In many radio frequency identification (RFID) applications, the reader identifies the tags in its scope repeatedly. For these applications, many algorithms, such as an adaptive binary splitting algorithm (ABS), a single resolution blocking ABS (SRB), a pair resolution blocking ABS (PRB) and a dynamic blocking ABS (DBA) have been proposed. All these algorithms require the staying tags to reply with their IDs to be recognized by the reader. However, the IDs of the staying tags are stored in the reader in the last identification round. The reader can verify the existence of these tags when identifying them. Thus, we propose an anti-collision algorithm with short reply for RFID tag identification (ACSR). In ACSR, each staying tag emits a short reply to indicate its continued existence. Therefore, the data amount transmitted by staying tags is reduced significantly. The identification rate of ACSR is analyzed in this paper. Finally, simulation and analysis results show that ACSR greatly outperforms ABS, SRB and DBA in terms of the identification rate and average amount of data transmitted by a tag.

The low complexity tree-structure based user scheduling algorithm is extended into up-link MLD-based multi-user multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing access (OFDMA) wireless systems. The system sum capacity is maximized by careful user selection on a defined tree structure. The calculation load is reduced by selecting the M most possible best branches and sampling in frequency dimension. The performances of the proposed scheduling algorithm are analyzed within three kinds of OFDMA systems and compared with conventional throughput-based algorithm. Both the theoretical analysis and simulation results show that the proposed algorithm obtains better performance with much low complexity.

Radio Frequency based Device-Free Localization (RFDFL) is an emerging localization technique without requirements of attaching any electronic device to a target. The target can be localized by means of measuring the shadowing of received signal strength caused by the target. However, the accuracy of RFDFL deteriorates seriously in environment with WiFi interference. State-of-the-art methods do not efficiently solve this problem. In this paper, we propose a dual-band method to improve the accuracy of RFDFL in environment without/with severe WiFi interference. We introduce an algorithm of fusing dual-band images in order to obtain an enhanced image inferring more precise location and propose a timestamp-based synchronization method to associate the dual-band images to ensure their one-one correspondence. With real-world experiments, we show that our method outperforms traditional single-band localization methods and improves the localization accuracy by up to 40.4% in real indoor environment with high WiFi interference.

In recent years, blockchain has been widely applied in the Internet of Things (IoT). Blockchain oracle, as a bridge for data communication between blockchain and off-chain, has also received significant attention. However, the numerous and heterogeneous devices in the IoT pose great challenges to the efficiency and security of data acquisition for oracles. We find that the matching relationship between data sources and oracle nodes greatly affects the efficiency and service quality of the entire oracle system. To address these issues, this paper proposes a distributed and efficient oracle solution tailored for the IoT, enabling fast acquisition of real-time off-chain data. Specifically, we first design a distributed oracle architecture that combines both Trusted Execution Environment (TEE) devices and ordinary devices to improve system scalability, considering the heterogeneity of IoT devices. Secondly, based on the trusted node information provided by TEE, we determine the matching relationship between nodes and data sources, assigning appropriate nodes for tasks to enhance system efficiency. Through simulation experiments, our proposed solution has been shown to effectively improve the efficiency and service quality of the system, reducing the average response time by approximately 9.92% compared to conventional approaches.

In this study, we propose a one dimensional (1D) based successive generalized sidelobe canceller (GSC) structure for the implementation of 2D adaptive beamformers using a uniform rectangular antenna array (URA). The proposed approach takes advantage of the URA feature that the 2D spatial signature of the receive signal can be decomposed into an outer product of two 1D spatial signatures. The 1D spatial signatures lie in the column and the row spaces of the receive signal matrix, respectively. It follows that the interferers can be successively eliminated by two rounds of 1D-based GSC structure. As compared to the conventional 2D-GSC structure, computer simulations show that in addition to having significantly low computational complexity, the proposed adaptive approach possesses higher convergence rate.

Orthogonal frequency division multiplexing (OFDM) is very sensitive to the frequency errors caused by phase noise and Doppler shift. These errors will disturb the orthogonality among subcarriers and cause intercarrier interference (ICI). A simple method to combat ICI is proposed in this letter. The main idea is to map each data symbol onto a couple of subcarriers rather to a single subcarrier. Different from the conventional adjacent coupling and symmetric coupling methods, the frequency diversity can be utilized more efficiently by the proposed adaptive coupling method based on optimal subcarrier spacing. Numerical results show that our proposed method provides a robust signal-to-noise ratio (SNR) improvement over the conventional coupling methods.

Coupled with the discrete wavelet transform, SPIHT (set partitioning in hierarchical trees) is a highly efficient image compression technique that allows for progressive transmission. One problem, however, is that its decoding can be extremely sensitive to bit errors in the code sequence. In this paper, we address the issue of transmitting SPIHT-encoded images via noisy channels, wherein errors are inevitable. The communication scenario assumed in this paper is that the transmitter cannot get any acknowledgement from the receiver. In our scheme, the original SPIHT code sequence is first segmented into packets. Each packet is classified as either a CP (critical packet) or an RP (refinement packet). For error control, cyclic redundancy check (CRC) is incorporated into each packet. By checking the CRC check sum, the receiver is able to tell whether a packet is correctly received or not. In this way, the noisy channel can be effectively modeled as an erasure channel. For unequal error protection (UEP), each of those packets are repeatedly transmitted for a few times, as determined by a process called diversity allocation (DA). Two DA algorithms are proposed. The first algorithm produces a nearly optimal decoded image (as measured in the expected signal-to-noise ratio). However, its computation cost is extremely high. The second algorithm works in a progressive fashion and is naturally compatible with progressive transmission. Its computation complexity is extremely low. Nonetheless, its decoded image is nearly as good. Experimental results show that the proposed scheme significantly improves the decoded images. They also show that making distinction between CP and RP results in wiser diversity allocation to packets and thus produces higher quality in the decoded images.

In this paper, we present a new approach for the design of partially adaptive broadband beamformers with the generalized sidelobe canceller (GSC) as an underlying structure. The approach designs the blocking matrix involved by utilizing a set of P-regular, M-band wavelet filters, whose vanishing moment property is shown to meet the requirement of a blocking matrix in the GSC structure. Furthermore, basing on the subband decomposition property of these wavelet filters, we introduce a new dynamic subband selection scheme succeeding the blocking matrix. The scheme only retains the principal subband components of the blocking matrix outputs based on a prescribed statistical hypothesis test and thus further reduces the dimension of weights in adaptive processing. As such, the overall computational complexity, which is mainly dictated by the dimension of adaptive weights, is substantially reduced. The furnished simulations show that this new approach offers comparable performance as the existing fully adaptive beamformers but with reduced computations.