Channel estimation is fundamental to wireless communications, yet it becomes increasingly challenging in massive multiple-input multiple-output (MIMO) systems where base stations employ hundreds of antennas. Traditional least-squares methods require prohibitive pilot overhead that scales with antenna count, while sparse estimation methods depend on precise channel models that may not always be practical. This paper proposes a model-free approach combining deep autoencoders and LSTM networks. The method first learns low-dimensional channel representations preserving temporal correlation through augmenting a channel charting-inspired loss function, then tracks these features to recover full channel information from limited pilots. Simulation results using ray-tracing datasets show that the proposed approach achieves up to 9 dB improvement in normalized mean square error compared to the least-squares methods under ill-conditioned scenarios, while maintaining scalability across MIMO configurations.

The integration of pattern-reconfigurable antennas into hybrid multiple-input multiple-output (MIMO) architectures presents a promising path toward high-efficiency and low-cost transceiver solutions. Pattern-reconfigurable antennas can dynamically steer per-antenna radiation patterns, enabling more efficient power utilization and interference suppression. In this work, we study a tri-hybrid MIMO architecture for multi-user communications that integrates digital, analog, and antenna-domain precoding using pattern-reconfigurable antennas. For characterizing the reconfigurability of antenna radiation patterns, we develop two models---Model~I and Model~II. Model~I captures realistic hardware constraints through limited pattern selection, while Model~II explores the performance upper bound by assuming arbitrary pattern generation. Based on these models, we develop two corresponding tri-hybrid precoding algorithms grounded in the weighted minimum mean square error (WMMSE) framework, which alternately optimize the digital, analog, and antenna precoders under practical per-antenna power constraints. Realistic simulations conducted in ray-tracing generated environments are utilized to evaluate the proposed system and algorithms. The results demonstrate the significant potential of the considered tri-hybrid architecture in enhancing communication performance and hardware efficiency. However, they also reveal that the existing hardware is not yet capable of fully realizing these performance gains, underscoring the need for joint progress in antenna design and communication theory development.

Ultraviolet (UV) localization has attracted significant attention for its ability to operate without line-of-sight. Existing UV localization techniques usually require anchor nodes to be placed in specific geometric configurations, including linear alignment or co-location. However, this requirement is often impractical in real-world scenarios, where obstacles such as walls and equipment prevent anchor nodes from being placed in ideal positions. In this paper, we consider general scenarios without constraints on anchor deployment and propose a UV localization technique, referred to as EIUL (Evolutionary and Invex approximation-based Ultraviolet Localization), to address non-line-of-sight scenarios. We adopt the single-scattering model and the geometric relationship between the transmitting beam and the receiver’s field of view to develop a least-squares-based estimator for jointly estimating the target node’s location, along with the transmitting beam’s azimuth angle and elevation angle. We first apply differential evolution to obtain an initial estimate, which is then used to facilitate invex approximation, thereby formulating an invexified objective function to further refine the location estimate. We derive the Lipschitz constant for the gradient of the invexified objective function and employ the Nesterov’s accelerated gradient descent to achieve the global minimum. Additionally, we present a concise form of the Cramer-Rao lower bound for UV localization based on the single-scattering model, which is straightforward to compute numerically. Extensive simulations demonstrate that EIUL provides more accurate parameter estimation with lower computational complexity compared to existing techniques.

In this paper, we design a deep learning-based convolutional autoencoder for channel coding and modulation. The objective is to develop an adaptive scheme capable of operating at various signal-to-noise ratios (SNR)s without the need for re-training. Additionally, the proposed framework allows validation by testing all possible codes in the codebook, as opposed to previous AI-based encoder/decoder frameworks which relied on testing only a small subset of the available codes. This limitation in earlier methods often led to unreliable conclusions when generalized to larger codebooks. In contrast to previous methods, our multi-level encoding and decoding approach splits the message into blocks, where each encoder block processes a distinct group of B bits. By doing so, the proposed scheme can exhaustively test 2Bpossible codewords for each encoder/decoder level, constituting a layer of the overall scheme. The proposed model was compared to classical polar codes and TurboAE-MOD schemes, showing improved reliability with achieving comparable, or even superior results in some settings. Notably, the architecture can adapt to different SNRs by selectively removing one of the encoder/decoder layers without re-training, thus demonstrating flexibility and efficiency in practical wireless communication scenarios.

