (PAPR). Tone reservation is a popular technique for PAPR reduction. It consists in reserving a number of carriers to produce a redundant additive signal which reduces the peak power. There are several schemes to select the reserved carriers. In this paper, we propose a new selection method for adaptive tone reservation. It is showed through simulations that this new proposed selection technique allows 5 dB gain in terms of signal-to- noise ratio for a bit error rate of 10-3, for different constellations, in frequency-selective Rayleigh fading channel.

This paper establishes a necessary condition that must be satisfied by the modulation waveforms of any generalized waveforms for multicarrier (GWMC) system with better peak-to-average power ratio (PAPR) than conventional orthogonal frequency division multiplexing (OFDM). GWMC systems include in particular all classical multicarrier modulation systems. As a consequence, we show that OFDM has the best PAPR performance over all GWMC systems that do not satisfy this necessary condition. We also identify an infinite family of GWMC systems with the same PAPR performance as OFDM. To illustrate our results, we present the simulations of the PAPR behavior for different GWMC systems, including some with better PAPR performance than OFDM.

This paper presents a design of linear-phase, low-complexity, reconfigurable digital filter bank that offers independent and complete control over the bandwidth as well as the center frequency of all subbands. The proposed filter bank is designed by integrating spectral parameter approximation (SPA) technique with the modified coefficient decimation method (MCDM), referred to as SPA-MCDM-FB. The architectural details, design examples and complexity comparisons show that the SPA-MCDM-FB is easy to design and offers substantial savings in gate count, number of variable multipliers and group delay over other filter banks. Moreover, these savings increase further with the increase in the filter-bank resolution (i.e., number of subbands). The SPA-MCDM-FB is then combined with the upper confidence bound (UCB)-based decision-making algorithm to search the vacant band(s) of any desired bandwidth for spectrum-sensing application in cognitive radio (CR). The simulations results verify that the proposed scheme offers superior performance [i.e., improved utilization of vacant subband(s)] and needs fewer gate counts compared to uniform filter bank and UCB-algorithm-based schemes. Furthermore, the functionality and advantages of the SPA-MCDM-FB are also verified for the channelization operation in CR supporting multiple communication standards.

The spatially distributed sparsity of the mobile devices (MDs) in indoor wireless local area networks (WLANs) makes compressive sensing (CS) based localisation algorithms feasible and desirable. In this Letter, the authors exploit the most recent developments in CS to efficiently perform localisation in WLANs and design an accurate indoor localisation scheme by taking advantage of the theory of multi‐task Bayesian CS (MBCS). The proposed scheme assembles the strength measurements of signals from the MDs to distinct access points (APs) and jointly utilises them at a central unit or a specific AP to achieve localisation, thus being able to alleviate the burden of MDs while simultaneously giving a precise estimation of the locations. Afterwards, they give a deeper insight into the localisation problem in more practical scenarios with varying number of MDs and investigate two different adaptive algorithms to meet the satisfactory localisation error requirement. Compared with the conventional MBCS algorithms, simulation results validate that both adaptive algorithms could provide superior localisation accuracy and exhibit stronger resilience to the changes in the number of MDs.

Recent works have validated the possibility of improving energy efficiency in radio access networks (RANs), achieved by dynamically turning on/off some base stations (BSs). In this paper, we extend the research over BS switching operations, which should match up with traffic load variations. Instead of depending on the dynamic traffic loads which are still quite challenging to precisely forecast, we firstly formulate the traffic variations as a Markov decision process. Afterwards, in order to foresightedly minimize the energy consumption of RANs, we design a reinforcement learning framework based BS switching operation scheme. Furthermore, to speed up the ongoing learning process, a transfer actor-critic algorithm (TACT), which utilizes the transferred learning expertise in historical periods or neighboring regions, is proposed and provably converges. In the end, we evaluate our proposed scheme by extensive simulations under various practical configurations and show that the proposed TACT algorithm contributes to a performance jump start and demonstrates the feasibility of significant energy efficiency improvement at the expense of tolerable delay performance.

