This paper presents a new high-rate data encoder structure for Wake-Up Signals (WUS) in wireless networks that serve terminals equipped with low-power wake-up receivers. The encoder yields better missed detection performance compared to uncoded transmissions and prior solutions, whereas its contained complexity copes with low-power receivers' typcal limitations in memory size and processing capability. The encoder uses a maximum distance separable (MDS) or almost-MDS code in order to guarantee low false alarm probability. The terminal identity is encoded by a novel low-complexity method based on associated polynomials (AP) over Galois fields. A randomized rate-matching block selects a given number of consecutive symbols at a random position from the MDS codeword and encodes them by an error correction code. The obtained codeword is modulated and transmitted. Randomized rate-matching provides common randomness be-tween transmitter and receivers, which is needed in order to obtain vanishing false alarm probability according to the Identification via Channels framework [1]. The random number generators (RNG) within rate matching are initialized with a same seed at the transmitter and receivers. Thus, unlike prior solutions, sending transmitter-generated random indices within the WUS is no longer required. This allows usage of stronger error correction codes compared to prior solutions, thereby producing SNR gains larger than 4 dB in terms of missed detection compared to uncoded transmissions, and orders of magnitude false-alarm probability gains. Moreover, the RNG seed is kept confidential among network nodes, thereby preventing generation of counterfeit WUSs by potential attackers.

A wake-up signal (WUS) can be transmitted from the base station to the user equipment (UE) in order to power-on a UE that was put in sleep mode. The UE may have a dedicated radio receiver for the WUS, which is highly optimized for power efficient operation and the WUS preferably uses a simple waveform which can be non-coherently detected. Thus, multiplexing of WUSs on the same time-frequency resource cannot be done with classical code division multiplexing (CDM). We propose a new multiplexing method of WUSs which is performed prior to the modulator, which allows to use a non-coherently detected waveform. This can be formulated as an encoding problem and we discuss constructions of such multiplexing codes. In particular, we address methods with low complexity to demultiplex the WUSs. The results show that the proposed multiplexing scheme could outperform time division multiplexing (TDM).

This paper introduces a novel physical-layer method labelled as Multi-Modal Concurrent Transmission (MMCT) for efficient transmission of multiple data streams with different reliability-latency performance requirements. The MMCT arranges data from multiple streams within a same physical-layer transport block wherein stream-specific modulation and coding scheme (MCS) selection is combined with joint mapping of modulated codewords to Multiple-Input Multiple-Output spatial layers and frequency resources. Mapping to spatial-frequency resources with higher Signal-to-Noise Ratios (SNRs) provides the required performance boost for the more demanding streams. In tactile internet applications, wherein haptic feedback/actuation and audiovideo streams flow in parallel, the method provides significant SNR and spectral efficiency enhancements compared to conventional 3GPP New Radio (NR) transmission methods.

Deep neural network (DNN)-assisted channel coding designs, such as low-complexity neural decoders for existing codes, or end-to-end neural-network-based auto-encoder designs are gaining interest recently due to their improved performance and flexibility; particularly for communication scenarios in which high-performing structured code designs do not exist. Communication in the presence of feedback is one such communication scenario, and practical code design for feedback channels has remained an open challenge in coding theory for many decades. Recently, DNN-based designs have shown impressive results in exploiting feedback. In particular, generalized block attention feedback (GBAF) codes, which utilizes the popular transformer architecture, achieved significant improvement in terms of the block error rate (BLER) performance. However, previous works have focused mainly on passive feedback, where the transmitter observes a noisy version of the signal at the receiver. In this work, we show that GBAF codes can also be used for channels with active feedback. We implement a pair of transformer architectures, at the transmitter and the receiver, which interact with each other sequentially, and achieve a new state-of-the-art BLER performance, especially in the low SNR regime.

Ultra-reliable short-packet communication is a major challenge in future wireless networks with critical applications. To achieve ultra-reliable communications beyond 99.999%, this paper envisions a new interaction-based communication paradigm that exploits feedback from the receiver. We present AttentionCode, a new class of feedback codes leveraging deep learning (DL) technologies. The underpinnings of AttentionCode are three architectural innovations: AttentionNet, input restructuring, and adaptation to fading channels, accompanied by several training methods, including large-batch training, distributed learning, look-ahead optimizer, training-test signal-to-noise ratio (SNR) mismatch, and curriculum learning. The training methods can potentially be generalized to other wireless communication applications with machine learning. Numerical experiments verify that AttentionCode establishes a new state of the art among all DL-based feedback codes in both additive white Gaussian noise (AWGN) channels and fading channels. In AWGN channels with noiseless feedback, for example, AttentionCode achieves a block error rate (BLER) of 10−7 when the forward channel SNR is 0 dB for a block size of 50 bits, demonstrating the potential of AttentionCode to provide ultra-reliable short-packet communications.