The rapid development of reconfigurable intelligent surfaces (RISs) has sparked transformative advancements in wireless communication systems. These intelligent metasurfaces, adept at dynamically manipulating electromagnetic (EM) waves, hold vast potential for enhancing network capacity, coverage, and efficiency. However, to fully unleash the capabilities of RIS-aided communication systems, effective optimization is crucial. This article provides a recent development of RIS-assisted communication from the viewpoint of physically-consistent EM models. We delve into the realm of physically-consistent EM models, highlighting their pivotal role in achieving robust and efficient RIS designs. Furthermore, this paper offers a survey of the different optimization models utilized for RIS-assisted wireless communication systems, which consider various EM and physical aspects of RIS. We explore solution approaches aimed at optimizing different objectives like sum-rate/spectral efficiency and energy efficiency, spanning traditional optimization models to machine learning-based methods. Additionally, we discuss some open research issues in this field.

The multiple-input-single-output (MISO) Gaussian broadcast channel (BC) under per-emitter peak-amplitude constraint arises in naturally indoor optical wireless communication (OWC) applications due to the availability of many luminaires and simple photo receivers. In this paper, we study the achievable rate region of the two-user peak-amplitude constrained MISO BC with the goal of increasing the rate region beyond the one achieved using zero-forcing (ZF) precoding. To this end, a novel precoding scheme is proposed that combines a type of discrete-state dirty paper channel (DPC) studied recently and ZF precoding for the MISO BC, termed the DPC-ZF precoding. We derive the achievable rate region of the proposed precoding scheme, and compare it with the one achieved by ZF precoding numerically by simulating a two-user indoor OWC broadcasting system. Numerical results show a significant improvement in the achievable rate region through DPC-ZF precoding compared to ZF precoding, implying the existence of more powerful interference management schemes for OWC broadcasting.

The reflection characteristics of a reconfigurable intelligent surface (RIS) depend on the reflection response of the constituent unit cells, which are necessarily frequency dependent. This paper investigates the role of an RIS comprised of unit cells with different phase-frequency profiles in improving the achievable rate of a wide-band orthogonal frequency division multiplexing (OFDM) system. Specifically, we propose phase-frequency profiles with both variable phase and variable slope that enable improvements in the spectral efficiency of a channel. We first propose a mathematical model for the frequency response of the reflection coefficient of a realizable RIS unit cell and parameterize the phase-frequency profile by its slope and by its resonance center frequency. Then, modelling each RIS element with b control bits, we propose a method for selecting the parameter pairs to obtain a set of$2^{b}$reflection profiles. We then use a low-complexity optimization algorithm to maximize the data rate through the joint optimization of (a) the reflection profile for each RIS unit cell from the available sets and (b) the power allocations across the sub-carriers. We show that the resulting RIS outperforms existing designs over a wide range of user locations in single-input single-output and multi-user multiple-input single-output OFDM systems.

Stacked intelligent metasurface (SIM) is an emerging programmable metasurface architecture that can imple-ment signal processing directly in the electromagnetic wave domain, thereby enabling efficient implementation of ultra-massive multiple-input multiple-output (MIMO) transceivers with a limited number of radio frequency (RF) chains. Channel estimation (CE) is challenging for SIM-enabled communication systems due to the multilayer architecture of SIM, and because we need to estimate large dimensional channels between the SIM and users with a limited number of RF chains. To efficiently solve this problem, we develop a novel hybrid digital-wave domain channel estimator, in which the received training symbols are first processed in the wave domain within the SIM layers, and then processed in the digital domain. The wave domain channel estimator, parametrized by the phase shifts applied by the meta-atoms in all layers, is optimized to minimize the mean squared error (MSE) using a gradient descent algorithm, within which the digital part is optimally updated. For an SIM-enabled multi-user system equipped with 4 RF chains and a 6-layer SIM with 64 meta-atoms each, the proposed estimator yields an MSE that becomes close to that achieved by fully digital CE in a massive MIMO system employing 64 RF chains. This high CE accuracy is achieved at the cost of a training overhead that can be reduced by exploiting the potential low rank of channel correlation matrices.

