Low-density parity-check (LDPC) codes are widely used in communication systems for their high error-correcting performance. This survey introduces the elements of LDPC codes: decoding algorithms, code construction, encoding algorithms, and several classes of LDPC codes.

This paper details the design of a plate that controls the beam direction in an aperture array excited by a waveguide 2-plane hybrid coupler. The beam direction can be controlled in the range of ±15-32deg. in the quasi H-plane, and ±26-54deg. in the quasi E-plane at the design frequency of 66.425GHz. Inductive irises are introduced into tapered waveguides in the plate and the reflection is suppressed by narrow apertures. A plate that has a larger tilt angle in the quasi E-plane and another plate with conventional rectangular waveguide ports as a reference are fabricated and measured. The measured values agree well with the simulation results.

In this paper, an experimental method is proposed for extracting the primary and secondary parameters of transmission lines with frequency dispersion. So far, there is no report of these methods being applied to transmission lines with frequency dispersion. This paper provides an experimental evaluation means of transmission lines with frequency dispersion and clarifies the issues when applying the proposed method. In the proposed experimental method, unnecessary components such as connectors are removed by using a simple de-embedding method. The frequency response of the primary and secondary parameters extracted by using the method reproduced all dispersion characteristics of a transmission line with frequency dispersion successfully. It is demonstrated that an accurate RLGC equivalent-circuit model is obtained experimentally, which can be used to quantitatively evaluate the frequency/time responses of shielded-FPC with frequency dispersion and to validate RLGC equivalent-circuit models extracted by using electromagnetic field analysis.

This paper presents a deep neural network (DNN) based symbol detection and modulation classification detector (SDMCD) for mixed blind signals detection. Unlike conventional methods that employ symbol detection after modulation classification, the proposed SDMCD can perform symbol recovery and modulation identification simultaneously. A cumulant and moment feature vector is presented in conjunction with a low complexity sparse autoencoder architecture to complete mixed signals detection. Numerical results show that SDMCD scheme has remarkable symbol error rate performance and modulation classification accuracy for various modulation formats in AWGN and Rayleigh fading channels. Furthermore, the proposed detector has robust performance under the impact of frequency and phase offsets.

In recent years, there has been significant interest in information-theoretic security techniques that encrypt physical layer signals. We have proposed chaos modulation, which has both physical layer security and channel coding gain, as one such technique. In the chaos modulation method, the channel coding gain can be increased using a turbo mechanism that exchanges the log-likelihood ratio (LLR) with an external concatenated code using the max-log approximation. However, chaos modulation, which is a type of Gaussian modulation, does not use fixed mapping, and the distance between signal points is not constant; therefore, the accuracy of the max-log approximated LLR degrades under poor channel conditions. As a result, conventional methods suffer from performance degradation owing to error propagation in turbo decoding. Therefore, in this paper, we propose a new LLR clipping method that can be optimally applied to chaos modulation by limiting the confidence level of LLR and suppressing error propagation. For effective clipping on chaos modulation that does not have fixed mappings, the average confidence value is obtained from the extrinsic LLR calculated from the demodulator and decoder, and clipping is performed based on this value, either in the demodulator or the decoder. Numerical results indicated that the proposed method achieves the same performance as the one using the exact LLR, which requires complicated calculations. Furthermore, the security feature of the proposed system is evaluated, and we observe that sufficient security is provided.

Deployment of machine-type communications (MTCs) over the current cellular network could lead to severe overloading of the radio access network of Long Term Evolution (LTE)-based systems. This paper proposes a slotted access-based solution, called the Slotted Access For Group Paging (SAFGP), to cope with the paging-induced MTC traffic. The proposed SAFGP splits paged devices into multiple access groups, and each group is then allocated separate radio resources on the LTE's Physical Random Access Channel (PRACH) in a periodic manner during the paging interval. To support the proposed scheme, a new adaptive barring algorithm is proposed to stabilize the number of successful devices in each dedicated access slot. The objective is to let as few devices transmitting preambles in an access slot as possible while ensuring that the number of preambles selected by exactly one device approximates the maximum number of uplink grants that can be allocated by the eNB for an access slot. Analysis and simulation results demonstrate that, given the same amount of time-frequency resources, the proposed method significantly improves the access success and resource utilization rates at the cost of slightly increasing the access delay compared to state-of-the-art methods.

