New Lower Bounds on Aperiodic Ambiguity Function of Unimodular Sequences

This paper presents new aperiodic ambiguity function (AF) lower bounds of unimodular sequences under certain low ambiguity zone. Our key idea, motivated by the Levenshtein correlation bound, is to introduce two weight vectors associated to the delay and Doppler shifts, respectively, and then exploit the upper and lower bounds on the Frobenius norm of the weighted auto- and cross-AF matrices to derive these bounds. Furthermore, the inherent structure properties of aperiodic AF are also utilized in our derivation. The derived bounds are useful design guidelines for optimal AF shaping in modern communication and radar systems.

AFDM-SCMA: A Promising Waveform for Massive Connectivity over High Mobility Channels

This paper studies the affine frequency division multiplexing (AFDM)-empowered sparse code multiple access (SCMA) system, referred to as AFDM-SCMA, for supporting massive connectivity in high-mobility environments. First, by placing the sparse codewords on the AFDM chirp subcarriers, the input-output (I/O) relation of AFDM-SCMA systems is presented. Next, we delve into the generalized receiver design, chirp rate selection, and error rate performance of the proposed AFDM-SCMA. The proposed AFDM-SCMA is shown to provide a general framework and subsume the existing OFDM-SCMA as a special case. Third, for efficient transceiver design, we further propose a class of sparse codebooks for simplifying the I/O relation, referred to as I/O relation-inspired codebook design in this paper. Building upon these codebooks, we propose a novel iterative detection and decoding scheme with linear minimum mean square error (LMMSE) estimator for both downlink and uplink channels based on orthogonal approximate message passing principles. Our numerical results demonstrate the superiority of the proposed AFDM-SCMA systems over OFDM-SCMA systems in terms of the error rate performance. We show that the proposed receiver can significantly enhance the error rate performance while reducing the detection complexity.

Here Is Not There: Measuring Entailment-Based Trajectory Similarity for Location-Privacy Protection and Beyond

While the paths humans take play out in social as well as physical space, measures to describe and compare their trajectories are carried out in abstract, typically Euclidean, space. When these measures are applied to trajectories of actual individuals in an application area, alterations that are inconsequential in abstract space may suddenly become problematic once overlaid with geographic reality. In this work, we present a different view on trajectory similarity by introducing a measure that utilizes logical entailment. This is an inferential perspective that considers facts as triple statements deduced from the social and environmental context in which the travel takes place, and their practical implications. We suggest a formalization of entailment-based trajectory similarity, measured as the overlapping proportion of facts, which are spatial relation statements in our case study. With the proposed measure, we evaluate LSTM-TrajGAN, a privacy-preserving trajectory-generation model. The entailment-based model evaluation reveals potential consequences of disregarding the rich structure of geographic space (e.g., miscalculated insurance risk due to regional shifts in our toy example). Our work highlights the advantage of applying logical entailment to trajectory-similarity reasoning for location-privacy protection and beyond.

BER Analysis of SCMA-OFDM Systems in the Presence of Carrier Frequency Offset

Sparse code multiple access (SCMA) building upon orthogonal frequency division multiplexing (OFDM) is a promising wireless technology for supporting massive connectivity in future machine-type communication networks. However, the sensitivity of OFDM to carrier frequency offset (CFO) poses a major challenge because it leads to orthogonality loss and incurs intercarrier interference (ICI). In this paper, we investigate the bit error rate (BER) performance of SCMA-OFDM systems in the presence of CFO over both Gaussian and multipath Rayleigh fading channels. We first model the ICI in SCMA-OFDM as Gaussian variables conditioned on a single channel realization for fading channels. The BER is then evaluated by averaging over all codeword pairs considering the fading statistics. Through simulations, we validate the accuracy of our BER analysis and reveal that there is a significant BER degradation for SCMA-OFDM systems when the normalized CFO exceeds 0.02.

Deep Learning Assisted Multiuser MIMO Load Modulated Systems for Enhanced Downlink mmWave Communications

This paper is focused on multiuser load modulation arrays (MU-LMAs) which are attractive due to their low system complexity and reduced cost for millimeter wave (mmWave) multi-input multi-output (MIMO) systems. The existing precoding algorithm for downlink MU-LMA relies on a sub-array structured (SAS) transmitter which may suffer from decreased degrees of freedom and complex system configuration. Furthermore, a conventional LMA codebook with codewords uniformly distributed on a hypersphere may not be channel-adaptive and may lead to increased signal detection complexity. In this paper, we conceive an MU-LMA system employing a full-array structured (FAS) transmitter and propose two algorithms accordingly. The proposed FAS-based system addresses the SAS structural problems and can support larger numbers of users. For LMA-imposed constant-power downlink precoding, we propose an FAS-based normalized block diagonalization (FAS-NBD) algorithm. However, the forced normalization may result in performance degradation. This degradation, together with the aforementioned codebook design problems, is difficult to solve analytically. This motivates us to propose a Deep Learning-enhanced (FAS-DL-NBD) algorithm for adaptive codebook design and codebook-independent decoding. It is shown that the proposed algorithms are robust to imperfect knowledge of channel state information and yield excellent error performance. Moreover, the FAS-DL-NBD algorithm enables signal detection with low complexity as the number of bits per codeword increases.