Cell free (CF) massive multiple-input multiple-output (mMIMO) is a promising technology in realizing beyond fifth generation (B5G) networks. Massive deployment of access points (APs) in a CF-mMIMO system increases the spectral efficiency, however it also increases the energy consumption and fronthaul requirements. Since recently reconfigurable intelligent surface (RIS) is shown to be a cost-effective solution to improve performance of wireless networks, RIS can be a promising technology to enhance the performance of CF-mMIMO systems. In this work, we study the downlink (DL) performance of CF-mMIMO system aided by multiple RISs, while considering correlated Rician fading channels, discrete RIS phase-shifts and low-complexity channel estimation (CE) protocol. Given the obtained imperfect channel state information (CSI), we derive lower bounds on the rates achieved using conjugate beamforming (CB) and zero-forcing (ZF) precoders. The obtained bounds depend on channel statistics, RIS phase-shifts and number of RIS elements. To optimize the performance with respect to RIS phase-shifts, we formulate a maximization problem and propose a sub-optimal genetic algorithm (GA)-based solution. Through simulations, we demonstrate that distributed RIS deployment outperforms centralized RIS deployment in terms of DL throughput. Interestingly, we demonstrate that the DL throughput improves as number of RISs increases until an optimal number of distributed RISs over which the DL performance of the system starts to drop. We discuss this effect under varying the number of APs and RISs. We extend the analysis by considering different precoders, CE and RIS optimization schemes, and verify the accuracy of our derived analytical results by Monte-Carlo simulations.

This work studies a multi-cell one-bit massive multiple-input multiple-output (MIMO) system that employs one-bit analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) at each base station (BS). We utilize Bussgang decomposition to derive downlink signal-to-quantization-plus-interference-plus-noise ratio (SQINR) and ergodic achievable rate expressions under one-bit quantized maximum ratio transmission (MRT) and zero-forcing (ZF) precoding schemes considering scenarios with and without pilot contamination (PC) in the derived channel estimates. The results are also simplified for the mixed architecture that employs full resolution (FR) ADCs and one-bit DACs, and the conventional architecture that employs FR ADCs and DACs. The SQINR is shown to decrease by a factor of 2/π and 4/π2in the one-bit setting compared to that achieved in the mixed setting and conventional setting respectively under MRT precoding without PC. Interestingly, the decrease in SQINR is less when we consider PC, which is shown to adversely impact the conventional system more than the one-bit system. Similar insights are obtained under ZF precoding with the decrease in the SQINR with the use of one-bit ADCs and DACs being more pronounced. We utilize the derived expressions to yield performance insights related to power efficiency, the numbers of antennas needed by the three architectures to achieve the same sum-rate, and energy efficiency.

In this paper, we study an uplink reconfigurable intelligent surface (RIS) aided orthogonal frequency division multiplexing (OFDM) system, where the RIS simultaneously acts as a passive reflector for a user’s quadrature phase-shift keying (QPSK) OFDM signal and an information source which sends information through spatial modulation of the reflected signal. We present a maximum-likelihood (ML) detector for the detection of RIS signals and analyze the error probability theoretically. We derive closed-form expressions of the error probability for the detection of RIS signals for the special case of flat-fading channels. Then we analyze the error probability of the detection of user’s signals. Analysis indicates that faulty detection of RIS signal results in channel estimation errors, consequently compromising the precision of OFDM signal detection. High correlation between code words limits the error propagation to the user but decreases accuracy for RIS signal’s detection. Addressing this, an index modulation with beamforming (IM-BF) code is proposed to enhance the transmission for the user, and a quadrature reflection modulation with beamforming (QRM-BF) code is proposed for a performance trade-off between the user and the RIS. Simulation results demonstrate the theoretical results, and show that the QRM-BF code has better performance for the RIS transmission, and both schemes outperform benchmark schemes from the literature for the user’s transmission. Simulation results also show that the IM-BF scheme significantly improves the user transmission performance compared to the state of the art.

Some emerging 5G and beyond use-cases impose stringent latency constraints, which necessitates a paradigm shift towards finite blocklength performance analysis. In contrast to Shannon capacity-achieving codes, the codeword length in the finite blocklength regime (FBR) is a critical design parameter that imposes an intricate tradeoff between delay, reliability, and information coding rate. In this context, this paper presents a novel mathematical analysis to characterize the performance of large-scale downlink networks using short codewords. Theoretical achievable rates, outage probability, and reliability expressions are derived using the finite blocklength coding theory in conjunction with stochastic geometry, and compared to the performance in the asymptotic regime (AR). Achievable rates under practical modulation schemes as well as multilevel polar coded modulation (MLPCM) are investigated. Numerical results provide theoretical performance benchmarks, highlight the potential of MLPCM in achieving close to optimal performance with short codewords, and confirm the discrepancy between the performance in the FBR and that predicted by analysis in the AR. Finally, the meta distribution of the coding rate is derived, providing the percentiles of users that achieve a predefined target rate in a network.

