The construction of frequency hopping sequences with good Hamming correlation is the foundation of research in frequency hopping communication. In this letter, classes of optimal low hit zone frequency hopping sequence set are constructed based on the interleaving technology. The results of the study show that the sequence set with large family size is optimal for the Peng-Fan-Lee bound. And all the sequences in the set are inequivalent.

This paper describes a design methodology for process variation aware D-Flip-Flop (DFF) using regression analysis. We propose to use a regression analysis to model the worst-case delay characteristics of a DFF under process variation. We utilize the regression equation for transistor width tuning of the DFF to improve its worst-case delay performance. Regression analysis can not only identify the performance-critical transistors inside the DFF, but also shows these impacts on DFF delay performance in quantitative form. Proposed design methodology is verified using Monte-Carlo simulation. The result shows the proposed method achieves to design a DFF which has similar or better delay characteristics in comparison with the DFF designed by an experienced cell designer.

In this paper, we propose a design of reversible adder/subtractor blocks and arithmetic logic units (ALUs). The main concept of our approach is different from that of the existing related studies; we emphasize the function design. Our approach of investigating the reversible functions includes (a) the embedding of irreversible functions into incompletely-specified reversible functions, (b) the operation assignment, and (c) the permutation of function outputs. We give some extensions of these techniques for further improvements in the design of reversible functions. The resulting reversible circuits are smaller than that of the existing design in terms of the number of multiple-control Toffoli gates. To evaluate the quantum cost of the obtained circuits, we convert the circuits to reduced quantum circuits for experiments. The results also show the superiority of our realization of adder/subtractor blocks and ALUs in quantum cost.

Spectrum sensing is the first task performed by cognitive radio (CR) networks. In this paper we propose a spectrum sensing algorithm for orthogonal frequency division multiplex (OFDM) signal based on deep learning and covariance matrix graph. The advantage of deep learning in image processing is applied to the spectrum sensing of OFDM signals. We start by building the spectrum sensing model of OFDM signal, and then analyze structural characteristics of covariance matrix (CM). Once CM has been normalized and transformed into a gray level representation, the gray scale map of covariance matrix (GSM-CM) is established. Then, the convolutional neural network (CNN) is designed based on the LeNet-5 network, which is used to learn the training data to obtain more abstract features hierarchically. Finally, the test data is input into the trained spectrum sensing network model, based on which spectrum sensing of OFDM signals is completed. Simulation results show that this method can complete the spectrum sensing task by taking advantage of the GSM-CM model, which has better spectrum sensing performance for OFDM signals under low SNR than existing methods.

For an odd prime p and a positive integer k ≥ 2, we propose and analyze construction of perfect pk-ary sequences of period pk based on cubic polynomials over the integers modulo pk. The constructed perfect polyphase sequences from cubic polynomials is a subclass of the perfect polyphase sequences from the Mow's unified construction. And then, we give a general approach for constructing optimal families of perfect polyphase sequences with some properties of perfect polyphase sequences and their optimal families. By using this, we construct new optimal families of pk-ary perfect polyphase sequences of period pk. The constructed optimal families of perfect polyphase sequences are of size p-1.

Semi-bent functions have very high nonlinearity and hence they have many applications in symmetric-key cryptography, binary sequence design for communications, and combinatorics. In this paper, we focus on studying the additive autocorrelation of semi-bent functions. We provide a lower bound on the maximum additive autocorrelation absolute value of semi-bent functions with three-level additive autocorrelation. Semi-bent functions with three-level additive autocorrelation achieving this bound with equality are said to have perfect three-level additive autocorrelation. We present two classes of balanced semi-bent functions with optimal algebraic degree and perfect three-level additive autocorrelation.

