In literatures, there are various constructions of frequency hopping sequence (FHS for short) sets with good Hamming correlations. Some papers employed only multiplicative groups of finite fields to construct FHS sets, while other papers implicitly used only additive groups of finite fields for construction of FHS sets. In this paper, we make use of both multiplicative and additive groups of finite fields simultaneously to present a construction of optimal FHS sets. The construction provides a new family of optimal (qm – 1,qm-t-1/r,rqt;qm-t-1/r+1) frequency hopping sequence sets archiving the Peng-Fan bound. Thus, some FHS sets constructed in literatures using either multiplicative groups or additive groups of finite fields are included in our family. In addition, some other FHS sets can be obtained via the well-known recursive construction through one-coincidence sequence set.

In this paper, we propose a new multi-edge metric-constrained quasi-cyclic progressive edge-growth algorithm (MM-QC-PEGA), which is suitable for constructing both single- and multi-weighted (binary) QC low-density parity-check (LDPC) codes with arbitrary lengths, rates, circulant sizes, and variable node (VN)-degree distributions. The MM-QC-PEGA is able to detect all cyclic-edge-set-minimum-virtual cycles (CMVCs), as it accurately computes the metric value of each CMVC with an a posteriori test. In addition, we propose a new greatest-common-divisor (GCD)-approximation for time efficiently approximating the metric value of a CMVC without a posteriori tests, and propose a new GCD-approximated MM-QC-PEGA (G-MM-QC-PEGA) by using the GCD-approximation to replace the a posteriori test involved in the MM-QC-PEGA. As a result, the G-MM-QC-PEGA is faster than the MM-QC-PEGA, and the CMVCs undetectable to the G-MM-QC-PEGA under multi- and single-weighted QC-LDPC code graphs have minimum lengths of eight and ten, respectively. Moreover, we propose a new masking technique that is efficient in masking the parity-check matrix consisting of an array of arbitrary circulants of the same size. Compared with the several existing works, our proposed algorithms could perform better or comparably in terms of avoiding generating small cycles and error performances. Our proposed algorithms somewhat perfect the works of QC-LDPC code construction.

In this letter, we consider the bit mapping (BM) design for regular low-density parity-check (LDPC) coded bit-interleaved coded modulation (BICM) schemes. We propose a check-node type distribution and develop multi-edge type extrinsic information transfer (EXIT) functions for the regular LDPC coded BICM schemes. Based on the EXIT functions, we propose a two-phase design method to generate the optimized practical BM in terms of the lowest decoding threshold for a given finite length LDPC code. Simulation results show that the proposed BM has a better decoding threshold compared to those of the existing works.

In order to evaluate the goodness of frequency hopping (FH) sequence design, the periodic Hamming correlation function is used as an important measure. Usually, the length of correlation window is shorter than the period of the chosen FH sequence, so the study of the partial Hamming correlation of FH sequence is particularly important. If an FH sequence or an FH sequence set has optimal partial Hamming correlation with respect to the partial Hamming correlation bound for all length of correlation window, then the FH sequence or FH sequence set is said to be strictly optimal. In this paper, we first prove that there is no strictly optimal FH sequence set of family size M and sequence length N over a frequency slot set of size q with respect to the partial Hamming correlation bound derived by Niu et al. when N > q2/M and q ≥ 2, and that by Cai et al. when N > q2/M and q ≥ 2N/N–2. Further, we define a special partition-type difference packing (DP) called [N,∇,Hla] PDP and give several classes of [N,∇,Hla] PDPs. Then we present a new construction of strictly optimal FH sequences. By choosing different PDPs, the FH sequences constructed can give new and flexible parameters. By utilizing this construction method recursively, we can obtain new [N,∇,Hl a] PDPs which lead to infinitely many classes of strictly optimal FH sequences with new parameters. Moreover, based upon an [N,∇,Hla] PDP we present a construction of strictly optimal FH sequence sets. By preceding construction method and recursive construction, we can also obtain infinite classes of strictly optimal FH sequence sets which can give new and flexible parameters.

This paper is concerned with a machine learning approach to cancel the interference for cognitive Internet of Things (C-IoT) in the concurrent spectrum access (CSA) model, where the C-IoT system is non-cooperative and has very limited knowledge on the interference. Our transceiver design uses an iterative processing structure, which consists of a linear estimator, a demodulation-and-decoding module, and a clustering module. In the clustering module, we employ modified expectation maximization (EM) based algorithms to estimate the interference under the knowledge of the modulation constraint (MC) of the interference. We show that this modified EM algorithm based receiver outperforms the original EM-based receiver, since the former is able to generate a more accurate clustering result by reducing the dimension of the parameter space. We further improve the performance of the iterative receiver by introducing the extrinsic information technique, with the resulting algorithm referred to as theextrinsic modulation constrained EM (Ext-MC-EM) algorithm. We show that the Ext-MC-EM algorithm based receiver considerably outperforms the counterpart iterative receivers, including the MC-EM algorithm.

In this letter, we propose a new low-density paritycheck coded scheme for two-user Gaussian multiple access channels (GMACs) with equal rate and equal average power constraints. In the proposed scheme, we divide a codeword into two parts with equal length and transmit them by using BPSK signals with two power levels. Two users use the two power levels alternatively to avoid ambiguity problem in two-user GMACs. We optimize the ratio between the two power levels to minimize the required average signalto- noise ratio for a given rate. We also design a joint decoding algorithm for our proposed scheme. Numerical results show that the proposed scheme has a better bit error rate performance, compared to the existing schemes.