In large scale dynamic wireless networks, the amount of overhead caused by channel estimation (CE) is becoming one of the main performance bottlenecks. This is due to large number of users whose channels should be estimated and the user mobility. This work proposes a new hybrid channel estimation/prediction (CEP) scheme to reduce overhead in time-division duplex (TDD) wireless cell-free massive multiple-input-multiple-output (mMIMO) systems. The scheme proposes sending a pilot signal from each user only once in a given number (window) of coherence intervals (CIs). Then minimum mean-square error (MMSE) estimation is used to estimate the channel of this CI, while a deep neural network (DNN) is used to predict the channels of the remaining CIs in the window, exploiting the temporal correlation between the consecutive CIs. By doing so, CE overhead is reduced by at least 50 percent at the expense of negligible CE error for practical user mobility settings. Consequently, the proposed CEP scheme improves the spectral efficiency compared to the conventional MMSE CE approach, which is demonstrated numerically.

Physical-layer security (PLS) is superior to classical cryptography techniques due to its notion of perfect secrecy and independence to an eavesdropper's computational power. One form of PLS arises when Alice and Bob (the legitimate users) exchange signals to extract a common key from the random common channels. The drawback of extracting keys from wireless channels is the ample dependence on the dynamicity and fluctuations of the radio channel. However, some radio channels are constant such as line-of-sight (LoS) and can be estimated by Eve (an illegitimate user), or can be quite static in behavior due to the presence low-mobility users thus restricting the amount of randomness. This in turn lowers the secret key rate (SKR) defined as the number of bits of key generated per channel use. In this work, we aim to address this challenge by using a reconfigurable intelligent surface (RIS) to produce random phases at certain carefully curated intervals such that it disrupts the channel in low-entropy environments. We propose an RIS assisted key generation method, study its performance, and compare with benchmarks to observe the benefit of using an RIS while considering various important metrics such as key mismatch rate and average secret key throughput. Simulations are made to validate our theoretical findings showing an improvement in performance when an RIS is deployed.

The development of delay-constrained applications which require high data rates, ultra-low latency, and high reliability pushed future communication technologies towards using short codes. This necessitates studying the performance of large-scale networks under short codes. Works in the literature that study large-scale uplink (UL) networks rely on the classical Shannon coding theory which assumes long codes and vanishing frame error probability, which is imprecise for short codes. Thus, this paper studies the performance of a large-scale UL network in the finite blocklength regime (FBR), under two power control schemes to mitigate the effect of interference: truncated channel inversion power control and channel inversion power control with maximum power transmission. The average coding rate, outage probability, and reliability of this network are derived in the FBR. Numerical results study the effect of network parameters and also show that the classical coding theory overestimates the average coding rate and imprecisely characterizes the outage probability and the reliability in the FBR.

The dirty paper channel (DPC) under a peak amplitude constraint arises in an optical wireless broadcast channel (BC), where the state at one receiver is the transmitted signal intended for the other receiver(s). This paper studies a class of peak-constrained DPC that is applicable to the optical wireless BC, where the channel state (i.e, ‘dirt’) takes values from some evenly-spaced grid. For the discrete-state DPC studied this paper, a capacity upper bound is obtained from its state-free counterpart. To lower bound its capacity, classical dirty paper coding schemes are revisited, including Costa’s coding for DPC and Tomlinson-Harashima (TH) precoding, which serves as benchmark schemes. To improve the benchmark performance, two new precoding schemes are proposed for the discrete-state DPC. Although the proposed schemes do not achieve the state-free capacity contrary to what is known about the Costa’s DPC, achievable rates within a small gap to the state-free capacity are demonstrated for the discrete-state DPC. Using the proposed precoding scheme in a two-user peak-constrained Gaussian BC, a new capacity inner bound (IB) is obtained, and is shown to outperform the truncated Gaussian (TG) based IB and is comparable to the best-known IB.

