No abstract

WiFi backscatter communication has emerged as a promising enabler of ultralow-power connectivity for Internet of things, wireless sensor network and smart energy. In this paper, we propose a multi-filter design for effective decoding of WiFi backscattered signals. Backscattered signals are relatively weak compared to carrier WiFi signals and therefore require algorithms that filter out original WiFi signals without affecting the backscattered signals. Two multi-filter designs for WiFi backscatter decoding are presented: the summation and delimiter approaches. Both implementations employ the use of additional filters with different window sizes to efficiently cut off undesired noise/interference, thus enhancing frame detection and decoding performance, and can be coupled with a wide range of decoding algorithms. The designs are particularly productive in the frequency-shift WiFi backscatter communication. We demonstrate via prototyping and testbed experiments that the proposed design enhances the performance of various decoding algorithms in real environments.

In WiFi backscatter communication, the frequency shift technique allows a backscattered signal to appear not in the frequency channel of the carrier signal but in adjacent ones, thus avoiding noisy OFDM-based carrier signals and increasing the communication range. Through testbed experiments, we observe that frequency shift is effective in mitigating the impact of the inherent fluctuation of WiFi signals, particularly in bistate backscatter communication; however, due to the weak strength of the backscattered signal, other signals from incumbent transmitters may appear in the shifted frequency channels, significantly interfering with the backscattered signal. To combat this challenge in a way that is nondisruptive to incumbent transmitters, we propose a receiver-side spectro-temporal combining scheme in which spectrum combining is performed to suppress interference appearing in one of the shifted channels, while temporal combining is performed with transmission repetitions to suppress bit errors resulting from residual interference. The scheme's on-the-fly spectrum combining and bit-sequence temporal combining require minimal buffer memory. Through system prototyping and testbed experiments, we demonstrate that the proposed scheme outperforms the conventional and temporal-combining-only cases in terms of the bit error rate and throughput under various conditions.

In this paper, we propose an algorithm of angular mode selection for high-performance HEVC intra prediction. HEVC intra prediction is used to remove the spatial redundancy. Intra prediction has a total of 35 modes and block size of 64x64 to 4x4. Intra prediction has a high amount of calculation and operational time due to performing all 35 modes for each block size for the best cost. The angular mode algorithm proposed has a simple difference between pixels of the original image and the selected angular mode. A decision is made to select one angular mode plus planar mode and DC mode to perform the intra prediction and determine the mode with the best cost. In effect, only three modes are executed compared to the traditional 35 modes. Performance evaluation index used are BDPSNR and BDBitrate. For the proposed algorithm, BDPSNR results averagely increased by 0.035 and BDBitrate decreased by 0.623 relative to the HM-16.9 intra prediction. In addition, the encoding time is decreased by about 6.905%.