Search

We consider construction of deletion and substitution correcting codes with low redundancy and efficient encoding/ decoding. First, by simplifying the method of Sima et al. (ISIT 2020), we construct a family of binary single-deletion $s$ -substitution correcting codes with redundancy $(s+1) (2s+1)\log _{2} n+o(\log _{2} n)$ and encoding complexity $O(n^{2})$ , where $n$ is the blocklength of the code and $s\geq 1$. The construction can be viewed as a generalization of Smagloy et al.’s construction (ISIT 2020), and for the special case of $s=1$ , our construction is a slight improvement in redundancy of the existing works. Further, we modify the syndrome compression technique by combining a precoding process and construct a family of systematic $t$ -deletion $s$ -substitution correcting codes with polynomial time encoding/decoding algorithms for both binary and nonbinary alphabets, where $t\geq 1$ and $s\geq 1$. Specifically, our binary $t$ -deletion $s$ -substitution correcting codes of length $n$ have redundancy $(4t+3s)\log _{2}n+o(\log _{2}n)$ , whereas, for $q$ being a prime power, the redundancy of $q$ -ary $t$ -deletion $s$ -substitution codes is asymptotically $\left({4t+4s-1-\lfloor \frac {2s-1}{q}\rfloor }\right)\vphantom {{\lfloor \frac {2s-1}{q}\rfloor }_{j}}\log _{q} n + o(\log _{q}n)$ as $n\to \infty $. We also construct a family of binary systematic $t$ -deletion correcting codes (i.e., $s=0$) with redundancy $(4t-1)\log _{2} n+o(\log _{2} n)$. The proposed constructions improve upon the redundancy of the state-of-the-art constructions. [ABSTRACT FROM AUTHOR]

This article proposes a new cooperation framework of energy storage sharing that comprises prosumers, energy storage providers (ESPs), and a middle agent to achieve social energy optimality. In this framework, the prosumers share multiple energy storages of the ESPs via the agent. An energy sharing optimization problem minimizing the total energy cost is formulated involving the energy storage operation, the shiftable load schedule, and the energy trading with the utility. To solve the problem, a fast alternating direction multiplier method (ADMM) with restart which converges faster than traditional ADMM is adopted. Furthermore, a clearing scheme, named as an ideal profit realization ratio distribution model is introduced to distribute the participants’ net profits fairly. Simulation results show that the energy costs can be substantially reduced, and the net profit distribution is relatively fairer compared with the widely used Nash bargaining scheme, which ensures the feasibility of our framework in real applications. [ABSTRACT FROM AUTHOR]

In this communication, a dual polarized (DP) stacked patch filtenna (filtering antenna) with a wide stopband is developed for tile array applications. The bandpass filtering property is realized by improving the feeding network and patch without adding extra bandpass circuit or size. An elaborate feeding structure with complementary pair of a short-circuited stub and an open-circuited stub (CSSOS) is developed, which generates two transmission nulls effectively enhancing the selectivity and suppressing the harmonic. Moreover, CSSOS has a small size and broadens the impedance bandwidth apparently by introducing an in-band resonance. By properly etching four U-shaped slots on the driven patch, a radiation null in the upper stopband is also generated. The nulls generated by the two approaches can be adjusted independently in wide ranges. For further harmonic suppression, bandstop striplines (BSSs) with ultralow insertion loss are developed. Measured results show that the filtenna performs a wide operating band (3.10–3.95 GHz) and a wide stopband up to 8 GHz with a rejection level higher than 16 dB. Besides, a 32-element tile phased array employing the filtennas is also fabricated and measured. A compact configuration, high selectivity, and good beam steering capacity are exhibited. [ABSTRACT FROM AUTHOR]

In this paper, we propose a framework of the mutual information-maximizing (MIM) quantized decoding for low-density parity-check (LDPC) codes by using simple mappings and fixed-point additions. Our decoding method is generic in the sense that it can be applied to LDPC codes with arbitrary degree distributions, and can be implemented based on either the belief propagation (BP) algorithm or the min-sum (MS) algorithm. In particular, we propose the MIM density evolution (MIM-DE) to construct the lookup tables (LUTs) for the node updates. The computational complexity and memory requirements are discussed and compared to the LUT decoder variants. For applications with low-latency requirement, we consider the layered schedule to accelerate the convergence speed of decoding quasi-cyclic LDPC codes. In particular, we develop the layered MIM-DE to design the LUTs based on the MS algorithm, leading to the MIM layered quantized MS (MIM-LQMS) decoder. An optimization method is further introduced to reduce the memory requirement for storing the LUTs. Simulation results show that the MIM quantized decoders outperform the state-of-the-art LUT decoders in the waterfall region with both 3-bit and 4-bit precision over the additive white Gaussian noise channels. For small decoding iterations, the MIM quantized decoders also achieve a faster convergence speed compared to the benchmarks. Moreover, the 4-bit MIM-LQMS decoder can approach the error performance of the floating-point layered BP decoder within 0.3 dB in the moderate-to-high SNR regions, over both the AWGN channels and the fast fading channels. [ABSTRACT FROM AUTHOR]

