A random access scheme is a fundamental scenario in which the users transmit through a shared channel and cannot coordinate with each other. Recently, successive interference cancellation (SIC) is introduced into the random access scheme. The SIC decodes the transmitted packets using collided packets. The coded slotted ALOHA (CSA) is a random access scheme using the SIC. The CSA encodes each packet by a local code prior to transmission. It is known that the CSA achieves excellent throughput. On the other hand, it is reported that shift operation improves the decoding performance for packet-oriented erasure correcting coding systems. In this paper, we propose a protocol which applies the shift operation to the CSA. Numerical simulations show that the proposed protocol achieves better throughput and packet loss rate than the CSA. Moreover, we analyze the asymptotic behavior of the throughput and the decoding erasure rate for the proposed protocol by the density evolution.

In this letter, we investigate a design of efficient antenna allocation at the full duplex receiver (FDR) in a multi-input multi-output multi-eavesdropper (MIMOME) wiretap channel for physical layer security improvement. Specifically, we propose the allocation which are feasible for the practical scenario with self-interference (SI) taken into account, because the jamming signals from FDR not only confuse the eavesdropper but also inevitably cause SI at the FDR. Due to the nolinear and coupling of the antenna allocation optimization problem, we transform the original problem into an integer programming problem. Then, we derive the optimal solution and the corresponding beamforming matrices in closed-form by means of combining spatial alignment and null-space projection method. Furthermore, we present the feasibility condition and full-protection condition, which offer insight into principles that enable more efficient and effective use of FDR in the wiretap channel for security improvement. From the simulation results, we validate the theoretical analysis and demonstrate the outstanding performance of the proposed antennas allocation at FDR.

At PQCrypto 2016, Szepieniec et al. proposed a new type of trapdoor called Extension Field Cancellation (EFC) for constructing secure multivariate encryption cryptosystems. They also specifically suggested two schemes EFCp- and EFCpt2- that apply this trapdoor and some modifiers. Although both of them seem to avoid all attacks used for cryptanalysis on multivariate cryptography, their decryption efficiency has room for improvement. On the other hand, their security was analyzed mainly through an algebraic attack of computing the Gröbner basis of the public key, and there possibly exists more effective attacks. In this paper, we introduce a more efficient decryption approach for EFCp- and EFCpt2-, which manages to avoid all redundant computation involved in the original decryption algorithms without altering their public key. In addition, we estimate the secure parameters for EFCp- and EFCpt2- through a hybrid attack of algebraic attack and exhaustive search.

This paper proposes a novel low complexity lattice reduction-aided iterative receiver for overloaded MIMO. Novel noise cancellation is proposed that increases an equivalent channel gain with a scalar gain introduced in this paper, which results in the improvement of the signal to noise power ratio (SNR). We theoretically analyze the performance of the proposed receiver that the lattice reduction raises the SNR of the detector output signals as the scalar gain increases, when the Lenstra-Lenstra-Lova's (LLL) algorithm is applied to implement the lattice reduction. Because the SNR improvement causes the scalar gain to increase, the performance is improved by iterating the reception process. Computer simulations confirm the performance. The proposed receiver attains a gain of about 5dB at the BER of 10-4 in a 6×2 overloaded MIMO channel. Computational complexity of the proposed receiver is about 1/50 as much as that of the maximum likelihood detection (MLD).

This paper presents a method combining array signal processing and adaptive noise cancellation to suppress unwanted ambient interferences in in situ measurement of radiated emissions of equipment. First, the signals received by the antenna array are processed to form a main data channel and an auxiliary data channel. The main channel contains the radiated emissions of the equipment under test and the attenuated ambient interferences. The auxiliary channel only contains the attenuated ambient interferences. Then, the adaptive noise cancellation technique is used to suppress the ambient interferences based on the correlation of the interferences in the main and auxiliary channels. The proposed method overcomes the problem that the ambient interferences in the two channels of the virtual chamber method are not correlated, and realizes the suppression of multi-source ambient noises in the use of fewer array elements. The results of simulation and experiment show that the proposed method can effectively extract radiated emissions of the equipment under test in complex electromagnetic environment. Finally, discussions on the effect of the beam width of the main channel and the generalization of the proposed method to three dimensionally distributed signals are addressed.