This paper improves the family size of quadrature amplitude modulation (QAM) complementary sequences with binary inputs. By employing new mathematical description: B-type-2 of 4q-QAM constellation (integer q ≥ 2), a new construction yielding 4q-QAM complementary sequences (CSs) with length 2m (integer m ≥ 2) is developed. The resultant sequences include the known QAM CSs with binary inputs as special cases, and the family sizes of new sequences are approximately 22·2q-4q-1(22·2q-3-1) times as many as the known. Also, both new sequences and the known have the same the peak envelope power (PEP) upper bounds, when they are used in an orthogonal frequency-division multiplexing communication system.

Bit-interleaved coded modulation with iterative decoding (BICM-ID) is suitable for correlated Rayleigh fading channels. Additionally, BICM-ID using differential encoding can avoid the pilot overhead. In this paper, we consider BICM-ID using 16-DAPSK (differential amplitude and phase-shift keying). We first derive the probability of receiving signals conditioned on the transmission of input bits for general differential encoding; then we propose two new 16-DAPSK bit labeling methods. In addition, convolutional codes for the new bit labeling are developed. Both the minimum distance and the simulation results show that the proposed labeling has better error performance than that of the original differential encoding, and the searched new codes can further improve the error performance.

We propose an approach to allocate bandwidth for a satellite communications (SATCOM) system that includes the recent high-throughput satellite (HTS) with frequency flexibility. To efficiently operate the system, we manage the limited bandwidth resources available for SATCOM by employing a control method that allows the allocated bandwidths to exceed the communication demand of user terminals per HTS beam. To this end, we consider bandwidth allocation for SATCOM as an optimal control problem. Then, assuming that the model of communication requests is available, we propose an optimal control method by combining model predictive control and sparse optimization. The resulting control method enables the efficient use of the limited bandwidth and reduces the bandwidth loss and number of control actions for the HTS compared to a setup with conventional frequency allocation and no frequency flexibility. Furthermore, the proposed method allows to allocate bandwidth depending on various control objectives and beam priorities by tuning the corresponding weighting matrices. These findings were verified through numerical simulations by using a simple time variation model of the communication requests and predicted aircraft communication demand obtained from the analysis of actual flight tracking data.

The order/degree problem consists of finding the smallest diameter graph for a given order and degree. Such a graph is beneficial for designing low-latency networks with high performance for massively parallel computers. The average shortest path length (ASPL) of a graph has an influence on latency. In this paper, we propose a novel order adjustment approach. In the proposed approach, we search for Cayley graphs of the given degree that are close to the given order. We then adjust the order of the best Cayley graph to meet the given order. For some order and degree pairs, we explain how to derive the smallest known graphs from the Graph Golf 2016 and 2017 competitions.

An optimal arrangement problem involves finding a component arrangement to maximize system reliability, namely, the optimal arrangement. It is useful to obtain the optimal arrangement when we design a practical system. An existing study developed an algorithm for finding the optimal arrangement of a connected-(r, s)-out-of-(m, n): F lattice system with r=m-1 and n<2s. However, the algorithm is time-consuming to find the optimal arrangement of a system having many components. In this study, we develop an algorithm for efficiently finding the optimal arrangement of the system with r=m-1 and s=n-1 based on the depth-first branch-and-bound method. In the algorithm, before enumerating arrangements, we assign some components without computing the system reliability. As a result, we can find the optimal arrangement effectively because the number of components which must be assigned decreases. Furthermore, we develop an efficient method for computing the system reliability. The numerical experiment demonstrates the effectiveness of our proposed algorithm.

The enhanced chosen-ciphertext security (ECCA) is motivated by the concept of randomness recovering encryption, which was presented by Dana Dachman-Soled et al. in PKC 2014 [9]. ECCA security is the enhanced version of CCA security. CCA security often appears to be somewhat too strong, so ECCA security is also too strong: there exist encryption schemes that are not ECCA secure but still have some practical application. Canetti et al. proposed a relaxed variant of CCA security called Replayable CCA (RCCA) security in CRYPTO 2003 [3]. In this paper, we propose a relaxed variant of ECCA security called Replayable security (RECCA). RECCA security is the enhanced version of RCCA security. Since RCCA security suffices for the most existing application of CCA security, RECCA security also suffices for them, too. Moreover, RECCA security provides a useful general version of security against active attacks.