Flag Sequence Set Design for Low-Complexity Delay-Doppler Estimation

This paper studies Flag sequences for lowcomplexity delay-Doppler estimation by exploiting their distinctive peak-curtain ambiguity functions (AFs). Unlike the existing Flag sequence designs that are limited to prime lengths and periodic auto-AFs, we aim to design Flag sequence sets of arbitrary lengths and with low (nontrivial) periodic/aperiodic auto- and cross-AFs. Since every Flag sequence consists of a Curtain sequence and a Peak sequence, we first investigate the algebraic design of zone-based Curtain sequence sets of arbitrary lengths. Our proposed design gives rise to novel Curtain sequence sets with ideal curtain auto-AFs and low/zero cross-AFs within the delay-Doppler zone of interest. Leveraging these Curtain sequence sets, two optimization problems are formulated to minimize the summed customized weighted integrated sidelobe level (SCWISL) of the Flag sequence set. Accelerated Parallel Partially Majorization-Minimization Algorithms are proposed to jointly optimize the transmit Flag sequences and matched/mismatched reference sequences stored in the receiver. Simulations demonstrate that our proposed Flag sequences lead to improved SCWISL and customized peak-to-max-sidelobe ratio compared with the existing Flag sequences. Additionally, our Flag sequences under Flag method exhibit Mean Squared Errors that approach the Cramer-Rao Lower Bound and the Sampling Bound at high signal-to-noise power ratios.

Novel Power-Imbalanced Dense Codebooks for Reliable Multiplexing in Nakagami Channels

This paper studies enhanced dense code multiple access (DCMA) system design for downlink transmission over the Nakagami-$m$ fading channels. By studying the DCMA pairwise error probability (PEP) in a Nakagami-$m$ channel, a novel design metric called minimum logarithmic sum distance (MLSD) is first derived. With respect to the proposed MLSD, we introduce a new family of power-imbalanced dense codebooks by deleting certain rows of a special non-unimodular circulant matrix. Simulation results demonstrate that our proposed dense codebooks lead to both larger minimum Euclidean distance and MLSD, thus yielding significant improvements of error performance over the existing sparse code multiple access and conventional unimodular DCMA schemes in Nakagami-$m$ fading channels under different overloading factors.

Enhancing Signal Space Diversity for SCMA Over Rayleigh Fading Channels

Sparse code multiple access (SCMA) is a promising technique for the enabling of massive connectivity in future machine-type communication networks, but it suffers from a limited diversity order which is a bottleneck for significant improvement of error performance. This paper aims for enhancing the signal space diversity of sparse code multiple access (SCMA) by introducing quadrature component delay to the transmitted codeword of a downlink SCMA system in Rayleigh fading channels. Such a system is called SSD-SCMA throughout this work. By looking into the average mutual information (AMI) and the pairwise error probability (PEP) of the proposed SSD-SCMA, we develop novel codebooks by maximizing the derived AMI lower bound and a modified minimum product distance (MMPD), respectively. The intrinsic asymptotic relationship between the AMI lower bound and proposed MMPD based codebook designs is revealed. Numerical results show significant error performance improvement in the both uncoded and coded SSD-SCMA systems.

OTFS-SCMA: A Downlink NOMA Scheme for Massive Connectivity in High Mobility Channels

This paper studies a downlink system that combines orthogonal-time-frequency-space (OTFS) modulation and sparse code multiple access (SCMA) to support massive connectivity in high-mobility environments. We propose a cross-domain receiver for the considered OTFS-SCMA system which efficiently carries out OTFS symbol estimation and SCMA decoding in a joint manner. This is done by iteratively passing the extrinsic information between the time domain and the delay-Doppler (DD) domain via the corresponding unitary transformation to ensure the principal orthogonality of errors from each domain. We show that the proposed OTFS-SCMA detection algorithm exists at a fixed point in the state evolution when it converges. To further enhance the error performance of the proposed OTFS-SCMA system, we investigate the cooperation between downlink users to exploit the diversity gains and develop a distributed cooperative detection (DCD) algorithm with the aid of belief consensus. Our numerical results demonstrate the effectiveness and convergence of the proposed algorithm and show an increased spectral efficiency compared to the conventional OTFS transmission.

Jamming Modulation: An Active Anti-Jamming Scheme

Providing quality communications under adversarial electronic attacks, e.g., broadband jamming attacks, is a challenging task. Unlike state-of-the-art approaches which treat jamming signals as destructive interference, this paper presents a novel active anti-jamming (AAJ) scheme for a jammed channel to enhance the communication quality between a transmitter node (TN) and receiver node (RN), where the TN actively exploits the jamming signal as a carrier to send messages. Specifically, the TN is equipped with a programmable-gain amplifier, which is capable of re-modulating the jamming signals for jamming modulation. Considering four typical jamming types, we derive both the bit error rates (BER) and the corresponding optimal detection thresholds of the AAJ scheme. The asymptotic performances of the AAJ scheme are discussed under the high jamming-to-noise ratio (JNR) and sampling rate cases. Our analysis shows that there exists a BER floor for sufficiently large JNR. Simulation results indicate that the proposed AAJ scheme allows the TN to communicate with the RN reliably even under extremely strong and/or broadband jamming. Additionally, we investigate the channel capacity of the proposed AAJ scheme and show that the channel capacity of the AAJ scheme outperforms that of the direct transmission when the JNR is relatively high.