This paper proposes a new design criterion of adaptively scaled belief (ASB) in Gaussian belief propagation (GaBP) for large multi-user multi-input multi-output (MU-MIMO) detection. In practical MU detection (MUD) scenarios, the most vital issue for improving the convergence property of GaBP iterative detection is how to deal with belief outliers in each iteration. Such outliers are caused by modeling errors due to the fact that the law of large number does not work well when it is difficult to satisfy the large system limit. One of the simplest ways to mitigate the harmful impact of outliers is belief scaling. A typical approach for determining the scaling parameter for the belief is to create a look-up table (LUT) based on the received signal-to-noise ratio (SNR) through computer simulations. However, the instantaneous SNR differs among beliefs because the MIMO channels in the MUD problem are random; hence, the creation of LUT is infeasible. To stabilize the dynamics of the random MIMO channels, we propose a new transmission block based criterion that adapts belief scaling to the instantaneous channel state. Finally, we verify the validity of ASB in terms of the suppression of the bit error rate (BER) floor.

This paper presents a wideband inductorless noise-cancelling balun LNA with two gain modes, low NF, and high-linearity for LTE and intermediate-frequency-band (eg. 3.3-3.6GHz, 4.8-5GHz) 5G applications fabricated in 65nm CMOS. The proposed LNA is bonding tested and exhibits a minimum NF of 2.2dB and maximum IIP3 of -3.5dBm. Taking advantage of an off-chip bias inductor in CG stage and a cross-coupled buffer, the LNA occupies high operation frequency up to 5GHz with remarkable linearity and NF as well as compact area.

This study proposes a multiple-output differential-input operational transconductance amplifier-C (MODI OTA-C) filter with an impedance scaler to detect cardiac activity. A ladder-type fifth-orderButterworth low-pass filter with a large time constant and low noise is implemented to reduce coefficient sensitivity and address signal distortion. Moreover, linearized MODI OTA structures with reduced transconductance and impedance scaler circuits for noise reduction are used to achieve a wide dynamic range (DR). The OTA-based circuit is operated in the subthreshold region at a supply voltage of 1 V to reduce the power consumption of the wearable device in long-term use. Experimental results of the filter with a bandwidth of 250 Hz reveal that DR is 57.6 dB, and the harmonic distortion components are below -59 dB. The power consumption of the filter, which is fabricated through a TSMC 0.18 µm CMOS process, is lower than 390 nW, and the active area is 0.135 mm2.

Recently, the demand for the digitization of manga is increased. Then, in the case of an old manga where the original pictures have been lost, we have to digitize it from comics. However, the show-through phenomenon would be caused by scanning of the comics since it is represented as the double sided images. This letter proposes the manga show-through cancellation method based on the deep convolutional neural network (CNN). Numerical results show that the effectiveness of the proposed method.

In this paper, we present self-interference (SI) cancellation techniques in the digital domain for in-band full-duplex systems employing orthogonal frequency division multiple access (OFDMA) in the downlink (DL) and single-carrier frequency division multiple access (SC-FDMA) in the uplink (UL), as in the long-term evolution (LTE) system. The proposed techniques use UL subcarrier nulling to accurately estimate SI channels without any UL interference. In addition, by exploiting the structures of the transmitter imperfection and the known or estimated parameters associated with the imperfection, the techniques can further improve the accuracy of SI channel estimation. We also analytically derive the lower bound of the mean square error (MSE) performance and the upper bound of the signal-to-interference-plus-noise ratio (SINR) performance for the techniques, and show that the performance of the techniques are close to the bounds. Furthermore, by utilizing the SI channel estimates and the nonlinear signal components of the SI caused by the imperfection to effectively eliminate the SI, the proposed techniques can achieve SINR performance very close to the one in perfect SI cancellation. Finally, because the SI channel estimation of the proposed techniques is performed in the time domain, the techniques do not require symbol time alignment between SI and UL symbols.