Vehicle-to-vehicle (V2V) resource allocation (RA) schemes have been introduced in the cellular V2V (C-V2V) standard for sidelink (SL) communications to allow for an efficient sharing of the time-frequency resources in sub-6 GHz bands. However, the recent progress in connected and automated vehicles and the introduction of new bandwidth-eager mobility services are driving towards the use of millimeter-wave (mmW) frequencies (24.25-52.6 GHz). A characteristic of propagation at mmW frequencies is the severe path loss attenuation that can be compensated through beamforming. Therefore, its introduction adds a spatial dimension that must be considered in the design of RA schemes. The current fifth-generation (5G) RA standard for SL communication, which is inherited from the previous C-V2V standard, is not designed for directional communication and does not take into account the interference impact. Hence, this paper proposes a novel RA scheme to manage spatial-interference by adding the spatial dimension, i.e. the spatial beam directivity, and cooperation between vehicles for resource selection. The simulation results confirm that the three-dimensional cooperative RA (3D-CRA) has an average improvement of 10% in packet delivery ratio, 50% in collision probability, and 60% in channel busy ratio compared to the standard RA.

We introduce a new family of error correction codes based on sparse superposition called Quasi- Orthogonal} Sparse Superposition Codes (QO-SSC). The core of QO-SSC is a special structure of the SSC projection matrix which is obtained by concatenation of orthogonal submatrices. Concrete examples of QO-SCC constructions based on Zadoff- Chu sequences and Kerdock bent sequences are provided. A low-complexity iterative successive interference cancellation algorithm is proposed for QO-SSC decoding. Performance evaluations show that QO-SSC is an efficient solution for short- packet transmission at low signal-to-noise ratios, as it achieves lower block error rate than conventional coded modulation schemes, e.g., QPSK- modulated polar codes. As a further advantage, QO-SSC features a low PAPR when transmitted using OFDM waveforms.

We propose a novel Simultaneous Wireless Information and Power Transmission (SWIPT) scheme to enable a compatible multiplexing of energy and information based on the frequency that can be used with the state-of-art transceivers. In the proposed scheme, the transmitter superimposes a Direct-Current (DC) signal on Orthogonal Frequency-Division Multiplexing (OFDM) Radio Frequency (RF) signal to generate OFDM-DC signal for SWIPT where the OFDM part is used for information transmission and the DC signal is used for energy transfer. The power level of the DC signal is configured by a controller at the transmitter side. The corresponding receiver is constructed with direct-conversion-receiver front-end such that the DC signal is extracted using a low-pass filter whose bandwidth is configured based on the subcarrier spacing of the OFDM waveform and then fed to a voltage-to-current converter to generate current to charge a battery for energy storage. The OFDM signal without DC power signal is then fed to Analog-to-Digital (A/D) converter for information decoding. The numerical and simulation evaluations provide encouraging evidence in the favor of the proposed OFDM-DC scheme.

Superposed transmission on the broadcast channel delivers multiple private messages simultaneously to the intended users. Superposed transmission is employed in non-orthogonal multiple access to increase the aggregate throughput and connectivity of wireless cellular systems. Rate-adaptive constellation Expansion Multiple Access (REMA, a.k.a. RA-CEMA) is a non-orthogonal multiple access scheme which exhibits performance similar to the conventional superposed transmission schemes for transmission on the degraded broadcast channel, while requiring less complex signal processing and scheduling algorithms. This paper solves the problem of user scheduling and rate allocation for REMA. We pose the problem as a weighted sum-rate optimization and develop provably optimal algorithms for user selection and rate allocation with REMA broadcast-channel transmission. System-level evaluations show that our schemes outperform an LTE-A compliant orthogonal multiple access system and exhibit similar or better performance compared to other known non-orthogonal multiple access schemes.

A new non-orthogonal multiple access scheme performing simultaneous transmission to multiple users characterized by different signal-to-noise ratios is proposed. Different users are multiplexed by storing their codewords into a multiplexing matrix according to properly designed patterns and then mapping the columns of the matrix onto the symbols of a higher-order constellation. At the receiver, an interference cancellation algorithm is employed in order to achieve a higher spectral efficiency than orthogonal user multiplexing. Rate-Adaptive Constellation Expansion Multiple Access (RA-CEMA) is an alternative to conventional superposition coding as a solution for transmission on the degraded broadcast channel. It combines the benefits of an increased spectral efficiency with the advantages of reusing the coding and modulation schemes already used in contemporary communication systems, thereby facilitating its adoption in standards.

We propose an enhanced version of trellis coded multiple access (TCMA), an overloaded multiple access scheme that outperforms the original TCMA in terms of achieved spectral efficiency. Enhanced TCMA (ETCMA) performs simultaneous transmission of multiple data streams intended for users experiencing similar signal-to-noise ratios and can be employed both in the uplink and in the downlink of wireless systems, thus overcoming one of the main limitations of TCMA. Thanks to a new receiver algorithm, ETCMA is capable of delivering a significantly higher spectral efficiency. We show that ETCMA approaches the capacity of the Additive White Gaussian Noise channel for a wide range of signal-to-noise ratios.

