Doppler Shift Characterization of Wideband Mobile Radio Channels

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Enhanced Channel Estimation Algorithm for Dedicated Short-Range Communication Systems

The Dedicated Short-Range Communication (DSRC) has been widely accepted as a promising wireless technology for enhancing traffic safety. In such DSRC-based vehicle-to-vehicle (V2V) communication systems, because of the extremely time-varying characteristic of wireless propagation channels, accurate channel estimation is essential for reliable information exchange between vehicles. In this paper, the characteristics of the propagation channel and several traditional channel estimation schemes for V2V communications are reviewed. Then, a delay-based channel-frequency-response decomposition scheme is proposed to estimate and predict the double-selective V2V channel while adhering to the IEEE 802.11p standard. The proposed method achieves a more favorable performance than the traditional methods in V2V scenarios by combining the least square estimation in the frequency domain with the linear prediction in time domain. The performance advantages of the proposed scheme are verified by the simulation results from three typical scenarios. Furthermore, a reference design on a field-programmable gate array for the proposed channel estimation scheme is presented for the purpose of demonstrating its implementation feasibility and complexity

Learning to Estimate: A Real-Time Online Learning Framework for MIMO-OFDM Channel Estimation

In this paper we introduce StructNet-CE, a novel real-time online learning framework for MIMO-OFDM channel estimation, which only utilizes over-the-air (OTA) pilot symbols for online training and converges within one OFDM subframe. The design of StructNet-CE leverages the structure information in the MIMO-OFDM system, including the repetitive structure of modulation constellation and the invariant property of symbol classification to inter-stream interference. The embedded structure information enables StructNet-CE to conduct channel estimation with a binary classification task and accurately learn channel coefficients with as few as two pilot OFDM symbols. Experiments show that the channel estimation performance is significantly improved with the incorporation of structure knowledge. StructNet-CE is compatible and readily applicable to current and future wireless networks, demonstrating the effectiveness and importance of combining machine learning techniques with domain knowledge for wireless communication systems

Implicit Channel Learning for Machine Learning Applications in 6G Wireless Networks

peer reviewedWith the deployment of the fifth generation (5G) wireless systems gathering momentum across the world, possible technologies for 6G are under active research discussions. In particular, the role of machine learning (ML) in 6G is expected to enhance and aid emerging applications such as virtual and augmented reality, vehicular autonomy, and computer vision. This will result in large segments of wireless data traffic comprising image, video and speech. The ML algorithms process these for classification/recognition/estimation through the learning models located on cloud servers. This requires wireless transmission of data from edge devices to the cloud server. Channel estimation, handled separately from recognition step, is critical for accurate learning performance. Toward combining the learning for both channel and the ML data, we introduce implicit channel learning to perform the ML tasks without estimating the wireless channel. Here, the ML models are trained with channel-corrupted datasets in place of nominal data. Without channel estimation, the proposed approach exhibits approximately 60% improvement in image and speech classification tasks for diverse scenarios such as millimeter wave and IEEE 802.11p vehicular channels

A New Study of Channel Estimation Methods for OFDM in DVB-T2

In this paper three proposed methods of channel estimation are introduced. These methods are based on pilot-aided OFDM system with the arrangement employed in the DVB-T2 standard in time-varying frequency-selective fading channels. The first and second methods (low complexity and improved low complexity methods, respectively) are modified methods based on Domain Transform Least Square Estimation (DTLSE) method; which reduce the computational complexity by avoiding the use of the matrix inversion. The estimation matrix size for obtaining Channel Impulse Response (CIR) depends only on the length of the channel rather than the number of pilot sub-carriers or the size of OFDM symbols. The third method (high performance method), which is based on the first proposed method and a Two Dimensional Linear Interpolation 2-DIL method, uses one frame instead of one symbol and offers lesser complexity than the MMSE method, and a BER performance close to it