In this letter, we propose a two-stage design method to construct memory efficient mutual information-maximizing quantized min-sum (MIM-QMS) decoder for rate-compatible low-density parity-check (LDPC) codes. We first develop a modified density evolution to design a unique set of lookup tables (LUTs) that can be used for rate-compatible LDPC codes. The constructed LUTs are optimized based on their discrepancy values and a merge function to reduce the memory requirement. Numerical results show that the proposed rate-compatible MIM-QMS decoder can reduce the memory requirement for decoding by up to 94.92 % compared to the benchmark rate-compatible LUT-based decoder with generally faster convergence speed. In addition, the proposed decoder can approach the performance of the floating-pointing belief propagation decoder within 0.15 dB. [ABSTRACT FROM AUTHOR]

Consider the computations at a node in a message passing algorithm. Assume that the node has incoming and outgoing messages $\mathbf {x} = (x_{1}, x_{2}, \ldots, x_{n})$ and $\mathbf {y} = (y_{1}, y_{2}, \ldots, y_{n})$ , respectively. In this paper, we investigate a class of structures that can be adopted by the node for computing $\mathbf {y}$ from $\mathbf {x}$ , where each $y_{j}, j = 1, 2, \ldots, n$ is computed via a binary tree with leaves $\mathbf {x}$ excluding $x_{j}$. We make three main contributions regarding this class of structures. First, we prove that the minimum complexity of such a structure is $3n - 6$ , and if a structure has such complexity, its minimum latency is $\delta + \lceil \log (n-2^{\delta }) \rceil $ with $\delta = \lfloor \log (n/2) \rfloor $ , where the logarithm always takes base two. Second, we prove that the minimum latency of such a structure is $\lceil \log (n-1) \rceil $ , and if a structure has such latency, its minimum complexity is $n \log (n-1)$ when $n-1$ is a power of two. Third, given $(n, \tau)$ with $\tau \geq \lceil \log (n-1) \rceil $ , we propose a construction for a structure which we conjecture to have the minimum complexity among structures with latencies at most $\tau $. Our construction method runs in $O(n^{3} \log ^{2}(n))$ time, and the obtained structure has complexity at most (generally much smaller than) $n \lceil \log (n) \rceil - 2$. [ABSTRACT FROM AUTHOR]

Green scheduling in the manufacturing industry has attracted increasing attention in academic research and industrial applications with a focus on energy saving. As a typical scheduling problem, the no-wait flow-shop scheduling has been extensively studied due to its wide industrial applications. However, energy consumption is usually ignored in the study of typical scheduling problems. In this article, a two-stage cooperative evolutionary algorithm with problem-specific knowledge called TS-CEA is proposed to address energy-efficient scheduling of the no-wait flow-shop problem (EENWFSP) with the criteria of minimizing both makespan and total energy consumption. In TS-CEA, two constructive heuristics are designed to generate a desirable initial solution after analyzing the properties of the problem. In the first stage of TS-CEA, an iterative local search strategy (ILS) is employed to explore potential extreme solutions. Moreover, a hybrid neighborhood structure is designed to improve the quality of the solution. In the second stage of TS-CEA, a mutation strategy based on critical path knowledge is proposed to extend the extreme solutions to the Pareto front. Moreover, a co-evolutionary closed-loop system is generated with ILS and mutation strategies in the iteration process. Numerical results demonstrate the effectiveness and efficiency of TS-CEA in solving the EENWFSP. [ABSTRACT FROM AUTHOR]

In this article, under a general cost function C, we present a dynamic programming (DP) method to obtain an optimal sequential deterministic quantizer (SDQ) for q-ary input discrete memoryless channel (DMC). The DP method has complexity O(q (N-M)2M), where N and M are the alphabet sizes of the DMC output and quantizer output, respectively. Then, starting from the quadrangle inequality, two techniques are applied to reduce the DP method’s complexity. One technique makes use of the Shor-Moran-Aggarwal-Wilber-Klawe (SMAWK) algorithm and achieves complexity O(q (N−M) M). The other technique is much easier to be implemented and achieves complexity O(q (N2−M2)). We further derive a sufficient condition under which the optimal SDQ is optimal among all quantizers and the two techniques are applicable. This generalizes the results in the literature for binary-input DMC. Next, we show that the cost function of α-mutual information (α−MI)-maximizing quantizer belongs to the category of C. We further prove that under a weaker condition than the sufficient condition we derived, the aforementioned two techniques are applicable to the design of α−MI-maximizing quantizer. Finally, we illustrate the particular application of our design method to practical pulse-amplitude modulation systems. [ABSTRACT FROM AUTHOR]