# Symbol-Level Selective Channel Estimation in Packet-Based OFDM Systems
## 1 Introduction  
Cooperative intelligent transportation systems (C-ITS) have been developed to provide various traffic services such as road safety, route planning, and congestion avoidance [1; 2; 3]. C-ITS is expected to increase traffic efficiency and safety by enabling traffic participants such as vehicles and roadside infrastructures to exchange their information [4]. Wireless communications are perceived as an enabler for high-performance C-ITS applications. Therefore, vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications are key technologies for enabling C-ITSs [5; 6]. In particular, wireless access in vehicular environments (WAVE) was designed as a radio communication system for V2V and V2I communications [7; 8; 9]. In WAVE, the physical (PHY) and medium access control layers are defined by using the IEEE 802.11p and IEEE 802.11p/IEEE 1609.4 standards, respectively [10; 11]. C-ITS systems provide safety services for drivers whereby the vehicles periodically transmit a broadcast message containing status information such as their location and speed. In terms of safety services (e.g., cooperative forward collision warning), safety applications can help avoid dangerous road conditions by assisting the driver with the gathered information and sensing problems early enough for the driver to respond [12]. To realize these services, accurate information exchange must be performed, and the reliability of vehicular communications is one of the most important factors. Therefore, robust channel estimation is needed to improve reliability in vehicular environments, and this affects overall system performance. In high-speed vehicular environments, wireless channels exhibit high Doppler shifts and large delay spreads. Consequently, the channels have both time- and frequency-selective fading owing to motion and multipath components [13; 14; 15]. The channel conditions vary rapidly and affect the transmitted packet; thus, the channel coefficient can change significantly from the start to the end of the packet. To adapt to these rapid channel variations, IEEE 802.11p/WAVE employs four pilot subcarriers among 48 data subcarriers in a packet. However, these pilot subcarriers are not sufficient for estimating channel variations in the frequency domain owing to large delay spreads; consequently, performance degradation occurs in communication systems. Therefore, the accuracy of channel estimation has a significant effect on system performance, and numerous channel estimation schemes complying with the IEEE 802.11p standard have been proposed to adapt to fast-varying channels [16; 17; 18; 19; 20; 21]. A good survey and review of other schemes can be found in [21]. The spectral temporal averaging (STA) [16] scheme can demonstrate better error performance at low signal-to-noise ratios (SNRs), but an error floor occurs at high SNRs. The time-domain reliable test frequency domain interpolation (TRFI) scheme [17] improves the channel estimation performance using the time-frequency correlation properties, but it cannot achieve satisfactory performance at low SNRs. In [18], the decision-directed estimation with time-domain truncation (DD-TT) channel estimation scheme was proposed; however, performance degradation occurs at high SNRs. In [19], channel estimation using frequency self-organization was proposed to improve error performance. This method needs a decoder and encoder chain equal to the number of symbols in the packet to obtain the channel estimate, resulting in high computational complexity and delay. In [20], the packet-level selective (PLS) scheme, which selects the better channel estimation scheme on a packet-by-packet basis, was proposed by our researchers to achieve outstanding performance over the entire SNR region. However, as this technique uses long preambles only once at the start of the packet to determine the better channel estimation technique, the PLS scheme has difficulty in accurately tracking channel variations that occur along the packet over time.