We revisit the Gaussian broadcast channel (GBC) and explore the rate region achieved by purely discrete inputs with treating interference as noise (TIN) decoding. Specifically, we introduce a simple scheme based on superposition coding with identically and independently distributed (i.i.d.) inputs drawn from discrete constellations, e.g., pulse amplitude modulations (PAM). Most importantly, we prove that the resulting achievable rate region under TIN decoding is within a constant gap to the capacity region of the GBC, where the gap is independent of all channel parameters. In addition, we show via simulation that the weak user can achieve a higher rate with PAM than with Gaussian signaling in some cases.

Wireless backhauling is envisioned to play a pivotal role in 6G non-terrestrial networks (NTNs) due to its ability to deliver cable-free connectivity between edge nodes and gateways. However, the dynamic network topology and time-varying channels inherent to NTNs pose significant challenges for real-time network status monitoring. To address these challenges, we propose PhyINT, a novel in-band network telemetry approach that collects telemetry data at the physical layer for time-slotted NTNs. PhyINT allows network nodes to encode telemetry data onto resource elements (REs) in a distributed manner. Since REs are consistently available in every time slot, regardless of wireless channel variability, the encoding process can be made highly predictable and faithfully reconstructed at the gateway for decoding. Moreover, we formulate a multi-objective optimization problem that jointly minimizes the resource consumption and the telemetry collection completion latency. Extensive simulations across NTNs demonstrate that PhyINT significantly outperforms existing methods in reliability, latency, and goodput.

In this work, we propose the orthogonal delay-Doppler (DD) division multiplexing (ODDM) modulation with frequency modulated continuous wave (FMCW) (ODDM-FMCW) waveform to enable integrated sensing and communication (ISAC) with a low peak-to-average power ratio (PAPR). We first propose a square-root-Nyquist-filtered FMCW (SRN-FMCW) waveform to address limitations of conventional linear FMCW waveforms in ISAC systems. To better integrate with ODDM, we generate SRN-FMCW by embedding symbols in the DD domain, referred to as a DD-SRN-FMCW frame. A DD chirp compression receiver is designed to obtain the channel response efficiently. Next, we construct the proposed ODDM-FMCW waveform for ISAC by superimposing a DD-SRN-FMCW frame onto an ODDM data frame. A comprehensive performance analysis of the ODDM-FMCW waveform is presented, covering peak-to-average power ratio, spectrum, ambiguity function, and Cramér-Rao bound for delay and Doppler estimation. Numerical results show that the proposed ODDM-FMCW waveform delivers excellent ISAC performance in terms of root mean square error for sensing and bit error rate for communications.

In this paper, we investigate the fundamental trade-off between communication and sensing performance ofad hocintegrated sensing and communication (ISAC) wireless networks. Specifically, we consider thatnnodes are randomly located in an extended network with areanand transmit ISAC signals. Under the pure path loss channel gain model and the condition that the transmission power scales according to the communication distance, we fully characterize the optimal scaling law trade-off between throughput and sensing distance by proposing an achievable scheme and proving its converse. Our results can be interpreted as follows: by reducing the throughput by a factor of a function ofn, the sensing range order improves according to the same function ofn, raised to the power of the ratio between the path loss factors in communication and sensing. We prove that the same result also holds true for ISAC networks with random fading, despite the uncertainty on the connectivity and power level created by random fading. In addition, we show that the scaling law tradeoff cannot be improved by allowing the transmission power and communication distance to scale freely. To the best of our knowledge, this is the first work formally formulating and characterizing the communication and sensing performance scaling law tradeoff ofad hocISAC networks.

Orthogonal delay-Doppler (DD) division multiplexing (ODDM) modulation has recently been proposed as a promising paradigm for communications in doubly-selective channels. In this work, we propose a novel ODDM with frequency modulated continuous wave (FMCW) (ODDM-FMCW) signal to enable integrated sensing and communication (ISAC) with a low peak-to-average power ratio (PAPR). We first propose the DD-domain embedded root-raised-cosine filtered FMCW (DD-RRC-FMCW) signal, where digital chirp compression is introduced for efficient radar signal processing. By superimposing this signal onto an ODDM data frame, we obtain the ODDM-FMCW signal for the proposed ISAC system. Next, we introduce a modified orthogonal matching pursuit algorithm for data-aided sensing. The algorithm is then combined with the soft successive interference cancellation with minimum mean square error detector to perform joint channel estimation and data detection. Our numerical results show that the proposed ODDM-FMCW signal delivers excellent normalized mean square error and bit error rate performance for ISAC.

