Amor Nafkha

A FPGA partial reconfiguration design approach for cognitive radio based on NoC architecture

A cognitive radio is the final point of software-defined radio platform evolution : a fully reconfigurable radio that changes its communication modules depending on network and/or user demands. His definition on reconfigurability is very broad and we only focus on the heterogeneous reconfigurable hardware platform for cognitive radio. software defined radio (SDR) basically refers to a set of techniques that permit the reconfiguration of a communication system without the need to change any hardware system element. The goal of Software Defined Radio is to produce communication devices which can support several different services. These terminals must adapt their hardware structure in function of the wireless networks such as GSM, UMTS, wireless LAN standards like IEEE 802.11a/b/g As a consequence, NoC offer good perspectives to future SoC in the way to satisfy SDR concept. Conception, validation and evaluation of solutions for NoC design (mapping of cores, topology, FIFO and link sizes) is conducted through simulations. We are proposing to extend the NoC structure to a FPGA where PR (Partial Reconfiguration) is used to dynamically reconfigure the requested IP block of the telecommunication chain. This work is part of our contribution for E2RII project and IDROMEL project.

New OPBHWICAP Interface for Realtime Partial Reconfiguration of FPGA

We propose in this paper, a timing analysis of dynamic partial reconfiguration (PR) applied to a NoC (Network on Chip) structure inside a FPGA. In the context of a SDR (Software Defined Radio) example, PR is used to dynamically reconfigure a baseband processing block of a 4G telecommunication chain running in real-time (data rates up to 100 Mbps). The results presented show the validity of our methodology for PR management regarding the timing performances obtained in a real implementation. PR timing is a key point to make SDR approach realistic. These results show that using PR, FPGAs combine the flexibility of SW (software) and the processing power of HW (hardware). This makes PR a tremendous enabling technology for SDR. These results are based on a new IP managing the ICAP component that allows a gain in time of a rate of 124 comparing to the provided OPBHWICAP. Moreover, we have integrated a methodology which can reduce significantly the bitstream size and consequently the reconfiguration duration. The results presented in this paper show that PR reconfiguration time can go downto a few tens of microseconds. This makes PR really attractive for SDR design or any other highly demanding real-time applications.

Hybrid Spectrum Sensing Architecture for Cognitive Radio Equipment

Spectrum sensing is the key function in implementing cognitive radio, which enables secondary users to identify and utilize vacant spectrum resource allocated to primary users. Recent studies have proposed four major sensing methods, including matched filter, energy, feature, and eigenvalue-based detectors. However, there are some drawbacks along with them. In this paper, we propose a hybrid architecture, associating energy and cyclostationary detectors, for spectrum sensing that improves the ability of conventional energy detector to detect the primary user in the presence of noise uncertainty. In a constant noise environment, the performance of the proposed detector approaches that of an ideal radiometer.

Blind spectrum sensing using symmetry property of cyclic autocorrelation function: from theory to practice

Spectrum sensing has been identified as the key step of the cognition cycle and the most important function for the establishment of cognitive radio. In this paper, a blind cyclostationary feature detector, which is based on the symmetry property of cyclic autocorrelation function (SP-CAF), is implemented and tested using universal software radio peripheral platform and GNU Radio open-source software development toolkit. Performance of the SP-CAF is compared to the classical energy detector via various tests conducted in real scenarios where both detection algorithms are employed to blindly sense the spectrum for opportunistic access. This study shows that the blind cyclostationary feature detector outperforms the classical energy detector while guaranteeing acceptable complexity and low sensing time. Moreover, different experimental results indicate that the blind sensing detector can achieve high detection probability at a low false alarm probability under real channel conditions and low signal-to-noise ratio.

Blind Spectrum Detector for Cognitive Radio Using Compressed Sensing

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.

Open Platform for Prototyping of Advanced Software Defined Radio and Cognitive Radio Techniques

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.)

Accurate measurement of power consumption overhead during FPGA dynamic partial reconfiguration.

In the context of embedded systems design, two important challenges are still under investigation. First, improve real-time data processing, reconfigurability, scalability, and self-adjusting capabilities of hardware components. Second, reduce power consumption through low-power design techniques as clock gating, logic gating, and dynamic partial reconfiguration (DPR) capabilities. Today, several application, e.g., cryptography, Software-defined radio or aerospace missions exploit the benefits of DPR of programmable logic devices. The DPR allows well defined reconfigurable FPGA region to be modified during runtime. However, it introduces an overhead in term of power consumption and time during the reconfiguration phase. In this paper, we present an investigation of power consumption overhead of the DPR process using a high-speed digital oscilloscope and the shunt resistor method. Results in terms of reconfiguration time and power consumption overhead for Virtex 5 FPGAs are shown.

Blind standard identification with bandwidth shape and GI recognition using USRP platforms and SDR4all tools

In this paper, focusing on identifying standards blindly, we propose a bandwidth shape sensor and a GI (guard interval) sensor using USRP (Universal Software Radio Peripheral) platforms and SDR4all tools. These sensors are fundamental parts of the so-called Blind Standard Recognition Sensor. The blind standard bandwidth sensor is based on a Radial Basis Function Neuronal Network designed in Matlab. We have presented first experience of using blind standard bandwidth sensor in a previous work. We will provide in this paper further details on the results of this sensor (simulations, preliminary implementations and validations). The GI sensor is implemented in order to improve the detection performance in the case of two identical bandwidth shapes. The SDR4all driver offers a simple yet efficient interface between the Matlab signal processing codes and the USRP transmitting and receiving platforms. These simple and easily accessible software defined radio tools were used to design and implement two sensors. The inducted simulations and experiments show that the designed system is indeed able to discriminate three standard-like spectrums (e.g., GSM-like, UMTS-like and OFDM-like) under simple yet real transmission conditions using their different bandwidth shapes and to identify a GI-OFDM-like system using cyclic autocorrelation method.

Complexity Gain of QR Decomposition Based Sphere Decoder in LTE Receivers

It has been widely shown that the Sphere Decoding can be used to find the Maximum Likelihood (ML) solution with an expected complexity that is roughly cubic in the dimensions of the problem. However, the computational complexity becomes prohibitive if the Signal-to-Noise Ratio is too low and/or if the dimension of the problem is too large. That is why another technique denoted as Fixed-complexity Sphere Decoder (FSD) is an interesting approach. This algorithm needs a preprocessing step, and in this paper the QR-Decomposition-based prepro- cessing technique, which is not inconsequential, will be studied. Two different techniques are exposed, including the classical Gram Schmidt orthonormalization process. Their computational complexities and their impacts on the FSD computational com- plexity are studied. In the LTE context, the overall computational complexities of the two detection techniques are quantified and are shown to be dependent on the constellation size. Index Terms—MIMO detection, Sphere Decoder, QR Decom- position, Householder, LTE.

Enhanced hybrid spectrum sensing architecture for cognitive radio equipment

Spectrum sensing is an important process in cognitive communication and must be performed accurately. In this paper we propose a low complexity detector based on a combination of two well-known and complementary spectrum sensing methods: energy and cyclostationary detection. The cyclostationary detector is used to estimate the noise level N0, which is then used to fix the threshold of the energy detector. Simulation results show promising performances of the proposed detector in low Signal to Noise Ratio (SNR).