Federated learning (FL) has emerged as a distributed machine learning (ML) technique to train models without sharing users’ private data. In this paper, we introduce a decentralized FL scheme that is called federated learning empowered overlapped clustering for decentralized aggregation (FL-EOCD). The introduced FL-EOCD leverages device-to-device (D2D) communications and overlapped clustering to enable decentralized aggregation, where a cluster is defined as a coverage zone of a typical device. The devices located on the overlapped clusters are called bridge devices (BDs). In the proposed FL-EOCD scheme, a clustering topology is envisioned where clusters are connected through BDs, so as the aggregated models of each cluster is disseminated to the other clusters in a decentralized manner without the need for a global aggregator or an additional hop of transmission. To evaluate our proposed FL-EOCD scheme as opposed to baseline FL schemes, we consider minimizing the overall energy-consumption of devices while maintaining the convergence rate of FL subject to its time constraint. To this end, a joint optimization problem, considering scheduling the local devices/BDs to the CHs and computation frequency allocation, is formulated, where an iterative solution to this joint problem is devised. Extensive simulations are conducted to verify the effectiveness of the proposed FL-EOCD algorithm over FL conventional schemes in terms of energy consumption, latency, and convergence rate.

The paper provides a new perspective on peak- and average-constrained Gaussian channels. Such channels model optical wireless communication (OWC) systems which employ intensity-modulation with direct detection (IM/DD). First, the paper proposes a new, capacity-preserving vector binary channel (VBC) model, consisting of dependent binary noisy bit-pipes. Then, to simplify coding over this VBC, the paper proposes coding schemes with varying levels of complexity, building on the capacity of binary-symmetric channels (BSC) and channels with state. The achievable rates are compared to capacity and capacity bounds, showing that coding for the BSC with state over the VBC achieves rates close to capacity at moderate to high signal-to-noise ratio (SNR), whereas simpler schemes achieve lower rates at lower complexity. The presented coding schemes are realizable using capacity-achieving codes for binary-input channels, such as polar codes. Numerical results are provided to validate the theoretical results and demonstrate the applicability of the proposed schemes.

In optical wireless communications, a broadcast channel (BC) employing intensity modulation and direct detection (IM/DD) is often modeled as a peak-constrained BC. A closed-form expression for its capacity region of the peak-constrained BC is not known. This paper presents an analytical capacity inner bound for the peak-constrained Gaussian BC achieved by a class of discrete input distribution, specifically, the evenly-spaced discrete uniform distribution (ESDU). In contrast to the continuous input distribution that provides the benchmark, ESDU is more promising in the application of peak-constrained Gaussian channels. The newly obtained capacity inner bound is easily-computable and is numerically shown to be tighter than the benchmark. Besides, we remark the newly developed analytical upper bound for the ESDU rate, which is tight in all tested settings.

Achieving high data rate is always a goal that could be met by developing new technologies and investigating potential ones. Recently, the concept of cell-free massive MIMO systems (CF-mMIMO) has been considered to enhance the performance of systems that operate merely with Radio Frequency (RF) or visible light communication (VLC) technologies. In this paper, a hybrid VLC/RF cell-free massive MIMO system is proposed where an RF cell-free network is used to support a VLC cell-free network. The idea is to utilize the benefits of each network and balance the load aiming at maximizing the system’s sum-rate. The system is evaluated using zero-forcing (ZF) precoding scheme. A user association algorithm is proposed to assign users to either VLC or RF networks. Results show that the proposed algorithm outperforms a random network association of users. Results also show great potential for the proposed system compared to standalone cell-free networks.

The tremendous growth of data traffic in mobile communication networks (MCNs) and the associated exponential increase in mobile devices’ numbers necessitate the use of multi-cloud radio access networks (MC-RANs) as a viable solution to cope with the requirements of next-generation MCNs (6G). In MC-RANs, each central processor (CP) manages the signal processing of its own set of base stations (BSs), and so the system performance becomes a function of the joint intra-cloud and inter-cloud interference mitigation techniques. To this end, this paper considers the problem of maximizing the network-wide energy efficiency (EE) subject to user-to-cloud association, fronthaul capacity, maximum transmit power, and achievable rate constraints, so as to determine the joint beamforming vector of each user and the user-to-cloud association strategy. The paper tackles the non-convex and mixed discrete-continuous nature of the problem formulation using fractional programming (FP) and inner-convex approximation (ICA) techniques, as well as l0-norm relaxation heuristics, and shows how the proposed approach can be implemented in a distributed fashion via a reasonable amount of information exchange across the CPs. The paper simulations highlight the appreciable algorithmic efficiency of the proposed approach over state-of-the-art schemes.

