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We show that Gallager's ensemble of Low-Density Parity Check (LDPC) codes achieves list-decoding capacity with high probability. These are the first graph-based codes shown to have this property. This result opens up a potential avenue towards truly linear-time list-decodable codes that achieve list-decoding capacity. Our result on list decoding follows from a much more general result: any $\textit{local}$ property satisfied with high probability by a random linear code is also satisfied with high probability by a random LDPC code from Gallager's distribution. Local properties are properties characterized by the exclusion of small sets of codewords, and include list-decodability, list-recoverability and average-radius list-decodability. In order to prove our results on LDPC codes, we establish sharp thresholds for when local properties are satisfied by a random linear code. More precisely, we show that for any local property $\mathcal{P}$, there is some $R^*$ so that random linear codes of rate slightly less than $R^*$ satisfy $\mathcal{P}$ with high probability, while random linear codes of rate slightly more than $R^*$, with high probability, do not. We also give a characterization of the threshold rate $R^*$.

In this work, we introduce the pattern-domain pilot design paradigm based on a "superposition of orthogonal-building-blocks" with significantly larger contention space to enhance the massive machine-type communications (mMTC) random access (RA) performance in massive multiple-input multiple-output (MIMO) systems.Specifically, the pattern-domain pilot is constructed based on the superposition of $L$ cyclically-shifted Zadoff-Chu (ZC) sequences. The pattern-domain pilots exhibit zero correlation values between non-colliding patterns from the same root and low correlation values between patterns from different roots. The increased contention space, i.e., from N to $\binom{N}{L}$, where $\binom{N}{L}$ denotes the number of all L-combinations of a set N, and low correlation valueslead to a significantly lower pilot collision probability without compromising excessively on channel estimation performance for mMTC RA in massive MIMO systems.We present the framework and analysis of the RA success probability of the pattern-domain based scheme with massive MIMO systems.Numerical results demonstrate that the proposed pattern division random access (PDRA) scheme achieves an appreciable performance gain over the conventional one,while preserving the existing physical layer virtually unchanged. The extension of the "superposition of orthogonal-building-blocks" scheme to "superposition of quasi-orthogonal-building-blocks" is straightforward.

This paper introduces a novel information-theoretic approach for studying the effects of mutual coupling (MC), between the transmit and receive antennas, on the overall performance of single-input-single-output (SISO) near-field communications. By incorporating the finite antenna size constraint using Chu's theory and under the assumption of canonical-minimum scattering, we derive the MC between two radiating volumes of fixed sizes. Expressions for the self and mutual impedances are obtained by the use of the reciprocity theorem. Based on a circuit-theoretic two-port model for SISO radio communication systems, we establish the achievable rate for a given pair of transmit and receive antenna sizes, thereby providing an upper bound on the system performance under physical size constraints. Through the lens of these findings, we shed new light on the influence of MC on the information-theoretic limits of near-field communications using compact antennas.

In recent years, the concept of continuous-aperture MIMO (CAP-MIMO) is reinvestigated to achieve improved communication performance with limited antenna apertures. Unlike the classical MIMO composed of discrete antennas, CAP-MIMO has a continuous antenna surface, which is expected to generate any current distribution (i.e., pattern) and induce controllable spatial electromagnetic waves. In this way, the information can be modulated on the electromagnetic waves, which makes it promising to approach the ultimate capacity of finite apertures. The pattern design is the key factor to determine the system performance of CAP-MIMO, but it has not been well studied in the literature. In this paper, we propose the pattern-division multiplexing to design the patterns for CAP-MIMO. Specifically, we first derive the system model of a typical CAP-MIMO system, which allows us to formulate the capacity maximization problem. Then we propose a general pattern-division multiplexing technique to transform the design of continuous pattern functions to the design of their projection lengths on finite orthogonal bases, which is able to overcome the design challenge of continuous functions. Based on this technique, we further propose an alternating optimization based pattern design scheme to solve the formulated capacity maximization problem. Simulation results show that, the capacity achieved by the proposed scheme is about 260% higher than that achieved by the benchmark scheme, which demonstrates the effectiveness of the proposed pattern-division multiplexing for CAP-MIMO.

We analyze whether a multidimensional parity check (MDPC) or a Reed-Solomon (RS) code in combination with an auxiliary channel can improve the throughput and extend the THz transmission distance. While channel quality is addressed by various coding approaches, and an effective THz system configuration is enabled by other approaches with additional channels, their combination is new with the potential for significant improvements in quality of the data transmission. Our specific solution is designed to correct data bits at the physical layer by using a low complexity erasure code (MDPC or RS), whereby original and parity data are transferred over two separate and parallel THz channels, including one main channel and one additional channel. The results are theoretically analyzed to see that our new solution can improve throughput, support higher modulation levels and transfer data over the longer distances with THz communications.