The cross- and co-tier interference creates the challenges to facilitate the concept of heterogeneous cellular networks (HCNs) in practice. In this paper, we establish a combined learning framework to autonomously mitigate the destructive interference. The macrocell is modeled as the leader and protects itself through pricing the interference from small-cells, which are the followers in the stochastic learning process. During each epoch (an epoch consists of T time slots), the leader commits to a pricing policy by knowing the resource allocation policies of all followers, while the followers compete against each other in each time slot only with the leader's price information. In general, for any two consecutive epochs, the HCN states are highly correlated. The previous policy information can thus be leveraged to improve the learning performance. Numerical results support that the proposed study substantially protects the macrocell and at the same time, optimizes the energy efficiency in small-cells.

Transmitter non-linear components cause distortions when a signal with high Peak to Average Power Ratio (PAPR) is transmitted. High PAPR is a parameter commonly associated to the multi-carrier signals like Orthogonal Frequency Division Multiplexing (OFDM) and Software Radio (SWR). Since SWR is an enabling technology for Cognitive Radio (CR), the signals demonstrate high PAPR in CR context as well. Upon opportunistic spectrum access in CR, PAPR further increases as more carriers (secondary carriers) are added in an already large numbered multi-carrier signal (primary signal). This paper explores the PAPR variations on spectrum access in CR context. Also, the reduction of PAPR in SWR and CR is performed using Tone Reservation (TR). In TR, certain carriers of the data signal are reserved to create a peak reducing signal which on addition to the data signal reduces its peak power. These carriers are called peak reducing carriers (PRC). At first, PAPR is reduced for different SWR signal scenarios. Then the influence of bandwidth, position and power of PRC on he PAPR reduction performance is discussed. Finally, CR PAPR is reduced by presenting a joint pectrum access scheme which implies a part of secondary data carriers as PRC to reduce CR PAPR.

Based on the sparse property of the cyclic autocorrelation in the cyclic frequencies domain, this paper proposes a new blind spectrum sensing method which uses the compressed sensing technique in order to detect free bands in the radio spectrum. This new sensing method that presents a relative low complexity has the particularity to perform blind and robust detection with only few samples (short observation time) and without any knowledge about the cyclic frequency of the signal, in contrary to cyclostationary detection methods that are not robust when the sample size is small and might need some information about the signal in order to detect. ROC curves obtained by simulation show the superiority of the new proposed technique over cyclostationary detection under the same conditions, particularly the same observation time.

In this paper, we consider the problem of exploiting spectrum resources for a secondary user (SU) of a wireless communication network. We suggest that Upper Confidence Bound (UCB) algorithms could be useful to design decision making strategies for SUs to exploit intelligently the spectrum resources based on their past observations. The algorithms use an index that provides an optimistic estimation of the availability of the resources to the SU. The suggestion is supported by some experimental results carried out on a specific dynamic spectrum access (DSA) framework.

Computationally intensive functions in the radio baseband have been typically implemented using dedicated hardware accelerators. The requirement of flexibility and multimode support in emerging communication paradigms has introduced new design challenges for implementing these accelerator cores, which were typically optimized for a single mode of operation. This paper focuses on the design of multimode accelerators for the channelization function in a flexible radio. This work introduces a theoretical framework, to systematically identify commonalities and redundancies in the channelization specification across multiple modes. A novel sample rate conversion ratio factorization strategy is also introduced, that allows a significant portion of the channelization accelerator to be hardwired and reused across multiple modes of operation.

The growing energy footprint and environmental costs of information and communication technologies has created an awareness of the need for greener communications. However, the task of reducing the energy footprint of wireless infrastructure and terminals is daunting due to the requirements of flexibility and reconfigurability in emerging paradigms like 4G. This paper addresses the flexibility and power consumption challenges of channel filtering, which is one of the most computationally intensive kernels in the radio baseband. Power reduction strategies for programmable time-shared filters have been generally focused on the dynamic power, which has been replaced by leakage power as the dominant mode of power consumption in nanoscale CMOS devices. We investigate the role of parallelism in reducing the nanoscale CMOS power consumption. We also propose a class of programmable time-shared filters that are more area efficient than traditional folded direct form filters, when the level of parallelism is increased.