In this paper, we investigate the communication and sensing performance tradeoff of ad hoc integrated sensing and communication (ISAC) wireless networks. Specifically, we consider that$n$nodes are randomly located in an extended network with area$n$and transmit ISAC signals. Our goal is to answer the following questions: what is the tradeoff between the throughput and sensing range of an ISAC network and how does it scale with the network size or node numbers? Under the condition that the transmission power scales according to the communication distance, we fully characterize the scaling law tradeoff between throughput and sensing distance by proposing an achievable scheme and proving its converse. Interestingly, our results reveal that by reducing the throughput by a factor of a function of$n$, the sensing range order improves according to the same function of$n$, raised to the power of the ratio between the path loss factors in communication and sensing. We also show that the scaling law tradeoff cannot be improved by allowing the transmission power and communication distance to scale differently. To the best of our knowledge, this is the first work formally formulating and characterizing the communication and sensing performance scaling law tradeoff of ad hoc ISAC networks.

This paper presents a new class of spatially coupled turbo-like codes (SC-TCs), namely half spatially coupled braided convolutional codes (HSC-BCCs) and half spatially coupled parallel concatenated codes (HSC-PCCs). Different from the conventional SC-TCs, the proposed codes have simpler and deterministic coupling structures. Most notably, the coupling of HSC-BCCs is performed by re-encoding the whole coupling sequence in the component encoder of one time instant, rather than spreading the coupling bits to component encoders of multiple time instants. This simplification not only addresses the window decoding threshold loss issue in existing BCCs, but also allows the proposed codes to attain very close-to-capacity performance with a coupling memory as small as 2. Both theoretical and numerical results are provided to demonstrate the performance advantages of the proposed codes over existing spatially coupled codes.

The orthogonal time frequency space with index modulation (OTFS-IM) offers flexible tradeoffs between spectral efficiency (SE) and bit error rate (BER) in doubly selective fading channels. While OTFS-IM schemes demonstrated such potential, a persistent challenge lies in the detection complexity. To address this problem, we propose the hierarchical mode-based index modulation (HMIM). HMIM introduces a novel approach to modulate information bits by IM patterns, significantly simplifying the complexity of maximum a posteriori (MAP) estimation with Gaussian noise. Further, we incorporate HMIM with the recently proposed orthogonal delay-Doppler division multiplexing (ODDM) modulation, namely ODDM-HMIM, to exploit the full diversity of the delay-Doppler (DD) channel. The BER performance of ODDM-HMIM is analyzed considering a maximum likelihood (ML) detector. Our numerical results reveal that, with the same SE, HMIM can outperform conventional IM in terms of both BER and computational complexity. In addition, we propose a successive interference cancellation-based minimum mean square error (SIC-MMSE) detector for ODDM-HMIM, which enables low-complexity detection with large frame sizes.

The orthogonal delay-Doppler division multiplexing (ODDM) modulation is a recently proposed multi-carrier modulation that features a realizable pulse orthogonal with respect to the delay-Doppler (DD) plane’s fine resolutions. In this paper, we investigate the performance of ODDM systems with imperfect channel estimation considering three detectors, namely the message passing algorithm (MPA) detector, iterative maximum-ratio combining (MRC) detector, and successive interference cancellation with minimum mean square error (SIC-MMSE) detector. We derive the post-equalization signal-to-interference-plus-noise ratio (SINR) for MRC and SIC-MMSE and analyze their bit error rate (BER) performance. Based on this analysis, we propose the MRC with subtractive dither (MRC-SD) and soft SIC-MMSE initialized MRC (SSMI-MRC) detector to improve the BER of iterative MRC. Our results demonstrate that soft SIC-MMSE consistently outperforms the other detectors in BER performance under perfect and imperfect CSI. While MRC exhibits a BER floor above$10^{-5}$, MRC-SD effectively lowers the BER with a negligible increase in detection complexity. SSMI-MRC achieves better BER than hard SIC-MMSE with the same detection complexity order. Additionally, we show that MPA has an error floor and is sensitive to imperfect CSI.

This paper proposes a novel parallel coding transmission strategy and an iterative detection and decoding receiver signal processing technique for orthogonal delay-Doppler division multiplexing (ODDM) modulation. Specifically, the proposed approach employs a parallel channel encoding (PCE) scheme that consists of multiple short-length codewords for each delay-Doppler multicarrier (DDMC) symbol. Building upon such a PCE transmission framework, we then introduce an iterative detection and decoding algorithm incorporating a successive decoding feedback (SDF) technique, which enables instant information exchange between the detector and decoder for each DDMC symbol. To characterize the error performance of the proposed scheme, we perform density evolution analysis considering the finite blocklength effects. Our analysis results, coupled with extensive simulations, demonstrate that the proposed PCE scheme with the SDF algorithm not only showcases a better overall performance but also requires much less decoding complexity to implement, compared to the conventional benchmark scheme that relies on a single long channel code for coding the entire ODDM frame.

