Theo Kreul

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.

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.

Robust spectrum sensing of DVB-T2 signal using the first preamble symbol

In the research on spectrum sensing, many works focus on TV bands, in which primary user signals follow digital video broadcasting-terrestrial (DVB-T) standard. However, DVB-T2 is the next generation of this standard. Some characteristics of the primary signal are changed including the pilot pattern and the cyclic prefix (CP). This issue results that the existing sensing algorithms based on the characteristics of DVB-T are not suitable for DVB-T2 signal, or become complex. In this paper, we propose a new sensing algorithm for DVB-T2 signal based on the first preamble symbol of DVB-T2 frame. We derive analytical forms for the detection. The detector works well at the SNR of -10dB with the false alarm of 0.01, with very short sensing time (0.224ms) and with all configurations of DVB-T2. Moreover, we propose a sensing scheme based on this algorithm for practical cognitive radio systems.

Massive MIMO exploitation to reduce HARQ delay in wireless communication system

As recommended by 5th generation Public-Private Partnership (5G-PPP) and Next Generation Mobile Networks (NGMN), one of the most important 5G requirements is to minimize the delay within the network for delay-sensitive services. Main objective of this work is to exploit massive MIMO technology to reduce Hybrid Automatic Repeat Query (HARQ) retransmission delay. Massive MIMO indoor environment is created by a 3D ray-tracing tool to simulate the received power, phase, delay, and angle of arrival of each ray in the channel. Two sizes of rectangular antenna array are used to evaluate the performance of beamforming in enhancing the bit error rate. This reflects directly on the mean and maximum numbers of packet retransmission. The angle between user-equipments is considered to evaluate the effect of inter-user interference on HARQ. This work opens the door to develop smarter resource allocation algorithms in 5G for delay-sensitive services based on the location and the angle of arrival of the users.

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.