High Peak to Average Power Ratio (PAPR) is a critical issue in multi-standard and multi-carrier communication systems. This problem can result in large performance degradation due to the non-linearity of the High Power Amplifier (HPA) or in low power efficiency. The Cognitive Radio (CR) is an efficient technology to meet the Green communications concept. In this paper, we study the PAPR reduction in the context of amplifying signals of several standards. Also, we propose a scenario allowing an opportunistic spectrum access in the context of Cognitive Radio without degrading the system performance keeping the same Input Back-Off (IBO) and thus the same efficiency of the power amplifier. This scenario uses particular Cognitive Radio (CR) sensors, a Hole Detector sensor and a PAPR sensor. The principle of the proposed method will be described. Also, simulation results based on two Tone Reservation (TR) based PAPR reduction techniques will be given in order to validate the proposed concept.

Orthogonal frequency division multiplexing (OFDM), has recently attracted considerable attention because of its features to combat delay spread or frequency selective fading of wireless or wireline channels. One of the major drawbacks of OFDM is the peak-to-average power ratio (PAPR) which leads to an inefficient use of high power amplifiers (HPA) in communications systems. The authors first briefly review the principle of geometric method (GM) that they previously proposed. This method has a couple of well identified drawbacks as the necessity of adding a radio frequency (RF) filter, the increasing of power amplifier band and the bit error rate degradation if PAPR is largely mitigated. Consequently we propose in this paper a new method to improve GM performance. This method mixes tone reservation (TR) technique and GM called ‘TR-GM’ in order to efficiency reduce the high PAPR of OFDM signals. In addition, the proposed TR-GM technique is compared with TR based on second order cone programming (‘TR-SOCP’) and TR based on the gradient-project (‘TR-GP’) techniques in terms of PAPR reduction, average power variation and complexity. The comparative study has shown that, the proposed TR technique seems to be a good compromise between PAPR reduction, complexity, and average power variation.

This paper presents the ANR project IDROMel, which aims at developing reconfigurable SDR (software defined radio) and cognitive radio (CR) equipments. IDROMel is a 3 years project that started in 2005 and finishes in 2009. The main objective of IDROMel is to define, develop and validate a powerful SDR and CR platform combining very last technology progresses. The platform includes software parts (reconfigurable protocol stacks) and hardware parts (a base band board and a radio frequency front end, RF). Both parts are presented in this paper.

In this paper, Cognitive Radio (CR) is proposed as an efficient technology to meet the Green communications concept. First of all, the concept of "green communications" is extended to the radio communications world. The main topics, described for example in the call for papers of the first Greencom09 Workshop include energy-efficient network, protocols, devices and energy management. But to reduce the global CO2 emission to protect our environment is not the sole way to address this green concept in wireless communications. The proper use and the optimal sharing of spectrum resources is also a very important topic. In this paper the electromagnetic waves can be considered as a pollution for other users and we shall also deal with this problem. Sustainable development should also address the human aspects both from the social and the health point of views. This paper demonstrates that CR may be a very good technology for dealing with the green radio communication, by describing in detail several examples.

Due to the simplest way for PAPR reduction, clipping technique have been proposed and seem to be promising for use in commercial systems. In this paper, the conventional clipping technique is formulated as an adding signal technique for PAPR reduction. We show that, when clipping occurs very rarely, the adding signal for PAPR reduction commonly called ldquopeak-reducing signalrdquo or ldquopeak-cancelling signalrdquo is approximately the distortion term resulting in the nonlinear processing of the OFDM envelope. This result may be extended to all forms of clipping. Later in this paper, the performance of clipping is characterized by deriving an asymptotic PAPR distribution of the clipped signal and by proposing a simple closed form of its signal-to-noise-and-distortion ratio (SNDR) metric. These theoretical results corresponds to a special case of geometric method which is an adding signal technique for PAPR reduction.