We consider the uplink multiple access of heterogeneous users, e.g., ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB) users. Each user has its own reliability requirement and blocklength constraint, and users transmitting longer blocks suffer from heterogeneous interference. On top of that, the decoding of URLLC messages cannot leverage successive interference cancellation (SIC) owing to the stringent latency requirements. This can significantly degrade the spectral efficiency of all URLLC users when the interference is strong. To overcome this issue, we propose a new multiple access scheme employing discrete signaling and treating interference as noise (TIN) decoding, i.e., without SIC. Specifically, to handle heterogeneous interference while maintaining the single-user encoding and decoding complexities, each user uses a single channel code and maps its coded bits onto sub-blocks of symbols, where the underlying constellations can be different. We demonstrate theoretically and numerically that the proposed scheme employing quadrature amplitude modulations and TIN decoding can perform very close to the benchmark scheme based on Gaussian signaling with perfect SIC decoding. Interestingly, we show that the proposed scheme does not need to use all the transmit power budget, but also can sometimes even outperform the benchmark scheme.

Multiple access (MA) is a crucial part of any wireless system and refers to techniques that make use of the resource dimensions (e.g., time, frequency, power, antenna, code, and message) to serve multiple users/devices/machines/ services, ideally in the most efficient way. Given the increasing need of multifunctional wireless networks for integrated communications, sensing, localization, and computing, coupled with the surge of machine learning (ML)/artificial intelligence (AI) in wireless networks, MA techniques are expected to experience a paradigm shift in 6G and beyond. In this article, we provide a tutorial, survey, and outlook on past, emerging, and future MA techniques and pay particular attention to how wireless network intelligence and multifunctionality will lead to a rethinking of those techniques. This article starts with an overview of orthogonal, physical-layer multicasting, space domain, power domain (PD), rate-splitting, code-domain MAs, MAs in other domains, and random access (RA), and highlights the importance of conducting research in universal MA (UMA) to shrink instead of grow the knowledge tree of MA schemes by providing a unified understanding of MA schemes across all resource dimensions. It then jumps into rethinking MA schemes in the era of wireless network intelligence, covering AI for MA such as AI-empowered resource allocation, optimization, channel estimation, and receiver designs, for different MA schemes, and MA for AI such as federated learning (FL)/edge intelligence and over-the-air computation (AirComp). We then discuss MA for network multifunctionality and the interplay between MA and integrated sensing, localization, and communications, covering MA for joint sensing and communications, multimodal sensing-aided communications, multimodal sensing and digital twin-assisted communications, and communication-aided sensing/localization systems. We finish with studying MA for emerging intelligent applications such as semantic communications (SeComs), virtual reality (VR), and smart radio and reconfigurable intelligent surfaces (RISs), before presenting a roadmap toward 6G standardization. Throughout the text, we also point out numerous directions that are promising for future research.

Recently, orthogonal time frequency space (OTFS) modulation has garnered considerable attention due to its robustness against doubly-selective wireless channels. In this paper, we propose a low-complexity iterative successive interference cancellation based minimum mean squared error (SIC-MMSE) detection algorithm for zero-padded OTFS (ZP-OTFS) modulation. In the proposed algorithm, signals are detected based on layers processed by multiple SIC-MMSE linear filters for each sub-channel, with interference on the targeted signal layer being successively canceled either by hard or soft information. To reduce the complexity of computing individual layer filter coefficients, we also propose a novel filter coefficients recycling approach in place of generating the exact form of MMSE filter weights. Moreover, we design a joint detection and decoding algorithm for ZP-OTFS to enhance error performance. Compared to the conventional SIC-MMSE detection, our proposed algorithms outperform other linear detectors, e.g., maximal ratio combining (MRC), for ZP-OTFS with up to 3 dB gain while maintaining comparable computation complexity.

In this work, we consider a covert communication scenario, where a transmitter Alice communicates to a receiver Bob with the aid of a probabilistic and uninformed jammer against an adversary warden’s detection. The transmission status and power of the jammer are random and follow some priori probabilities. We first analyze the warden’s detection performance as a function of the jammer’s transmission probability, transmit power distribution, and Alice’s transmit power. We then maximize the covert throughput from Alice to Bob subject to a covertness constraint, by designing the covert communication strategies from three different perspectives: Alice’s perspective, the jammer’s perspective, and the global perspective. Our analysis reveals that the minimum jamming power should not always be zero in the probabilistic jamming strategy, which is different from that in the continuous jamming strategy presented in the literature. In addition, we prove that the minimum jamming power should be the same as Alice’s covert transmit power, depending on the covertness and average jamming power constraints. Furthermore, our results show that the probabilistic jamming can outperform the continuous jamming in terms of achieving a higher covert throughput under the same covertness and average jamming power constraints.

