Distributed Sequential Detection for Cooperative Spectrum Sensing in Cognitive Internet of Things.

The rapid development of wireless communication technology has led to an increasing number of internet of thing (IoT) devices, and the demand for spectrum for these devices and their related applications is also increasing. However, spectrum scarcity has become an increasingly serious problem. Therefore, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources so that IoT devices can access them and, meanwhile, avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of sensing the PUs signal in IoT devices, the issue of sensing time and decision cost (the cost of determining whether the signal state of the PU is correct or incorrect) arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the sensing time and cost functions for IoT devices and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal sensing time problem as a finite horizon problem and solve the threshold of the optimal decision rule by person-by-person optimization (PBPO) methodology and dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various costs of each observation taken and thresholds.

Efficient and Low-Complex Signal Detection with Iterative Feedback in Wireless MIMO-OFDM Systems.

To solve error propagation and exorbitant computational complexity of signal detection in wireless multiple-input multiple-output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, a low-complex and efficient signal detection with iterative feedback is proposed via a constellation point feedback optimization of minimum mean square error-ordered successive interference cancellation (MMSE-OSIC) to approach the optimal detection. The candidate vectors are formed by selecting the candidate constellation points. Additionally, the vector most approaching received signals is chosen by the maximum likelihood (ML) criterion in formed candidate vectors to reduce the error propagation by previous erroneous decision, thus improving the detection performance. Under a large number of matrix inversion operations in the above iterative MMSE process, effective and fast signal detection is hard to be achieved. Then, a symmetric successive relaxation iterative algorithm is proposed to avoid the complex matrix inversion calculation process. The relaxation factor and initial iteration value are reasonably configured with low computational complexity to achieve good detection close to that of the MMSE with fewer iterations. Simultaneously, the error diffusion and complexity accumulation caused by the successive detection of the subsequent OSIC scheme are also improved. In addition, a method via a parallel coarse and fine detection deals with several layers to both reduce iterations and improve performance. Therefore, the proposed scheme significantly promotes the MIMO-OFDM performance and thus plays an irreplaceable role in the future sixth generation (6G) mobile communications and wireless sensor networks, and so on.

Improved Frequency Domain Turbo Equalization with Expectation Propagation Interference Cancellation in Underwater Acoustic Communications.

This paper proposes an improved frequency domain turbo equalization (IFDTE) with iterative channel estimation and feedback to achieve both a good performance and low complexity in underwater acoustic communications (UWACs). A selective zero-attracting (SZA) improved proportionate normal least mean square (SZA-IPNLMS) algorithm is adopted by utilizing the sparsity of the UWAC channel to estimate it using a training sequence. Simultaneously, a set-membership (SM) SZA differential IPNLMS (SM SZA-DIPNLMS) with variable step size is adopted to estimate the channel status information (CSI) in the iterative channel estimation with soft feedback. In this way, the computational complexity for iterative channel estimation is reduced effectively with minimal performance loss. Different from traditional schemes in UWACs, an IFDTE with expectation propagation (EP) interference cancellation is adopted to estimate the a posteriori probability of transmitted symbols iteratively. A bidirectional IFDTE with the EP interference cancellation is proposed to further accelerate the convergence. THe simulation results show that the proposed channel estimation obtains 1.9 and 0.5 dB performance gains, when compared with those of the IPNLMS and the l0-IPNLMS at a bit error rate (BER) of 10-3. The proposed channel estimation also effectively reduces the unnecessary updating of the coefficients of the UWAC channel. Compared with traditional time-domain turbo equalization and FDTE in UWACs, the IFDTE obtains 0.5 and 1 dB gains in the environment of SPACE'08 and it obtains 0.5 and 0.4 dB gains in the environment of MACE'04 at a BER of 10-3. Therefore, the proposed scheme obtains a good BER performance and low complexity and it is suitable for efficient use in UWACs.

Efficient Polar Coded Selective Decode-and-Forward with Cooperative Decision Threshold in Cooperative Multi-Relay Transmissions.

In some satellite Internet of Things (IoT) devices with terrain shielding, the qualities of the direct source-destination (S-D) channel are poor, requiring cooperative communications with multi-relays to be employed. In order to solve error propagation of current decode-and-forward (DF) on such occasions, an efficient polar coded selective decode-and-forward (SDF) cooperation method is proposed with a new decision threshold derived from channel state information (CSI). First, the proposed threshold is derived from the CSI by exploiting the channel gain ratio of optimal relay-destination link (R-D) with source-relay (S-R) link. The above R-D link possesses good channel quality among all links in the system. Second, when the channel gain ratio of certain relay links is larger than the aforementioned decision threshold, the source and all these relays cooperatively send messages together to the destination to accomplish perfect SDF transmission. Otherwise, all relays are frozen and the messages are directly transmitted through the S-D link. If it fails anyway, a retransmission is subsequently tried in the next transmission cycle. In addition, a polar code for fading channels is designed and adaptively adjusted to a proper code rate according to channel quality to attain good bit error rate (BER) performance. Simulation results show that the proposed scheme achieves about 0.9 and 0.5 dB gain at BER of 10-4, respectively, in multi-relay cooperative communications with multi-path fading channels compared with those of non-cooperation and existing polar coded cooperation channels. Therefore, the proposed polar coded SDF (PCSDF) scheme can improve both the BER and the outage probability (OP) performance in multi-relay cooperative systems, making it quite suitable for heterogeneous network applications in cooperative satellite IoT systems involving sixth-generation (6G) communications.

Case Report: A Frameshift Mutation in MSH2 Exon 2 in a Kidney Recipient With Muir-Torre Syndrome.

Muir-Torre syndrome (MTS), a rare subtype of Lynch syndrome, is mostly autosomal dominant, which is caused by germline mutations in DNA mismatch repair (MMR) genes, the resulting microsatellite instability (MSI) of which increases the risk of developing sebaceous and other visceral tumors. Several reports have showed an association between immunosuppressive agents and the progression of latent MTS. In this report, we described a 41-year-old man with a history of kidney transplantation, having a rapid growth of the nodule on the anterior chest under immunosuppressive therapy, which was histologically proved to be sebaceous carcinoma. Systemic evaluation for visceral malignancies revealed sigmoid adenocarcinoma. These findings were consistent with the clinical diagnosis of MTS. Histological findings showed an absence of MMR proteins, including MSH2 and MSH6 both in the sebaceous carcinoma and sigmoid adenocarcinoma on immunohistochemical (IHC) analysis. A frame-shift mutation of c.229_230delAG (p. Ser77fs) in the MSH2 exon 2 in the lesion was detected by next-generation sequencing (NGS) analysis. This case report not only reveals a new site of MSH2 mutation in this family of East Asian descent but also highlights the importance of adequate diagnosis for Muir-Torre syndrome, as well as further prevention of the development of latent visceral tumors in kidney transplant recipients.