This paper studies the capacity of the two-user intensity-modulation/direct-detection (IM/DD) interference channel (IC), which is relevant in the context of multi-user optical wireless communications. Despite some known single-letter capacity characterizations for general discrete-memoryless ICs, a computable capacity expression for the IM/DD IC is missing. In this paper, we provide tight and easily computable inner and outer bounds for a general two-user IM/DD IC under peak and average optical intensity constraints. The bounds enable characterizing the asymptotic sum-rate capacity in the strong and weak interference regimes, as well as the generalized degrees of freedom (GDoF) in the symmetric case. Using the obtained bounds, the GDoF of the IM/DD IC is shown to have a ‘W’ shape similar to the Gaussian IC with power constraints. The obtained bounds are also evaluated numerically in different interference regimes to show their tightness, and used to study the performance of on-chip and indoor OWC systems.

Cloud radio-access networks (C-RAN) have been proposed as an enabling technology for keeping up with the requirements of next-generation wireless networks. Most existing works on C-RAN study the uplink or the downlink separately. However, designing the uplink and the downlink jointly may bring additional advantages, especially if message source-destination information is taken into account. In this paper, this idea is demonstrated by considering pairwise message exchange between users in a C-RAN. A multi-pair two-way transmission scheme is proposed which targets maximizing the end-to-end sum rate. In the proposed scheme, a lattice-based computation strategy is used, where the baseband processing unit (BBU) pool decodes integer linear combinations of paired users’ codewords instead of decoding linear combinations of individual codewords. The BBU pool then precodes the computed signals, compresses, and forwards them to the remote radio heads (RRHs), which in turn decompress the signals and send them to the users. Finally, each user decodes its desired message using its own message as side information. The achievable rate of this scheme is derived, optimized, and evaluated numerically. Simulation results reveal that significant end-to-end rate improvement can be achieved using the proposed scheme compared to existing schemes.

Reconfigurable intelligent surfaces (RISs) have drawn considerable attention due to their ability to direct electromagnetic waves into desirable directions. Although RISs share some similarities with relays, the two have fundamental differences impacting their performance. To harness the benefits of both, we propose a downlink system wherein a relay and an RIS improve performance in terms of energy-efficiency. Using singular value decomposition (SVD), semidefinite programming (SDP), and function approximations, we propose different solutions for optimizing the beamforming matrices at the base-station (BS), the relay, and the phase shifts at the RIS to minimize the total power under quality-of-service (QoS) constraints. The problem is solved when the relay operates in half-duplex and full-duplex modes and when the reflecting elements have continuous and discrete phase shifts. Simulation results compare the performance of the system with and without the RIS or the relay, under different optimization solutions. The results show that the system with full-duplex relay and RIS outperforms the other scenarios, and the contribution of full-duplex relay is higher than that of the RIS. However, an RIS outperforms a half-duplex relay when the required QoS is high. The results also show that increasing the number of reflecting elements improves the performance better in the presence of a relay than in its absence.

Ultra-Reliable Low-Latency Communications have stringent delay constraints, and hence use codes with small block length (short codewords). In these cases, classical models that provide good approximations to systems with infinitely long codewords become imprecise. To remedy this, in this paper, an average coding rate expression is derived for a large-scale network with short codewords using stochastic geometry and the theory of coding in the finite blocklength regime. The average coding rate and upper and lower bounds on the outage probability of the large-scale network are derived, and a tight approximation of the outage probability is presented. Then, simulations are presented to study the effect of network parameters on the average coding rate and the outage probability of the network, which demonstrate that results in the literature derived for the infinite blocklength regime overestimate the network performance, whereas the results in this paper provide a more realistic performance evaluation.