We consider a covert communication system from a transmitter Alice to a receiver Bob with the aid of a proba-bilistic and uninformed jammer against an adversary warden's detection, where the jammer's transmission status and power are random with priori probabilities. We first analyze the warden's detection performance as a function of the jammer's transmission probability, transmit power distribution (e.g., minimum and maximum transmit power, average power), and Alice's transmit power, based on which we optimize these parameters to maximize the communication throughput from Alice to Bob subject to a covertness constraint. Our analysis reveals that the jammer's minimum transmit power is not always zero in the probabilistic jamming strategy, which is different from that in the continuous jamming strategy presented in the literature. Instead, our analysis proves that the jammer's minimum jamming power is the same as Alice's covert transmit power, which depends on the required covertness level and the available average jamming power. Furthermore, our results show that the probabilistic jamming can outperform the continuous jamming in terms of achieving a higher covert communication throughput.

The problem of enabling the coexistence of heterogeneous services, e.g., different ultra-reliable low-latency communications (URLLC) services and/or enhanced mobile broadband (eMBB) services, in the uplink is studied. Each service has its own error probability and blocklength constraints and the longer transmission block suffers from heterogeneous interference. Due to the latency concern, the decoding of URLLC messages cannot leverage successive interference cancellation (SIC) and should always be performed before the decoding of eMBB messages. This can significantly degrade the achievable rates of URLLC users when the interference from other users is strong. To overcome this issue, we propose a new transmission scheme based on discrete signaling and treating interference as noise decoding, i.e., without SIC. Guided by the deterministic model, we provide a systematic way to construct discrete signaling for handling heterogeneous interference effectively. We demonstrate theoretically and numerically that the proposed scheme can perform close to the benchmark scheme based on capacity-achieving Gaussian signaling with the assumption of perfect SIC.

In this paper, we consider the downlink broadcast channel under heterogenous blocklength constraints, where each user experiences different interference statistics across its received symbols. Different from the homogeneous blocklength case, the strong users with short blocklength transmitted symbol blocks usually cannot wait to receive the entire transmission frame and perform successive interference cancellation (SIC) owing to their stringent latency requirements. Even if SIC is feasible, it may not be perfect under finite blocklength constraints. To cope with the heterogeneity in latency and reliability requirements, we propose a practical downlink transmission scheme with discrete signaling and single-user decoding, i.e., without SIC. In addition, we derive the finite blocklength achievable rate and use it for guiding the design of channel coding and modulations. Both achievable rate and error probability simulation show that the proposed scheme can operate close to the benchmark scheme which assumes capacity-achieving signaling and perfect SIC.

The problem of designing downlink transmission schemes for supporting heterogeneous ultra-reliable low-latency communications (URLLC) and/or with other types of services is investigated. We consider the broadcast channel, where the base station sends superimposed signals to multiple users. Under heterogeneous blocklength constraints, strong users who are URLLC users cannot wait to receive the entire transmission frame and perform successive interference cancellation (SIC) due to stringent latency requirements, in contrast to the conventional infinite blocklength cases. Even if SIC is feasible, SIC may be imperfect under finite blocklength constraints. To cope with the heterogeneity in latency and reliability requirements, we propose a practical downlink transmission scheme withdiscrete signalingandsingle-user decoding (SUD), i.e., without SIC. We carefully design the discrete input distributions to enable efficient SUD by exploiting the structural interference. Furthermore, we derive the second-order achievable rate under heterogenous blocklength and error probability constraints and use it to guide the design of channel coding and modulations. It is shown that in terms of achievable rate under short blocklength, the proposed scheme with regular quadrature amplitude modulations and SUD can operateextremely closeto the benchmark schemes that assume perfect SIC with Gaussian signaling.

We propose a new family of spatially coupled product codes, called sub-block rearranged staircase (SR-staircase) codes. Each SR-staircase code block is constructed by encoding rearranged preceding code blocks and new information blocks, where the rearrangement involves sub-blocks decomposition and transposition. The proposed codes can be constructed to have each code block size of 1/q to that of the conventional staircase codes while having the same rate and component codes, for any positive integer q. In this regard, we can use strong algebraic component codes to construct SR-staircase codes with a similar or the same code block size and rate as staircase codes with weak component codes. Moreover, both waterfall and error floor performance can be further improved by using a large coupling width. The superior performance of the proposed codes is demonstrated through density evolution and error floor analysis as well as simulation.