Software defined radio testbed of television white space for video transmission

Recently, television white space (TVWS) has grabbed a lot of attention from researchers in the Cognitive Radio (CR) area. This underutilized spectrum is one of the possible solutions for spectrum scarcity problem in wireless communication. Thus, many research works have been carried out in order to find a suitable method to utilize this spectrum in an efficient manner. Nevertheless, the actual hardware implementation on utilizing this spectrum is still lacking. Therefore, in this research, an Orthogonal Frequency Division Multiplexing (OFDM) real-time video transmission is proposed using software defined radio (SDR) platform. Two modulation schemes are used namely Phase-shift keying (PSK) with its Binary-PSK (BPSK) and Quadrature-PSK (QPSK) and Quadrature amplitude modulation (QAM) with 16QAM and 64QAM modes. The free channel used in this work is selected under ultra high frequency (UHF) band based on the energy detection, which is either on channel 54 or channel 56. The proposed system is developed with the physical (PHY) layer design of the transmitter and receiver in GNU Radio and integration of medium access control (MAC) layer functionality. Video capture and display programs are designed based on OpenCV modules. The performance of this design is evaluated based on two types of environment, indoor and outdoor, with packet delivery ratio (PDR) and end-to-end delay (EED) as the performance metrics. Three types of video motion are used in the experimentation which are fast (mobile), medium (foreman) and slow (akiyo). Under allocated bandwidth of 1.0 MHz, optimal performances of PDR and EED for both scenarios are shown. In the indoor scenario, QPSK½ exhibits the best performance with 0.92 of PDR and 24.7 seconds of EED for akiyo. Meanwhile for foreman and mobile, BPSK¾ achieves the best performance with PDR of 0.96 and 0.95 and EED of 33.2 seconds and 35.0 seconds, respectively. In the outdoor scenario, the best performance of PDR is achieved by 16QAM½ with 0.9 and 23.5 seconds of EED for akiyo. For foreman and mobile, QPSK½ exhibits the best performance with 0.94 and 0.9 of PDR and 31.2 seconds and 32.5 seconds of EED, respectively. In conclusion, the proposed design exhibits promising solutions for the OFDM real-time video transmission over TVWS

Caracterización de la respuesta en fase y compensación de fase en sistemas multiportadora para canales con respuesta en frecuencia no uniforme

This work proposes a methodology for the phase estimation in sub-bands of a non-uniform response channel. The novelty of this proposal lies in the use of a modulation format in QSPK (Quadrature Phase Shift Keying) quadrature-phase modified as a test signal for the phase estimation that eliminates the ambiguity issue. The methodology here proposed is verified experimentally using a defective RF cable as transmission channel andthus achieving data transmission rates of 20 Kbaud in a 120 cm distance in a frequency band between the 50 kHz y 276 kHz.En este trabajo se propone una metodología de estimación de fase por subbandas de un canal de respuesta no uniforme. La novedad de la propuesta radica en la utilización de un formato de modulación en fase en cuadratura QPSK, (Quadrature Phase Shift Keying) modificado como señal de prueba para la estimación de fase que elimina el problema de la ambigüedad. La metodología propuesta se verifica experimentalmente utilizando como canal de transmisión un cable de RF defectuoso, logrando la transmisión de datos a tasas de 20 Kbaud en una distancia de 120 cm en una banda de frecuencias comprendida entre los 150 kHz y 276 kHz

Channel estimation and tracking algorithms for vehicle to vehicle communications

The vehicle-to-vehicle (V2V) communications channels are highly time-varying, making reliable communication difficult. This problem is particularly challenging because the standard of the V2V communications (IEEE 802.11p standard) is based on the WLAN IEEE 802.11a standard, which was designed for indoor, relatively stationary channels; so the IEEE 802.11p standard is not customized for outdo or, highly mobile non-stationary channels. In this thesis,We propose Channel estimation and tracking algorithms that are suitable for highly-time varying channels. The proposed algorithms utilize the finite alphabet property of the transmitted symbol, time domain truncation, decision-directed as well as pilot information. The proposed algorithm s improve the overall system performance in terms of bit error rates, enabling the system to achieve higher data rates and larger packet lengths at high relative velocities. Simulation results show that the proposed algorithms achieve improved performance for all the V2V channel models with different velocities, and for different modulation schemes and packet sizes as compared to the conventional least squares and other previously proposed channel estimation techniques for V2V channels