In this paper a new equalizer for Single Carrier FDMA (SCFDMA) is described. This signal is currently proposed for mobile radio uplink communications in 3G Long Term Evolution (3G LTE). In this system, equalization is performed thanks to the addition of a Cyclic Prefix (CP), as in OFDM system, and pilots regularly inserted for channel estimation which leads to the usefull throughput degradation. To reduce this degradation a new structure of blind time domain equalizer, shared in two parts, is proposed in this paper : The filtering itself which is a linear time domain filtering performed before any demodulation device in the receiver side, and the MMSE criterion algorithm performed in the time domain after user selection and demodulation. The results are very convincing both in terms of Mean Square Error and in throughput gain compared to the performances of Zero-Forcing technique(ZF) used in literature.

In the Software Radio (SWR) Area, techniques of parameterization are an active research topic. These techniques factorize common functions or operators and in consequence lead to compact though open implementation. However, reconfigurability is often achieved at the cost of additional configuration logic and the benefit of factorization must be carefully analysed. This paper is dedicated to a Reconfigurable Linear Feedback Shift Register (R-LFSR), which can carry out several front rank operations of multi mode transceivers (Pseudo Random Sequence Generators, Scrambling, Convolutive Coding, Cyclic coding, Reed-Solomon Coding or Reed-Solomon decoding). This R-LFSR is then used in the context of a Tri-Standards Transceiver (IEEE 802.11g, IEEE 802.16-2005, 3GPP LTE). Several architectures based on this R-LFSR structure are analysed in terms of complexity in order to select the best implementation trade-off.

This paper introduces a reconfigurable MIMO V-BLAST (vertical Bell Laboratories layered space-time) square root decoder that is CORDIC operators based, allows for dynamically changing the interconnections between the CORDIC (coordinate rotation digital computer) operators. These interconnections of CORDIC operators are implemented in a partial reconfigurable part of FPGA using the dynamic reconfiguration method which improves both the reconfiguration time and the area efficiency. Moreover, this reconfiguration time improvement is increased thanks to the MicroBlaze (within the FPGA) in which is included the reconfiguration management. This MIMO square root decoder is mapped on a Xilinx Virtex-4, showing the configuration time improvement, area efficiency and flexibility of the decoder by using the dynamic partial reconfiguration method.

SoftWare radio (SWR) is an enabling technology for cognitive radio (CR) systems which promises to (de) modulate any signal, at any frequency. SWR signal therefore is composed of different standard's signals, and each standard's signal is either multicarrier or multiplex of single carriers. This combination leads to high temporal fluctuations and thus SWR signal inherits high peak to average power ratio (PAPR) or simply high power ratio (PR). Nonlinear analogue components (amplifiers, converters etc.) cause distortions (in and out of band distortion) for high PR signals which result in system performance degradation. Usually PR problem is addressed in time domain, and here frequency domain interpretation of PR which is more appropriate in SWR context is presented. Gaussian equivalence between SWR signal and orthogonal frequency division multiplexing (OFDM) signal is proved first to accentuate high PR issue in SWR as OFDM suffers the same problem. Then frequency domain interpretation of PR metric is discussed which results in a PR upper bound. This PR upper bound depends only upon spectral values of the signal thus associates spectrum with PR. As a result this bound assists in spectrum access for CR systems by providing PR metric information related to any available bandwidth. Thus bandwidth allocation in a spectrum access scenario under PR constraint is simplified.

In many communication systems, fast and unambiguous carrier phase synchronization is required. When the synchronizer uses a periodic phase detector, it is currently the subject of ambiguous locking. Generally, for fast acquisition systems, the phase ambiguity is removed by the use of differential encoding. However, this results in degraded bit error probability performance. In this paper we introduce and describe an optimized phase detector suited to 16-QAM receivers which prevents ambiguous locking and performs relatively rapid acquisition. Based on a new decision scheme, the proposed phase detector outperforms a classical decision directed phase detector over a Gaussian channel, notably in the presence of frequency offset and even for low signal-to-noise ratios. An analytical analysis of the S-curve of the proposed phase detector is also carried out.