A new class of spatially-coupled turbo-like codes (SC-TCs), dubbed generalized spatially coupled parallel concatenated codes (GSC-PCCs), is introduced. These codes are constructed by applying spatial coupling on parallel concatenated codes (PCCs) with a fraction of information bits repeated$q$times. GSC-PCCs can be seen as a generalization of the original spatially-coupled parallel concatenated codes proposed by Moloudiet al., 2017. To characterize the asymptotic performance of GSC-PCCs, we derive the corresponding density evolution equations and compute their decoding thresholds. The threshold saturation effect is observed and proven. Most importantly, we rigorously prove that the rate-$R$GSC-PCC ensemble with 2-state convolutional component codes achieves at least a fraction$1-\frac {R}{R+q}$of the capacity of the binary erasure channel (BEC) for repetition factor$q\geq 2$and this multiplicative gap vanishes as$q$tends to infinity. To the best of our knowledge, this is the first class of SC-TCs that are proven to be capacity-achieving. Further, the connection between the strength of the component codes, the decoding thresholds of GSC-PCCs, and the repetition factor is established. The superiority of the proposed codes with finite blocklength is exemplified by comparing their error performance with that of existing SC-TCs via computer simulations.

We propose a new family of spatially coupled product codes, called sub-block rearranged staircase (SR-staircase) codes. Each code block of SR-staircase codes is obtained by encoding rearranged preceding code blocks and new information blocks, where the rearrangement involves sub-blocks decomposition and transposition. The proposed codes can be constructed to have each code block size of$1/q$to that of the conventional staircase codes while having the same rate and component codes, for any positive integer$q$. In this regard, we can use strong algebraic component codes to construct SR-staircase codes with a similar or the same code block size and rate as staircase codes with weak component codes. We characterize the decoding threshold of the proposed codes under iterative bounded distance decoding (iBDD) by using density evolution. We also derive the conditions under which they achieve a better decoding threshold than that of staircase codes. Further, we investigate the error floor performance by analyzing the contributing error patterns and their multiplicities. Both theoretical and simulation results show that the designed SR-staircase codes outperform staircase codes in terms of waterfall and error floor while the performance can be further improved by using a large coupling width.

We introduce generalized spatially coupled parallel concatenated codes (GSC-PCCs), a class of spatially coupled turbo-like codes obtained by coupling parallel concatenated codes (PCCs) with a fraction of information bits repeated before the PCC encoding. GSC-PCCs can be seen as a generalization of the original spatially coupled parallel concatenated convolutional codes (SC-PCCs) proposed by Moloudi et al. [1]. To characterize the asymptotic performance of GSC-PCCs, we derive the corresponding density evolution equations and compute their decoding thresholds. We show that the proposed codes have some nice properties such as threshold saturation and that their decoding thresholds improve with the repetition factor$q$. Most notably, our analysis suggests that the proposed codes asymptotically approach the capacity as$q$tends to infinity with any given constituent convolutional code.

This paper investigates the design and performance of delayed bit-interleaved coded modulation (DBICM) with low-density parity-check (LDPC) codes. For Gray labeled square M-ary quadrature amplitude modulation (QAM) constellations, we investigate the optimal delay scheme with the largest spectrum efficiency of DBICM for a fixed maximum number of delayed time slots and a given signal-to-noise ratio. When analyzing the capacity of DBICM, we find two important properties: the capacity improvement due to delayed coded bits being mapped to the real and imaginary parts of the transmitted symbols are independent of each other; a pair of delay schemes with delayed coded bits having identical bit-channel capacity lead to equivalent DBICM capacity. Using these two properties, we efficiently optimize the delay scheme for any uniform Gray-QAM systems. Furthermore, these two properties enable efficient LDPC code designs regarding unequal error protection via bit-channel type classifications. Moreover, we use protograph-based extrinsic information transfer charts to jointly optimize degree distributions and channel assignments of LDPC codes and propose a constrained progressive edge growth like algorithm to jointly construct LDPC codes and bit-interleavers for DBICM, taking distinctive bit-channel's capacity into account. Simulation results demonstrate that the designed LDPC coded DBICM systems significantly outperform LDPC coded BICM systems.

In this paper, we study a class of spatially coupled turbo codes, namely partially information- and partially parity-coupled turbo codes. This class of codes enjoy several advantages such as flexible code rate adjustment by varying the coupling ratio and the encoding and decoding architectures of the underlying component codes can remain unchanged. For this work, we first provide the construction methods for partially coupled turbo codes with coupling memory m and study the corresponding graph models. We then derive the density evolution equations for the corresponding ensembles on the binary erasure channel to precisely compute their iterative decoding thresholds. Rate-compatible designs and their decoding thresholds are also provided, where the coupling and puncturing ratios are jointly optimized to achieve the largest decoding threshold for a given target code rate. Our results show that for a wide range of code rates, the proposed codes attain close-to-capacity performance and the decoding performance improves with increasing the coupling memory. In particular, the proposed partially parity-coupled turbo codes have thresholds within 0.0002 of the BEC capacity for rates ranging from 1/3 to 9/10, yielding an attractive way for constructing rate-compatible capacity-approaching channel codes.