Excitation of Extremely Low Frequency (ELF)/Very Low Frequency (VLF) from ionosphere,which is artificial modulated by High Frequency (HF) waves can provide a way of antenna generation for deep submarine communication. In this paper, based on plasma energy conservation equation, the theoretical model of amplitude modulation HF pump heating low ionosphere for ELF/VLF generation is established. The linear frequency modulation technique of up-chirp and down-chirp have good self-correlation and cross-correlation, by which information can be transmitted by up-chirp and down-chirp. Thus, the linear frequency modulation technique can be applied to the ionosphere ELF/VLF communication. Based on this, a Chirp-BOK (Binary Orthogonal Keying) communication scheme is proposed. Indeed the Chirp-BOK amplitude and power modulation function are designed by combining the linear frequency modulation technique with the square wave amplitude modulation technique. The simulation results show in the condition that the ionosphere is heated by the Chirp-BOK power modulation HF waves, the temperature of ionospheric electronic and the variations of conductivity have obvious frequency modulation characteristics which are the same as that of power modulation, so does the variation of ionospheric current. Thus, when the ionosphere is heated by Chirp-BOK power modulation HF waves, the up-chirp (symbol ‘0’) and down-chirp (symbol ‘1’) ELF/VLF signals can be generated.

Network coding signature (NCS) scheme is a cryptographic tool for network coding against pollution attacks. In [5], Chang et al. first introduced the related-key attack (RKA) to the NCS schemes and tried to give an instantiation of it. However, their instantiation is based on the random oracle (RO) model. In this letter, we present a standard-model instantiation. In particular, we prove that standard-model-based NCS scheme introduced by Boneh et al. in [4] (BFKW scheme, for short) can achieve Φ-RKA security if the underlying signature scheme is also Φ-RKA secure, where Φ is any family of functions defined on signing keys of NCS schemes.

In-network guidance to off-path cache, Breadcrumbs, has been proposed for cache network. It guides content requests to off-path cached contents by using the latest content download direction pointer, breadcrumbs. In Breadcrumbs, breadcrumb pointer is overwritten when a new content download of the corresponding content passes through a router. There is a possibility that slightly old guidance information for popular contents might lead to better cached content than the latest one. In this paper, we propose a new in-network guidance, Multiple-Breadcrumbs, which holds old breadcrumbs even with the latest breadcrumb pointer generated with a new content download. We focus on its content search capability and propose Throughput Sensitive selection that selects the content source giving the best estimated throughput. Our performance evaluation gives interesting results that our proposed Multiple Breadcrumbs with Throughput Sensitive selection improves not only throughput for popular contents but also for unpopular contents.

Multiple input multiple output with orthogonal frequency division multiplexing (MIMO-OFDM) is used in various parts of wireless communication systems. Because the MIMO-OFDM system simultaneously transmits parallel data streams and each receive antenna receives all data streams at one time, the detection ability of the receiver is very important. Among the detection schemes suitable for OFDM, maximum likelihood (ML) detection has optimal performance, but its complexity is so high that it is infeasible. Linear detection schemes such as zero-forcing (ZF) and minimum mean square error (MMSE) have low complexity, but also low performance. Among non-linear detection schemes, the near-ML detection which is the sphere detection (SD) or the QR decomposition with M algorithm (QRD-M) also has optimal performance but the complexity of SD and QRD-M detection is also too high. Other non-linear detection schemes like successive interference cancellation (SIC) detection have low complexity. However, the performance of SIC detection is lower than other non-linear detection schemes. In this paper, selectively iterative detection is proposed for MIMO-OFDM system; it offers low complexity and good performance.