This paper is about the implementation of a MIMO V-BLAST (vertical bell laboratories layered space-time) square root decoder in a FPGA using dynamic partial reconfiguration. The decoder architecture is based on four CORDIC (coordinate rotation digital computer) units. Among these CORDIC units, three are used in rotation mode and the fourth one is used in vectoring mode. The design implementation aims power saving and area efficiency allowing dynamically changing the interconnections between the fixed modules in the reconfigurable modules. This MIMO square root design method shows the configuration time improvement, area efficiency and flexibility of the decoder by using the dynamic partial reconfiguration method.

In this paper, we investigate the complexity of a common FFT-like butterfly capable of carrying out both modular and complex arithmetic operations. This idea of resource sharing stands for software radio systems where re-configurability is of major importance for an optimal multi-standards terminal design. By taking into account, in the implementation on STRATIX II devices, the required number of logic blocks and the total execution time, this re-configurable butterfly can achieve a performance-to-cost ratio gain around 20% over the basic duplicated solution where no re-configuration is considered.

The design of future multi-standard systems still remains a challenge. Current habits are to associate existing separated systems in a device. This implies a duplication of radio systems, which is not economically viable in the long term, for cost, form factor, power consumption, cosmetic, etc. reasons. Flexible architectures exploiting processing commonalities of the different set of standards cohabiting in the device offer promising solutions. An approach for designing flexible multi-standard radio systems is proposed. It consists in exploring the design of multi-standard systems at different levels of granularity and selects the convenient level depending on each designer's needs. It consists first in making a graph description of the multi-standard system to be designed. Then, an architectural exploration (not in the scope of this paper) extracts the operators of a given multi-standard device. These operators are requested to have enhanced reconfiguration capabilities so that a fast reconfiguration is implementable. This paper illustrates our approach with two scenarios of multi-standard radio system designs. Furthermore this paper discusses the scheduling issues related to our design approach.

Abstract We approach the design of multi‐standard reconfigurable radio as a choice between two extremes: (a) installing complex, self‐contained dedicated components that provide high performance at a high cost (‘Velcro approach’), versus (b) supporting all targeted standards through primitive lower level components, which reduces cost but maximises latency. To find the optimal trade‐off between performance and cost, we build a mathematical model, in which we represent the design choices through a graph of progressively simpler functional modules. We illustrate our approach through a simple but realistic design example. Additionally, we show that this optimisation can be reformulated as a version of the well‐known network‐design problem, which opens the door to a wealth of results, algorithms and experience, already available in the scientific literature. We identify some specific algorithms that can help us find the optimal design and discuss limitations and future directions of our research program. Copyright © 2007 John Wiley & Sons, Ltd.

The "software radio (SWR)" concept has become a topic of widespread interest for reconfigurable mobile architecture design. It is seen as the next evolutionary step in the mobile communications. In this context of SWR, a way to decrease the runtime of the software reconfiguration and to optimize the sharing between the software and the hardware of the execution platform called "parametrization" was introduced. This technique is based on two approaches, the first one is called the common function approach, the second one is called the common operator approach. Being interested on the second parametrization technique, we propose in this paper a reconfigurable FFT (fast Fourier transform) operator. This operator can be reconfigured to switch from an operator dedicated to compute the FFT in the complex field (i.e for OFDM modulation or frequential equalization) to an operator which computes the FFT in the Galois field in order to perform Reed-Solomon (RS) encoding and two steps of the decoding process

Large fluctuation of OFDM signal amplitude represents an important problem for amplification in mobile communication systems. In this paper, we propose a new peak-to-average power ratio (PAPR) reduction technique. It is based on the well known clipping and filtering technique. Our technique, called "invertible clipping", is performed thanks to an invertible clipping function. It generates less intermodulation product noise than classical clipping and filtering. Furthermore, since this invertible clipping function could be inverted in reception side, degradations are compensated. The derived method benefits from the advantages (e.g., PAPR reduction) of classical clipping and filtering technique but it exhibits small computational complexity as compared to other peak reduction methods