In this paper, we propose partially information coupled bit-interleaved polar coded modulation (PIC-BIPCM), which is a class of spatially coupled polar coding schemes designed for$2^{Q}$-ary modulations. Specifically, we consider PIC-BIPCM schemes respectively constructed with three BIPCM schemes: direct BIPCM, punctured BIPCM, and multi-kernel BIPCM. We analyze the error performance of the proposed PIC-BIPCM over the binary erasure channel (BEC) via density evolution. With the analysis as a guideline, we jointly design the positions of coupled bits and the modulation bit-mapper by taking into account the partial polarization of finite length polar codes as well as the unequal error protection of high order modulations. Simulation results demonstrate significant performance improvement of the proposed PIC-BIPCM over the uncoupled BIPCM on both BEC and AWGN channels.

The two-user Gaussian interference channel (G-IC) is revisited, with a particular focus on practically amenable discrete input signalling and treating interference as noise (TIN) receivers. The corresponding deterministic interference channel (D-IC) is first investigated and coding schemes that can achieve the entire capacity region of the D-IC under TIN are proposed. These schemes are thensystematicallytranslated into multi-layer superposition coding schemes based on purely discrete inputs for the real-valued G-IC. Our analysis shows that the proposed scheme is able to achieve theentirecapacity region to within a constant gap for all channel parameters. To the best of our knowledge, this is the first constant-gap result under purely discrete signalling and TIN for the entire capacity region and all the interference regimes. Furthermore, the approach is extended to obtain coding schemes based on discrete inputs for the complex-valued G-IC. For such a scenario, the minimum distance and the achievable rate of the proposed scheme under TIN are analyzed, which takes into account the effects of random phase rotations introduced by the channels. Simulation results show that our scheme is capable of approaching the capacity region of the complex-valued G-IC and significantly outperforms Gaussian signalling with TIN in various interference regimes.

In this paper, we study the achievable rate performance and the design of using purely discrete input signaling and treating interference as noise (TIN) for the two-user complex Gaussian interference channel (G-IC), where the channel introduces random phase rotation for all links. To analyze the achievable rate performance under this scenario, we first look into the corresponding deterministic interference channel model and design schemes to achieve the entire capacity region under TIN. Then, we translate the scheme into a multi-layer superposition coding scheme based on discrete inputs for GIC and analyze the achievable rate under TIN. Our simulation results show that our scheme is capable of approaching the (outer bound of) capacity region of the complex G-IC and performs significantly better than Gaussian signalling with TIN.

Partially information coupled turbo codes (PICTCs) is a class of spatially coupled turbo codes that can approach the BEC capacity while keeping the encoding and decoding architectures of the underlying component codes unchanged. However, PIC-TCs have significant rate loss compared to its component rate-1/3turbo code, and the rate loss increases with the coupling ratio. To absorb the rate loss, in this paper, we propose the partially information coupled duo-binary turbo codes (PIC-dTCs). Given a rate-1/3 turbo code as the benchmark, we construct a duo-binary turbo code by introducing one extra input to the benchmark code. Then, parts of the information sequence from the original input are coupled to the extra input of the succeeding code blocks. By looking into the graph model of PICdTC ensembles, we derive the exact density evolution equations of the PIC-dTC ensembles, and compute their belief propagation decoding thresholds on the binary erasure channel. Simulation results verify the correctness of our theoretical analysis, and also show significant error performance improvement over the uncoupled rate-1/3 turbo codes and existing designs of spatially coupled turbo codes.

In this paper, we study the communication problem of multiuser multiple-input single-output (MISO) broadcast channels with imperfect channel state information (CSI) at the transmitter. Zero-forcing precoding based on the imperfect CSI is adopted so that the channel can be transformed into a Gaussian interference channel. We consider a practical setting where only discrete input signalings are employed and all the receivers adopt single-user treating-interference-as-noise (TIN) decoding, as opposed to rate-splitting and successive interference cancellation. Under this setting, we first use the deterministic model to approximate the original channel model and develop communication schemes to achieve the entire capacity region. By translating the results of the deterministic model back to the MISO model, we develop a systematic way to design discrete input signalings for the original problem. Our simulation results show that our scheme is capable of approaching the (outer bound of) capacity region of the Gaussian interference channel.