This paper proposes a novel dynamic channel assignment scheme named interference-aware dynamic channel assignment (IA-DCA) for the downlink of enterprise small-cell networks (ESNs) that employ orthogonal frequency division multiple access (OFDMA) and frequency division duplexing (FDD). In ESNs, a lot of small-cell access points (SAPs) are densely deployed in a building and thus small-cell user equipments (SUEs) have more serious co-tier interference from neighbor SAPs than the conventional small-cell network. Therefore, in the proposed IA-DCA scheme, a local gateway (LGW) dynamically assigns different numbers of subchannel groups to SUEs through their serving SAPs according to the given traffic load and interference information. Through simulation results, we show that the proposed IA-DCA scheme outperforms other dynamic channel assignment schemes based on graph coloring algorithm in terms of the mean SUE capacity, fairness, and mean SAP channel utilization.

This paper applies minimum mean square error (MMSE) interference rejection followed by joint maximum likelihood detection (MLD) to a receiver in a distributed antenna network (DAN). DAN receivers capture not only the desired signals, but also the interference signals from nearby uncoordinated antennas. For the overloaded signal situation, non-linear detection schemes such as joint MLD can be applied to the received signals. However, the amount of metric calculations in joint MLD increases exponentially with the number of signal streams. Therefore, MMSE interference rejection followed by MLD detection is proposed. The proposed scheme reduces the complexity by a factor of 1/2M(NT-1) where NT is the number of interference signals with 2MQAM modulation. The effect of residual interference after the MMSE interference rejection is evaluated. Numerical results obtained through computer simulation and experiment show that the performance of the proposed scheme is about 4.0dB worse at a bit error rate (BER) of 10-3 than that of the joint MLD while its complexity is four times lower for QPSK signal streams. The BER performance degradation can be suppressed to about 2.5dB by adjusting the value of the coefficient in the MMSE matrix.

Indoor fingerprint location based on WiFi in large-scale indoor parking lots is more and more widely employed for vehicle lookup. However, the challenge is to ensure the location functionality because of the particularity and complexities of the indoor parking lot environment. To reduce the need to deploy of reference points (RPs) and the offline sampling workload, a partition-fitting fingerprint algorithm (P-FP) is proposed. To improve the location accuracy of the target, the PS-FP algorithm, a sampling importance resampling (SIR) particle filter with threshold based on P-FP, is further proposed. Firstly, the entire indoor parking lot is partitioned and the environmental coefficients of each partitioned section are gained by using the polynomial fitting model. To improve the quality of the offline fingerprint database, an error characteristic matrix is established using the difference between the fitting values and the actual measured values. Thus, the virtual RPs are deployed and C-means clustering is utilized to reduce the amount of online computation. To decrease the fluctuation of location coordinates, the SIR particle filter with a threshold setting is adopted to optimize the location coordinates. Finally, the optimal threshold value is obtained by comparing the mean location error. Test results demonstrated that PS-FP could achieve high location accuracy with few RPs and the mean location error is only about 0.7m. The cumulative distribution function (CDF) show that, using PS-FP, 98% of location errors are within 2m. Compared with the weighted K-nearest neighbors (WKNN) algorithm, the location accuracy by PS-FP exhibit an 84% improvement.

In this paper, an enhanced feathery receiver initiated transmission (eF-RIT) protocol is proposed for wireless smart utility network (Wi-SUN) systems with high traffic bi-directional communications such as emergency gas automatic meter infrastructure (AMI) cases. Firstly, we evaluate the conventional F-RIT protocol by simulation and experiment. The measurement results show that the IEEE 802.15.4e compliant conventional F-RIT protocol can achieve over 90% transmission success rates under the practical AMI specified conditions. However, the transmission success rates decline in high traffic environments. Detailed analyses indicate the degradation of the performance is caused by the timeout problem which occurs when the destination terminal is in the wait duration of the data transmission, and so does not transmit an RIT data request frame. To overcome this problem, we propose the eF-RIT protocol that suppresses the frequency of timeout occurrence. The proposed eF-RIT protocol is also evaluated by simulation and experiment. The evaluation results indicate that the proposed eF-RIT protocol reduces the incident of timeout by up to 31%, and achieves transmission success rates as high as 90% when the data generation rate is 1.0×10-2s-1.