We provide a procedure for identifying an architecture for a multistandard reconfigurable radio that is optimal in view of cost and performance (latency) considerations. We examine the trade-off between installing complex self-contained components providing high performance at a high cost (as well as size and weight), versus invoking simpler, reusable low level modules, which reduces cost but increases system latency. In the present work, we show that the problem of finding an optimal design for a multistandard reconfigurable radio can be reformulated as a "network design problem". This reformulation provides a wealth of results, algorithms, and experience already available in the scientific literature. We explain the reformulation, give a simple but realistic design example, and discuss some algorithms available in the network design literature

In a paper entitled "Variation on Euclid's Algorithm for Plynomials", Calvez et al. has shown that the extended Euclid's algorithm can be partially obtained by the nonextended one; in fact, it can obtain only two of the three unknowns of the Bezout's theorem. This letter goes further and shows that all polynomials given by the extended Euclid's algorithm and all the intermediate values can be obtained directly by the nonextended Euclid's algorithm. Consequently, only remainder computations are used. Avoiding multiplications and divisions of polynomials decreases the computational complexity. This variation of Calvez et al. justifies the title of the present letter.

A parametric method for estimating the unknown channel impulse response (CIR) in a semi-blind manner is proposed. The main trait of this method is that, instead of seeking the whole CIR sequence, only the unknown time delays and attenuation factors of the physical channel multipath components are estimated. The technique is based on a suitable application of the subchannel response matching (SRM) criterion. The resulting cost function is separable with respect to the two sets of unknown parameters, i.e. time delays and attenuations. Thus, an efficient two step optimization procedure can be applied. The new method offers significant computational savings and a lower mean square estimation error as compared to existing semi-blind channel estimation methods.

An adaptive equalization scheme based on channel estimation is proposed. The structure of the whole scheme is novel as well as some of its most important constituent parts. The equalization part comprises an adaptive decision feedback equalizer (DFE) whose performance is significantly improved due to the information provided by the channel estimation part. To estimate the channel impulse response (CIR) a new adaptive semi-blind scheme based on the sub-channel response matching (SRM) criterion and implemented in the frequency domain has been developed. The equalization part exhibits a much faster convergence rate as compared to the conventional DFE, hence a much shorter training sequence is required. Moreover a significant reduction of the error propagation phenomenon can be achieved. The above advantages are offered with only a slight increase in computational load compared to classical LMS-based DFE.

Two new adaptive equalizers are proposed which belong to the quasi-Newton (QN) algorithmic family. The first algorithm. is a linear equalizer (LE) and the second one is a decision feedback equalizer (DFE). In the LE case, the involved inverse Hessian matrix is approximated by a proper expansion consisting of powers of a Toeplitz matrix. Due to this formulation, the algorithm can be efficiently implemented in the transform domain (TD) using FFT. The same idea is applied to the feedforward part of the DFE. The derived algorithms enjoy the advantages of QN algorithms, that is, they exhibit faster convergence than their stochastic gradient counterparts and less computational complexity as compared to other Newton-type algorithms. These advantages are further enhanced due to TD implementation.

A Markovian model of the error probability density for decision feedback equalizer is proposed and its application to the error propagation probability computation is derived. The model is a generalization of the Lutkemeyer and Noll (see ICC, Porto Carras, Greece, June 1998). It is obtained by the analysis of the Gaussian mixture distribution of the errors which follows a Markov process. The analysis of this process shows that the error propagation probability of the weighted DFE is less than the one of the classical DFE.

A weighted decision feedback equalizer (WDFE) is presented. This DFE does not suffer from the error propagation phenomenon as the classical DFE does. This equalizer employs a device which computes a reliability value (i.e. a probability value for taking the right decision). Two different means which use this value in such a way as not to decide errors in the feedback loop are described. The equalizer has been tested over several channels and convincing performances are presented. In addition, this WDFE offers very good performances in blind mode operation.

A new block adaptive filtering algorithm is derived. The algorithm belongs to the quasi-Newton class of algorithms which are known to have superior convergence properties as compared to gradient algorithms. An important feature of the algorithm is that it lends itself to efficient implementation in the frequency domain. The computational complexity of the frequency domain version of the algorithm is comparable to that of the self-orthogonalizing frequency domain block LMS algorithm while it converges at a faster rate. Depending on the input signal this improvement in performance may be significant in some practical cases.