The problem of downlink non-orthogonal multiple access (NOMA) scheme over fast fading channels is studied. A new class of downlink NOMA scheme is proposed, where each user's signals are encoded to a constellation corresponding to the same algebraic lattices from number fields and the transmitter sends the superposition of users' signals. The minimum product distance achieved by the proposed scheme with an arbitrary power allocation factor is investigated and its upper bounds are derived. Within this class, a family of NOMA schemes based on lattice partitions of the underlying ideal lattice is identified, whose minimum product distances can be easily controlled. Numerical results show that the scheme based on lattice partitions always results in the largest possible minimum product distance among the proposed class. Simulation results further indicate that the proposed scheme significantly outperforms the conventional NOMA scheme and the current state-of-the-art.

In this paper, we investigate the performance of a class of spatially coupled codes, namely partially information coupled turbo codes (PIC-TCs) over the binary erasure channel (BEC). This class of codes enjoy flexible code rate adjustment by varying the coupling ratio. Moreover, the coupling method can be directly applied to any component codes without changing the encoding and decoding architectures of the underlying component codes. However, the theoretical performance of PIC-TCs has not been fully investigated. For this work, we consider the codes that have coupling memory m and study the corresponding graph model. We then derive the exact density evolution equations for these code ensembles with any given coupling ratio and coupling memory m to precisely compute their belief propagation decoding thresholds for the BEC. Our simulation results verify the correctness of our theoretical analysis and also show better error performance over uncoupled turbo codes with a variety of code rates on the BEC.

In this paper, the problem of downlink non-orthogonal multiple access (NOMA) over slow fading channels is studied. Full-channel state information (CSI) is assumed at the receivers, while only the statistical CSI is assumed to be available at the transmitter. A novel lattice-partition-based scheme is proposed which, according to statistical CSI, employs discrete inputs from appropriately designed constellations carved from a lattice, rather than continuous Gaussian inputs as used in most existing works. Theoretical analysis shows that for any outage probability smaller than 63.21%, which covers almost all the cases of practical interest, the proposed scheme with single-user decoding, i.e., without successive interference cancellation (SIC) is able to approach the NOMA outage capacity region within a constant gap, independent of the signal-to-noise ratio, and the number of users. Simulation results fortify the effectiveness of the proposed scheme by showing that the approach without SIC can achieve outage rates that are very close to the outage capacity region and the gap becomes even smaller when SIC is employed.

In this paper, we investigate the problem of downlink non-orthogonal multiple access (NOMA) over block fading channels. For the single antenna case, we propose a class of NOMA schemes where all the users' signals are mapped into n-dimensional constellations corresponding to the same algebraic lattices from a number field, allowing every user attains full diversity gain with single-user decoding, i.e., no successive interference cancellation (SIC). The minimum product distances of the proposed scheme with arbitrary power allocation factor are analyzed and their upper bounds are derived. Within the proposed class of schemes, we also identify a special family of NOMA schemes based on lattice partitions of the underlying ideal lattices, whose minimum product distances can be easily controlled. Our analysis shows that among the proposed schemes, the lattice-partition-based schemes achieve the largest minimum product distances of the superimposed constellations, which are closely related to the symbol error rates for receivers with single-user decoding. The simulation results are presented to verify our analysis and to show the effectiveness of the proposed schemes as compared to benchmark NOMA schemes. Extensions of our design to the multi-antenna case are also considered where similar analysis and results are presented.

In this paper, we develop a lattice-partition-based downlink non-orthogonal multiple access (NOMA) scheme for slow fading channels without successive interference cancellation (SIC) at the receivers. With the knowledge of statistical channel state information at the transmitter, our scheme uses a finite constellation drawn from an n-dimensional lattice and employs channel coding on top of it. The outage rates achieved by our scheme without SIC are analyzed and their gaps to the multiuser outage capacity are derived. We show, both theoretically and numerically, that our scheme without SIC is capable of approaching any point in the multiuser outage capacity region within a constant gap when the required outage probability is smaller than 63.21%, which covers almost all cases of practical interest. Simulation results based on various lattices are provided and demonstrate that the near-capacity performance can be attained by our NOMA scheme without SIC.