Intelligent reflecting surfaces (IRS) can improve the physical layer security (PLS) by providing a controllable wireless environment. In this paper, we propose a novel PLS technique with the help of IRS implemented by an intelligent mirror array for the visible light communication (VLC) system. First, for the IRS aided VLC system containing an access point (AP), a legitimate user and an eavesdropper, the IRS channel gain and a lower bound of the achievable secrecy rate are derived. Further, to enhance the IRS channel gain of the legitimate user while restricting the IRS channel gain of the eavesdropper, we formulate an achievable secrecy rate maximization problem for the proposed IRS-aided PLS technique to find the optimal orientations of mirrors. Since the sensitivity of mirrors’ orientations on the IRS channel gain makes the optimization problem hard to solve, we transform the original problem into a reflected spot position optimization problem and solve it by a particle swarm optimization (PSO) algorithm. Our simulation results show that secrecy performance can be significantly improved by adding an IRS in a VLC system.

This paper develops a binary decomposition for the peak-constrained intensity-modulation with direct-detection (IM/DD) channel. Then, it uses this decomposition, which we call a Vector Binary Channel (VBC), to propose simple binary coding schemes. The VBC consists of$N$bit-pipes and, different from the Avestimehr-Diggavi-Tse linear deterministic model, captures interactions between bit-pipes thus preserves capacity. Two practical coding schemes are then designed for the VBC. The first is an Independent Coding scheme which encodes independently and decodes successively while ignoring the dependence between noises on different bit-pipes. The second improves upon the first by exploiting the knowledge of noises on previously decoded bit-pipes as a state for the current decoding operation. The achievable rates of the schemes are compared numerically with capacity, and shown to perform well with the second scheme approaching capacity for signal-to-noise ratio (SNR) > 2.5 dB. The schemes can be implemented using practical capacity-achieving codes for the binary symmetric channel (BSC) such as polar codes. Methods to improve the schemes at low-SNR are discussed towards the end of the paper.

The challenge of wildfire management and detection is recently gaining increased attention due to the increased severity and frequency of wildfires worldwide. Popular fire detection techniques, such as satellite imaging and remote camera-based sensing suffer from late detection and low reliability while early wildfire detection is a key to prevent massive fires. In this article, we propose a novel wildfire detection solution based on unmanned aerial vehicles assisted Internet of Things (UAV-IoT) networks. The main objective is to: 1) study the performance and reliability of the UAV-IoT networks for wildfire detection and 2) present a guideline to optimize the UAV-IoT network to improve fire detection probability under limited system cost budgets. We focus on optimizing the IoT devices’ density and the number of UAVs covering the forest area such that a lower bound on the wildfires detection probability is maximized within a limited time and system cost. At any time after the fire ignition, the IoT devices within a limited distance from the fire can detect it. These IoT devices can then report their measurements to nearby UAVs. Discrete-time Markov chain (DTMC) analysis is utilized to compute the fire detection and false-alarm probabilities. Numerical results suggest that given enough system cost, the UAV-IoT-based fire detection can offer a faster and more reliable wildfire detection solution than state-of-the-art satellite imaging techniques.

The current literature on intelligent reflecting surface (IRS) focuses on optimizing the IRS phase shifts to yield coherent beamforming gains, under the assumption of perfect channel state information (CSI) of individual IRS-assisted links, which is highly impractical. This work, instead, considers the random rotations scheme at the IRS in which the reflecting elements only employ random phase rotations without requiring any CSI. The only CSI then needed is at the base station (BS) of the overall channel to implement the beamforming transmission scheme. Under this framework, we derive the sum-rate scaling laws in the large number of users regime for the IRS-assisted multiple-input single-output (MISO) broadcast channel, with optimal dirty paper coding (DPC) scheme and the lower-complexity random beamforming (RBF) and deterministic beamforming (DBF) schemes at the BS. The random rotations scheme increases the sum-rate by exploiting multi-user diversity, but also compromises the gain to some extent due to correlation. Finally, energy efficiency maximization problems in terms of the number of BS antennas, IRS elements and transmit power are solved using the derived scaling laws. Simulation results show the proposed scheme to improve the sum-rate, with performance becoming close to that under coherent beamforming for a large number of users.

In next-generation wireless networks, providing secure transmission and delay guarantees are two critical goals. However, either of them requires a concession on the transmission rate. In this article, we consider a visible light network consisting of multiple access points and multiple users. Our first objective is to mathematically evaluate the achievable rate under constraints on delay and security. The second objective is to provide a cell formation with customized statistical delay and security guarantees for each user. First, we propose a user-centric design called secure cell formation, in which artificial noise is considered, and flexible user scheduling is determined. Then, based on the effective capacity theory, we derive the statistical-delay-constrained secrecy rate and formulate the cell formation problem as a stochastic optimization problem (OP). Further, based on the Lyapunov optimization theory, we transform the stochastic OP into a series of evolutionary per-slot drift-plus-penalty OPs. Finally, a modified particle swarm optimization algorithm and an interference graph-based user-centric scheduling algorithm are proposed to solve the OPs. We obtain a dynamic independent set of scheduled users as well as secure cell formation parameters. Simulation results show that the proposed algorithm can achieve a better delay-constrained secrecy rate than the existing cell formation approaches.