Our previous work proposed a semi-blind single antenna interference cancellation scheme to cope with severe inter-cell interference in heterogeneous networks. This paper extends the scheme to allow multiple-receive-antenna implementation. It does not require knowledge of the training sequences of interfering signals and can cancel multiple interfering signals irrespective of the number of receive antennas. The proposed scheme applies an enhanced version of the quantized channel approach to suboptimal joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals, while reducing the computational complexity of optimum JCESD drastically. Different from the previous work, the proposed scheme applies the quantized channel generation and local search at each individual receive antenna so as to estimate transmitted symbol matrices during the training period. Then, joint estimation is newly introduced in order to estimate a channel matrix from the estimated symbol matrices, which operates in the same manner as the expectation maximization (EM) algorithm and considers signals received at all receive antennas. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) during the data period under the maximum likelihood (ML) criterion in order to cancel the interference. Computer simulations with two receive antennas under two-interfering-stream conditions show that the proposed scheme outperforms interference rejection combining (IRC) with perfect channel state information (CSI) and MUD with channels estimated by a conventional scheme based on the generalized Viterbi algorithm, and can achieve almost the same average bit error rate (BER) performance as MUD with channels estimated from sufficiently long training sequences of both the desired stream(s) and the interfering streams, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

In order to cope with severe interference in heterogeneous networks, this paper proposes a semi-blind interference cancellation scheme, which does not require multiple receive antennas or knowledge about training sequences of the interfering signals. The proposed scheme performs joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals. On the other hand, maximum likelihood detection (MLD), which can be considered the optimum JCESD, must perform channel estimation for all transmitted signal candidates of the interfering signals and must search for the most likely signal candidate. Therefore, MLD incurs a prohibitive amount of computational complexity. To reduce such complexity drastically, the proposed scheme enhances the quantized channel approach, and applies the enhanced version to JCESD. In addition, a recalculation scheme is introduced to avoid inaccurate channel estimates due to local minima. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) of the data sequences in order to cancel the interference. Computer simulations show that the proposed scheme outperforms a conventional scheme based on the Viterbi algorithm, and can achieve almost the same average bit error rate performance as the MUD with channels estimated from sufficiently long training sequences of both the desired signal and the interfering signals, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

In the scenario of finite sample size, the performance of the generalized sidelobe canceller (GSC) is still affected by the desired signal even if all signal sources are independent with each other. Firstly, the novel expression of weight vector of the auxiliary array is derived under the circumstances of finite sample size. Utilizing this new weight vector and considering the correlative interferences, the general expression for the interference cancellation ratio (CR) is developed. Then, the impacts of the CR performance are further analyzed for the parameters including the input signal-to-noise ratio (SNR), the auxiliary array size, the correlation coefficient between the desired signal and interference as well as the snapshots of the sample data, respectively. Some guidelines can thus be given for the practical application. Numerical simulations demonstrate the agreement between the simulation results and the analytical results.

The breadth-first tree searching (BFTS) detection algorithm such as the QR decomposition with M algorithm (QRD-M) which is the generally K-best detection algorithm is suboptimal, but has high complexity. In this letter, the K-best BFTS detection algorithm having reduced complexity is proposed. The proposed detection algorithm calculates the channel condition to decide the thresholds for regulating complexity and performance and from the simulation results, it has good error performance with very low complexity.