In this paper, a novel lattice-partition-based downlink non-orthogonal multiple access framework is proposed. This framework is motivated by recognizing the algebraic structure behind the previous scheme recently proposed by Shieh and Huang as a lattice partition in Z and is in fact a generalization of the scheme to any base lattice. The schemes in the proposed framework enjoy many desirable properties such as explicit and systematic design and discrete input distributions. Moreover, the proposed method only requires a limited knowledge of channel parameters. The rates achieved by the proposed scheme with any base lattice and with single-user decoding (i.e., without successive interference cancellation) are analyzed, and a universal upper bound on the gap to the multiuser capacity is obtained as a function of the normalized second moment of the base lattice. Since the proposed framework has a substantially larger design space than that of the previous scheme of Shieh and Huang whose base lattice is a 1-D lattice, one can easily find instances in larger dimensions that can provide superior performance. Design examples with the base lattices A2, D4, E8, and Construction A lattices, respectively, are provided, and both theoretical and simulation results exhibit smaller gaps to the multiuser capacity as dimensions increase.

Most multi-dimensional (more than two dimensions) lattice partitions only form additive quotient groups and lack multiplication operations. This prevents us from constructing lattice codes based on multi-dimensional lattice partitions directly from non-binary linear codes over finite fields. In this paper, we design lattice codes from Construction A lattices where the underlying linear codes are non-binary irregular repeat-accumulate (IRA) codes. Most importantly, our codes are based on multi-dimensional lattice partitions with finite constellations. We propose a novel encoding structure that adds randomly generated lattice sequences to the encoder's messages, instead of multiplying lattice sequences to the encoder's messages. We prove that our approach can ensure that the decoder's messages exhibit permutation-invariance and symmetry properties. With these two properties, the densities of the messages in the iterative decoder can be modeled by Gaussian distributions described by a single parameter. With Gaussian approximation, extrinsic information transfer charts for our multi-dimensional IRA lattice codes are developed and used for analyzing the convergence behavior and optimizing the decoding thresholds. Simulation results show that our codes can approach the unrestricted Shannon limit within 0.46 dB and outperform the previously designed lattice codes with 2-D lattice partitions and existing lattice coding schemes for large codeword length.

In this paper, we propose novel terminated staircase codes for NAND flash memories. Specifically, we design a rate 0.89 staircase code whose component code is a Bose-Chaudhuri-Hocquenghem (BCH) code, for flash memories with page size of 16K bytes. Different from most conventional unterminated staircase codes, we propose a novel coding structure by performing cyclic redundancy check (CRC) encoding and decoding on each component codeword including information bits and parity bits. The CRC bits are protected by both row and column codewords. Furthermore, a novel iterative bit flipping algorithm is developed to solve stall patterns and lower the error floor. Based on our design, we perform an improved analysis on the error floor. We prove and show that our proposed decoding algorithm can solve more stall patterns which leads to a lower error floor compared with conventional staircase codes. Numerical results show that our terminated staircase codes outperform the stand-alone BCH codes and the conventional staircase codes.

In this paper, downlink non-orthogonal multiple access (NOMA) with receivers performing single- user decoding i.e., without successive interference cancellation (SIC) is studied. Using lattice partitions, we generalize the scheme recently proposed by Shieh and Huang [1] to general n-dimensional constellations carved from lattices. The achievable rates of the proposed scheme without SIC and the gap to the capacity region are investigated. Design examples based on lattice partition chains in Z2, A2, and D4 are studied. Numerical and simulation results are provided, which demonstrate advantages of the proposed scheme over the one in [1] and any orthogonal multiple access scheme.

We propose and design the lattice codes with finite lattice constellations based on multi-dimensional (more than two dimensions) lattice partitions. The codes are constructed from non-binary irregular repeat-accumulate (IRA) codes. Most notably, we propose a novel encoding structure to ensure that the decoder's messages exhibit permutation-invariance and symmetry properties. With these two properties, the densities of the messages in our iterative decoder can be well modeled by Gaussian distributions described by a single parameter. Under the Gaussian approximation, extrinsic information transfer charts for our multi-dimensional IRA lattice codes are developed and used for analysing the convergence behaviour and optimising the decoding threshold. Simulation results show that our proposed lattice codes outperform the previously designed lattice codes with two-dimensional lattice partitions.

We propose and design a lattice coded physical- layer network coding (PNC) over a finite complex number field Z[ω]ξZ[ω] in a two-way relay channel (TWRC). In our design, we construct the lattice codes from an irregular repeat- accumulate (IRA) code over GF(q). A randomly generated coset is employed to our scheme to ensure that the codes exhibit permutation invariance and symmetric properties. In a TWRC, two users employ the same lattice codebook and use the same transmit power. The relay attempts to decode the lattice coded network codes of the two users' messages by using an iterative belief propagation decoder and then broadcasts the lattice network coded messages back to both users. We use extrinsic information transfer (EXIT) charts to analyse the convergence behaviour and optimise the decoding threshold. Our results show that the optimised IRA lattice network codes can provide significant coding gain over the previous designed lattice coded PNC scheme over one dimensional Z lattice.