The application of compressed sensing (CS) theory to non-orthogonal multiple access (NOMA) systems has been investigated recently. As described in this paper, we propose a quality-of-service (QoS)-aware, low-complexity, CS-based user selection and power allocation scheme with adaptive resource block selection for downlink NOMA systems, where the tolerable interference threshold is designed mathematically to achieve a given QoS requirement by being relaxed to a constrained l1 norm optimization problem. The proposed scheme adopts two adaptive resource block (RB) selection algorithms that assign proper RB to user pairs, i.e. max-min channel assignment and two-step opportunistic channel assignment. Simulation results show that the proposed scheme is more effective at improving the user rate than other reference schemes while reducing the required complexity. The QoS requirement is approximately satisfied as long as the required QoS value is feasible.

This work investigates the effect of channel estimation error on the average secrecy outage capacity of dual selection in the presence of multiple eavesdroppers. The dual selection selects a transmit antenna of Alice and Bob (i.e., user terminal) which provide the best received signal to noise ratio (SNR) using channel state information from every user terminals. Using Gaussian approximation, this paper obtains the tight analytical expression of the dual selection for the average secrecy outage capacity over channel estimation error and multiple eavesdroppers. Using asymptotic analysis, this work quantifies the high SNR power offset and the high SNR slope for the average secrecy outage capacity at high SNR.

Currently, unmanned aerial vehicles (UAV) have been widely used in many applications, such as in transportation logistics, public safety, or even in non-terrestrial networks (NTN). In all these scenarios, it is an important issue to model channel behavior between the UAV and the user equipment (UE) on the ground. Among these channel features, a critical parameter that dominates channel behavior is the probability of the line-of-sight (LOS), since the statistical property of the channel fading can be either Ricean or Rayleigh, depending on the existence of LOS. Besides, with knowledge of LOS probability, operators can design approaches or schemes to maximum system performance, such as the serving coverage, received signal to noise ratio (SNR), or the bit error rate (BER) with the limited transmitted power. However, the LOS UAV channel is likely difficult to acquire or derive, as it depends on the deployment scenario, such as an urban or rural area. In this paper, we generated four different scenarios defined by the ITU via the ray tracing simulator. Then, we used the spatial geometric relation and the curve fitting approach to derive the analytic models to predict the probability of the UAV LOS channels for different scenarios. Results show that our proposed relationships yield better prediction results than the methods in the literature. Besides, an example of establishing UAV self-awareness ability for the deployed environment via using proposed models is also provided in this paper.

This paper presents a novel blind signal separation method for the measurement of pulse waves at multiple body positions using an array radar system. The proposed method is based on a mathematical model of pulse wave propagation. The model relies on three factors: (1) a small displacement approximation, (2) beam pattern orthogonality, and (3) an impulse response model of pulse waves. The separation of radar echoes is formulated as an optimization problem, and the associated objective function is established using the mathematical model. We evaluate the performance of the proposed method using measured radar data from participants lying in a prone position. The accuracy of the proposed method, in terms of estimating the body displacements, is measured using reference data taken from laser displacement sensors. The average estimation errors are found to be 10-21% smaller than those of conventional methods. These results indicate the effectiveness of the proposed method for achieving noncontact measurements of the displacements of multiple body positions.

While social media is now used by many people and plays a role in distributing information, it has recently created an unexpected problem: the actual shrinkage of information sources. This is mainly due to the ease of connecting people with similar opinions and the recommendation system. Biased information distribution promotes polarization that divides people into multiple groups with opposing views. Also, people may receive only the seemingly positive information that they prefer, or may trigger them into holding onto their opinions more strongly when they encounter opposing views. This, combined with the characteristics of social media, is accelerating the polarization of opinions and eventually social division. In this paper, we propose a model of opinion formation on social media to simulate polarization. While based on the idea that opinion neutrality is only relative, this model provides new techniques for dealing with polarization.

Tile-based virtual reality (VR) video consists of high-resolution tiles that are displayed in accordance with the users' viewing directions and a low-resolution tile that is the entire VR video and displayed when users change their viewing directions. Whether users perceive quality degradation when watching tile-based VR video depends on high-resolution tile size, the quality of high- and low-resolution tiles, and network condition. The display time of low-resolution tile (hereafter delay) affects users' perceived quality because longer delay makes users watch the low-resolution tiles longer. Since these degradations of low-resolution tiles markedly affect users' perceived quality, these points have to be considered in the quality-estimation model. Therefore, we propose a bitstream-quality-estimation model for tile-based VR video streaming services and investigate the effect of bitstream parameters and delay on tile-based VR video quality. Subjective experiments on several videos of different qualities and a comparison between other video quality-estimation models were conducted. In this paper, we prove that the proposed model can improve the quality-estimation accuracy by using the high- and low-resolution tiles' quantization parameters, resolution, framerate, and delay. Subjective experimental results show that the proposed model can estimate the quality of tile-based VR video more accurately than other video quality-estimation models.