Guessing Random Additive Noise Decoding (GRAND) is a universal decoding algorithm that has been recently proposed as a practical way to perform maximum likelihood decoding. It generates a sequence of possible error patterns and applies them to the received vector, checking if the result is a valid codeword. Ordered reliability bits GRAND (ORBGRAND) improves on GRAND by considering soft information received from the channel. Both GRAND and ORBGRAND have been implemented in hardware, focusing on average performance, sacrificing worst case throughput and latency. In this work, an improved pattern schedule for ORBGRAND is proposed. It provides $>0.5$dB gain over the standard schedule at a block error rate $\le 10^{-5}$, and outperforms more complex GRAND flavors with a fraction of the complexity. The proposed schedule is used within a novel code-agnositic decoder architecture: the decoder guarantees fixed high throughput and low latency, making it attractive for latency-constrained applications. It outperforms the worst-case performance of decoders by orders of magnitude, and outperforms many best-case figures. Decoding a code of length 128, it achieves a throughput of $79.21$Gb/s with $58.49$ns latency, and of $69.61$Gb/s with $40.58$ns latency, yielding better energy efficiency and comparable area efficiency with respect to the state of the art.

Spectrally efficient communication is studied for short-reach fiber-optic links with chromatic dispersion (CD) and receivers that employ direction-detection and oversampling. Achievable rates and symbol error probabilities are computed by using auxiliary channels that account for memory in the sampled symbol strings. Real-alphabet bipolar and complex-alphabet symmetric modulations are shown to achieve significant energy gains over classic intensity modulation. Moreover, frequency-domain raised-cosine (FD-RC) pulses outperform time-domain RC (TD-RC) pulses in terms of spectral efficiency for two scenarios. First, if one shares the spectrum with other users then inter-channel interference significantly reduces the TD-RC rates. Second, if there is a transmit filter to avoid interference then the detection complexity of FD-RC and TD-RC pulses is similar but FD-RC achieves higher rates.

Photon counting detectors such as single-photon avalanche diode (SPAD) arrays can be utilized to improve the sensitivity of optical wireless communication (OWC) systems. However, the achievable data rate of SPAD-based OWC systems is strongly limited by the nonlinearity induced by SPAD dead time. In this work, the performances of SPAD receivers for two different modulation schemes, namely, on-off keying (OOK) and orthogonal frequency division multiplexing (OFDM), are compared demonstrating contrasting optimal regimes of operation. We employ nonlinear equalization and peak-to-average power ratio optimization by adjusting the OFDM clipping level to achieve record experimental data rates of up to 5 Gbps. In particular, the experimental results demonstrate the achievable data rates of 3.22 Gbps and 5 Gbps when OOK and OFDM are employed, respectively. It is also illustrated that to achieve the best data rate performance over a wide range of received power, adaptive switching between OOK and OFDM may be utilized.

Queue length violation probability, i.e., the tail distribution of the queue length, is a widely used statistical quality-of-service (QoS) metric in wireless communications. Many previous works conducted tail distribution analysis on the control policies with the assumption that the condition of the large deviations theory (LDT) is satisfied. LDT indicates that the tail distribution of the queue length has a linear-decay-rate exponent. However, there are many control policies which do not meet that assumption, while the optimal control policy may be included in these policies. In this paper, we put our focus on the analysis of the tail distribution of the queue length from the perspective of cross-layer design in wireless link transmission. Specifically, we divide the wireless link transmission systems into three scenarios according to the decay rate of the queue-length tail distribution with the finite average power consumption. A heuristic policy is conceived to prove that the arbitrary-decay-rate tail distribution with the finite average power consumption exists in Rayleigh fading channels. Based on this heuristic policy, we generalize the analysis to Nakagami-m fading channels. Numerical results with approximation validate our analysis.

It is a practical research topic how to deal with multi-device audio inputs by a single acoustic scene classification system with efficient design. In this work, we propose Residual Normalization, a novel feature normalization method that uses frequency-wise normalization % instance normalization with a shortcut path to discard unnecessary device-specific information without losing useful information for classification. Moreover, we introduce an efficient architecture, BC-ResNet-ASC, a modified version of the baseline architecture with a limited receptive field. BC-ResNet-ASC outperforms the baseline architecture even though it contains the small number of parameters. Through three model compression schemes: pruning, quantization, and knowledge distillation, we can reduce model complexity further while mitigating the performance degradation. The proposed system achieves an average test accuracy of 76.3% in TAU Urban Acoustic Scenes 2020 Mobile, development dataset with 315k parameters, and average test accuracy of 75.3% after compression to 61.0KB of non-zero parameters. The proposed method won the 1st place in DCASE 2021 challenge, TASK1A.