Achieving higher aggregate data rates for many simultaneous users is considered as a fundamental challenge for the next generation of wireless systems. With low-density spreading (LDS), one could transmit information by overloading, i.e., using more spreading sequences than chips with reasonable implementation complexity. In this paper, we propose an improvement to the conventional LDS technique that consists in introducing a bit interleaver in the transmission scheme. Its role is to render the error bursts that appear at the output of the LDS detector into correctable patterns for the channel decoder. Numerical evaluations of the spectral efficiency show SNR improvements of more than 2dB when using convolutional codes in BI-LDS schemes. Slight improvements are also observed when turbo codes are employed.

In this paper we propose new capacity achieving modulation schemes for the peak-power limited Gaussian channel. Applying a multilayer approach to continuous phase modulations (CPM), we obtain schemes whose capacity approaches the capacity of the AWGN channel while exhibiting a low peak to average power ratio (PAPR). Moreover, thanks to the structure of CPM, the nonlinear characteristic of the RF power amplifier can be efficiently compensated with slight additional complexity. We compare multilayer CPM with APSK modulations and observe improvements both in capacity and PAPR.

In this paper we improve the spectral efficiency of continuous-phase modulations (CPM) when used in frequency-division multiplexing (FDM) systems with tight carrier frequency spacing. We show that significant improvements can be achieved applying a low-complexity iterative inter- channel interference (ICI) cancellation algorithm. Further improvements are obtained in coded CPM systems with joint ICI cancellation and iterative decoding.

The pragmatic approach to coded continuous-phase modulation (CPM) is proposed as a capacity-achieving low-complexity alternative to the serially concatenated CPM (SC-CPM) coding scheme. In this paper, we first perform a selection of the best spectrally efficient CPM modulations to be embedded into SC-CPM schemes. Then, we consider the pragmatic capacity (a.k.a. BICM capacity) of CPM modulations and optimize it through a careful design of the mapping between input bits and CPM waveforms. The so obtained schemes are cascaded with an outer serially concatenated convolutional code to form a pragmatic coded-modulation system. The resulting schemes exhibit performance very close to the CPM capacity without requiring iterations between the outer decoder and the CPM demodulator. As a result, the receiver exhibits reduced complexity and increased flexibility due to the separation of the demodulation and decoding functions.

The paper extends the pragmatic approach to coded continuous-phase modulation (CPM). It first proposes an optimization of the CPM capacity for given complexity and bandwidth efficiency. Then, the best CPM schemes are embedded into a pragmatic coded-modulation scheme, whose pragmatic capacity (a.k.a. BICM capacity) is maximized through a careful design of the mapping between input bits and CPM waveforms. The so obtained CPM schemes show a pragmatic capacity very close to the CPM capacity. An outer binary serially-concatenated convolutional code, cascaded with the CPM modulator through an interleaver, yields performance close to the pragmatic (and so to the CPM) capacity without requiring iterations between outer code and CPM modulator.

This correspondence presents an upper bound on the minimum distance of serially concatenated codes with interleaver where the inner code is a systematic recursive convolutional encoder and the outer code is any convolutional encoder. The resulting expression shows that the minimum distance of the concatenated code cannot grow more than O(K1-1/df(O)), where K is the information word length, and df(O)is the free distance of the outer code. The obtained upper bound is shown to agree with and, in some cases, improve over previously known results

In this paper, a concatenated coding scheme consisting of an outer algebraic block code performing hard decoding connected to an inner turbo code through a rectangular interleaver is analyzed. The performance of the concatenated code is evaluated through a semi-analytical approach, based on the expression of the word error probability at the output of the outer decoder as a function of the error statistics at the output of the turbo decoder estimated through simulation. The proposed technique yields results that depend on the size of the interleaver, and permits to obtain trade-offs between that size and the outer code characteristics.

A new upper bound on the minimum distance of turbo codes is derived. It improves over existing ones and shows that the minimum distance grows approximately with the base-3 logarithm of the information word length

This paper derives an upper bound on the minimum distance of serially concatenated convolutional codes. The resulting expression shows that their minimum distance cannot grow more than approximately K1-1/df(O), where K is the information word length, and df(O)is the free distance of the outer code

In this paper, a new upper bound on the minimum distance of turbo codes is derived. The new bound is obtained by construction of an undirected graph which reflects the characteristics of the constituent codes and the interleaver. The resulting expression shows that the minimum distance of a turbo code grows approximately with the base-3 logarithm of the information word length. The new bound is easy to compute, applies to rate k/sub 0//n/sub 0/ constituent encoders, and often improves over existing results.