Trung Thanh Nguyen

Key issues towards beyond LTE-Advanced systems with cognitive radio

In this paper, we give an introductory presentation on the state of the art of the key technologies in the field of cognitive radio, including spectrum awareness, cognitive engine, location awareness, digital front-end and baseband spectral shaping. The technical feasibility of opportunistically operating the future evolution of long-term evolution (LTE) over cognitive white spaces is discussed. A platform implementing these new concepts is briefly introduced.

Spectrum awareness scheme of the rapidly deployable eNodeB for unexpected and temporary events

In the EU FP7 ICT project ABSOLUTE, a novel network architecture based on the LTE-A aerial and terrestrial rapidly deployable eNodeB (RD-eNodeB) systems has been proposed for emergency communications in unexpected and temporary events. These systems would experience complex spectrum environment with multiple unknown coexisting cellular networks, which needs to be quickly adapted with cognitive radio techniques for rapid deployment. To this end, this paper proposes a spectrum awareness scheme considering initial spectrum sensing on RD-eNodeB, sensing using UEs measurement capability and the radio environment map (REM) during the roll-out and in-service phases of the systems operation. For the initial spectrum sensing, a novel scheme for detecting, classifying and measuring downlink signals from coexisting base stations with different radio access technologies (RATs) is presented, which is invulnerable to the noise uncertainty problem. Encouraging numerical results of effectively detecting and classifying coexisting UMTS signal and LTE signals with different physical layer identities have been obtained via simulation.

A multi-channel spectrum sensing scheme with filter bank realization for LTE signals

In cognitive ratio (CR), spectrum sensing is a crucial technique aiming at exploiting spectrum white spaces. This sensing task is more difficult for multiple channels in wide bands. In this paper, we investigate spectrum sensing tasks for long-term evolution (LTE) networks in large frequency-bands. We propose an effective spectrum sensing scheme to detect LTE signals and classify the cell-identities transmitted in multi-channels in parallel. To prove the concept and validate the performance of the proposed scheme, a secondary LTE transmission in TV bands is modeled in our simulations. At the perspective of realistic scenarios, the identified information could be utilized for some functions such as the co-ordination among secondary networks or initial-cell-search procedures between secondary user-equipments and their serving base-stations in the secondary LTE transmission. The simulation results show that the detection and classification performance of the proposed scheme is close tightly to that in the case of a single channel. The scheme works well in multi-path fading environment with carrier frequency offset (CFO) and is tolerant to noise uncertainty.

An enhanced spectrum sensing algorithm with maximum ratio combination of spectral correlation

In cognitive radio networks, the task of spectrum sensing is required to be reliable at low signal-to-noise ratios (SNRs). Spectral correlation is an effective approach to satisfy the requirement. The algorithms based on statistic spectral correlation profiles are a good method as shown in some previous works. In this paper, we propose an algorithm with maximum ratio combination for the profiles to enhance the method. We construct a formula of statistic test and describe an implementation for our algorithm in practice. Extensive simulations are carried out to verify the performance of algorithms. As a result, the proposed algorithm outperforms the existing algorithms with a neglectful cost of additional complexity.

Cyclic prefix-based noise estimation with DVB-T input for spectrum sensing in cognitive radio

The existing blind noise estimation called cyclic prefix based noise estimation without knowledge of a priori signal is simulated along with input of DVB-T and the multipath channel ITU-T pedestrian model A. The simulation is done by means to know NMSE and noise uncertainty over time observation with varied SNR. The NMSE shows a very good result and close to the result of the previous research. The corresponding noise uncertainty is simulated in order to observe the performance of detection of spectrum sensing. It has the result that such limitation of detection called SNR wall will not occur. Based on the research, the estimator is expected to be applied along with spectrum sensing in cognitive radio network.

Noise power estimation with DVB-T input for spectrum sensing in cognitive radio network

Noise estimation is an essential issue on the wireless communication system. Cognitive radio network uses the spectrum sensing to detect opportunistically the unoccupied spectrum holes and the licensed user. Several methods of spectrum sensing need the knowledge of noise power in advance. In this paper, we proposed noise power estimation that suitable for the condition of cognitive radio. The estimator does not need any a priori information about the signal. The simulation is done with the input of Digital Video Broadcasting - Terrestrial (DVBT) signal which passes through AWGN channel in two condition, ideal and real condition. The performances are given in normalized mean-square-error (NMSE) and noise uncertainty. It is shown a low value of NMSE. The estimator with DVB-T input also works well at low SNR and avoid SNR wall phenomenon.

Experiments on spectrum sensing algorithms of pilot-added OFDM signals with a cognitive LTE-A system

The reliability of spectrum sensing is a challenging issue in cognitive radio (CR) systems. In this paper, we validate the reliability of two spectrum sensing algorithms for pilot-added OFDM signals: time-domain symbol cross-correlation (TDSC) and periodical peaks of autocorrelation (PPA) with a real system in real environments. To validate, these two algorithms carry out detection function for real signals captured by a test-bed of cognitive Long Term Evolution Advanced (LTE-A) systems. Moreover, we use a transmission between a vector generator and a spectrum analyzer to cross-check with results by the test-bed. The experimental results agree with each other and with simulated results in previous works. Two algorithms work well in real-environments and are insensitive to noise-uncertainty. The results show that PPA algorithms outperform TDSC algorithms by 1 dB - 2.5 dB with the observation durations in experiments. Additionally, PPA algorithms are suitable for short observations. For example, PPA algorithms can work with a 5 ms duration of 8K mode Digital Video Broadcasting Terrestrial (DVB-T) signals, but TDSC algorithms cannot. The results also show the performance of TDSC and PPA algorithms by a test-bed of cognitive LTE-A systems. They give clues to apply suitable algorithms for different operations such as in-band and out-band sensing modes in cognitive cellular systems.

Experiments on multi-channel spectrum sensing with filter bank realization for cognitive LTE-A systems

Wideband spectrum sensing is an attractive topic in cognitive radio (CR). Filter-banks are a good approach for wideband sensing with different detection algorithms. A wideband sensing scheme with filter-bank realization was proposed as in [1] for long-term evolution advanced (LTE-A) signals. The scheme is able to detect and classify LTE-A signals in multi-channels in parallel. In this work, we validate the reliability of the scheme in realistic scenarios of mobile communications. Real wideband LTE signals are processed by the scheme with an integrated test-bed for LTE base-stations in emergency situations. The experimental results agree with previous works to approve the reliability of the spectrum sensing scheme. Besides, they lead a successful integration approach of the scheme into LTE base-stations.

Joint MAC and routing protocol for OFDMA-based adhoc networks

In this paper, a dynamic Sub-channel Assignment Algorithm (DSA) based on orthogonal frequency division multiple access (OFDMA) technology operating in time division duplexing (TDD) and a new routing protocol are proposed. The proposed dynamic Sub-channel Assignment Algorithm solves several drawbacks of existing radio resource allocation techniques in OFDM system used in ad-hoc and multi-hop networks, such as the hidden and exposed node problem, mobility, co-channels interference in frequency (CCI). The proposed routing protocol is jointed with the MAC protocol based the algorithm to ensure the mobility and multi-hop, thus the quality of service in ad-hoc and multi-hop networks is significantly improved.