A novel generalized side-information cancellation (GSIC) precoder is proposed for multiuser multi-input multi-output (MIMO) downlink systems with channel state information at the transmitter. The proposed transceiver involves the following stages. First, a minimum mean square error (MMSE) based channel inversion (MMSE-CI) technique is utilized to suppress multiuser broadcast interference. By using a GSIC technique, it can further reduce the residual multiuser interference and the noise induced by MMSE-CI preprocessing. Next, with a singular value decomposition method, the spatial stream interference of each user is suppressed by the pre-processing and post-processing eigenvector matrices. Finally, the proposed precoder can be extended to joint water filling and diagonal loading methods for performance enhancement. For the correlated MIMO channels, signal subspace and antenna selection methods, incorporating the proposed GSIC precoder, are further designed to maximize the sum rate performance. Simulation results show that the proposed GSIC precoder outperforms the conventional precoders. Besides, simulation results confirm that the proposed GSIC precoder with water filling, diagonal loading, and signal subspace techniques exhibits excellent performance.

This letter presents a successive partial interference cancellation (SPIC) scheme for full-duplex (FD) and multiple-input multiple-output (MIMO) relaying system. The proposed scheme coordinates the cancellation for the self-interference and inter-stream interference. The objective for the coordination focuses on simultaneously minimizing the two interferences. Simulation results under the measured data show that the system with the proposed scheme can achieve a significant performance gain compared to the conventional FD and half-duplex (HD) systems.

This paper experimentally verifies the potential of higher order space division multiplexing in line-of-sight (LOS) channels for multiuser massive MIMO. We previously proposed an inter-user interference (IUI) cancellation scheme and a simplified user scheduling method for Massive Antenna Systems for Wireless Entrance (MAS-WE). In order to verify the effectiveness of the proposed techniques, channel state information (CSI) for a 1×32 SIMO channel is measured in a real propagation environment with simplified test equipment. Evaluations of the measured CSI data confirm the effectiveness of our proposals; they offer good equal gain transmission (EGT) performance, reduced spatial correlation with enlarged angular gap between users, and quite small channel state fluctuation. Link level simulations elucidate that the simple IUI cancellation method is stable in practical conditions. The degradation in symbol error rate with the measured CSI, relative to that yielded by the output of the theoretical LOS channel model, is insignificant.

This paper proposes a practical application of Massive MIMO technology, Massive Antenna Systems for Wireless Entrance (MAS-WE), and along with related inter-user interference cancellation (IUIC) and scheduling techniques. MAS-WE, in which the entrance base station (EBS) employs a large number of antennas, can effectively provide high capacity wireless entrance links to a large number of access points (APs) distributed over a wide coverage area. The proposed techniques are simplified to practical implementation; EBS side uses around 100 antenna elements to spatially multiplex more than 16 signal streams. SIR performance is evaluated by system level simulations that consider imperfect channel state information (CSI). The results show that MAS-WE with the proposed techniques can reliably achieve high spectral efficiency with high level space division multiplexing.

In multi user multiple input multiple output systems, spatial precoding is typically employed as an interference cancellation technique. This technique, however, requires accurate channel state information at the transmitter and limits the mobility of the mobile station (MS). Instead of spatial precoding, this letter implements collaborative interference cancellation (CIC) for interference suppression. In CIC, neighboring MSs share their received signals without decoding and equivalently increase the number of received antennas. The performance is evaluated through a field experiment using a vehicle that is equipped with seven MSs and moves around an urban area.

For the nonlinear acoustic echo cancellation, we present an algorithm to estimate the threshold of the clipping effect and the room impulse response vector by suppressing their time-varying cost function. A common way to suppress the time-varying cost function of a pair of parameters is to alternatingly minimize the function with respect to each parameter while keeping the other fixed, which we refer to as adaptive alternating minimization. However, since the cost function for the threshold is nonconvex, the conventional methods approximate the exact minimizations by gradient descent updates, which causes serious degradation of the estimation accuracy in some occasions. In this paper, by exploring the fact that the cost function for the threshold becomes piecewise quadratic, we propose to exactly minimize the cost function for the threshold in a closed form while suppressing the cost function for the impulse response vector in an online manner, which we call exact-online adaptive alternating minimization. The proposed method is expected to approximate more efficiently the adaptive alternating minimization strategy than the conventional methods. Numerical experiments demonstrate the efficacy of the proposed method.