This work makes the preliminary contribution of studying the asymptotic performance of a multi-user intelligent reflecting surface (IRS) assisted-multiple-input single-output (MISO) downlink system under imperfect CSI. We first extend the existing least squares (LS) ON/OFF channel estimation protocol to a multi-user system, where we derive minimum mean squared error (MMSE) estimates of all IRS-assisted channels over multiple sub-phases. We also consider a low-complexity direct estimation (DE) scheme, where the BS obtains the MMSE estimate of the overall channel in a single sub-phase. Under both protocols, the BS implements maximum ratio transmission (MRT) precoding while the IRS design is studied in the large system limit, where we derive deterministic equivalents of the signal-to-interference-plus-noise ratio (SINR) and the sum-rate. The derived asymptotic expressions, which depend only on channel statistics, reveal that under Rayleigh fading IRS-to-users channels, the IRS phase-shift values do not play a significant role in improving the sum-rate but the IRS still provides an array gain. Simulation results confirm the accuracy of the derived deterministic equivalents and show that under Rayleigh fading, the IRS gains are more significant in noise-limited scenarios. We also conclude that the DE of the overall channel yields better performance when considering large systems.

Multi-user (MU) diversity yields sum-rate gains by scheduling a user for transmission at times when its channel is near its peak. These gains are limited in environments with line- of-sight (LoS) channel components and/or spatial correlation. To remedy this, previous works have proposed opportunistic beamforming (OBF) using multiple antennas at the BS to transmit the same signal, modulated by time-varying gains, to the best user at each time slot. In this paper, we propose reconfigurable surface (RS)-assisted OBF to increase the range of channel fluctuations in a single-antenna broadcast channel (BC), where opportunistic scheduling (OS) strategy achieves the sum-rate capacity. The RS is abstracted as an array of passive reflecting elements that only induce random phase shifts onto the impinging electromagnetic waves. We develop the sum-rate scaling laws under Rayleigh, Rician and correlated Rayleigh fading and show that RS-assisted OBF with a single-antenna BS can outperform multi-antenna BS- assisted OBF using a moderate number of elements.

Full-duplex communication allows a terminal to transmit and receive signals simultaneously, and hence, it is helpful in general to adapt transmissions to received signals. However, this often requires unaffordable complexity. This work focuses on simple non-adaptive transmission, and provides two classes of channels for which Shannon's information capacity regions are achieved without adaptation. The first is the injective semi-deterministic two-way channel that includes additive channels with various types of noises modeling wireless, coaxial cable, and other settings. The other is the Poisson two-way channel, for which we show that non-adaptive transmission is asymptotically optimal in the high dark current regime.

This work focuses on the downlink of a single-cell multi-user system in which a base station (BS) equipped with M antennas communicates with K single-antenna users through a reconfigurable intelligent surface (RIS) installed in the line-of-sight (LoS) of the BS. RIS is envisioned to offer unprecedented spectral efficiency gains by utilizing N passive reflecting elements that induce phase shifts on the impinging electromagnetic waves to smartly reconfigure the signal propagation environment. We study the minimum signal-to-interference-plus-noise ratio (SINR) achieved by the optimal linear precoder (OLP), that maximizes the minimum SINR subject to a given power constraint for any given RIS phase matrix, for the cases where the LoS channel matrix between the BS and the RIS is of rank-one and of full-rank. In the former scenario, the minimum SINR achieved by the RIS-assisted link is bounded by a quantity that goes to zero with K. For the high-rank scenario, we develop accurate deterministic approximations for the parameters of the asymptotically OLP, which are then utilized to optimize the RIS phase matrix. Simulation results show that RISs can outperform half-duplex relays with a small number of passive reflecting elements while large RISs are needed to outperform full-duplex relays.

Optical orthogonal frequency division multiplexing (O-OFDM) schemes are variations of OFDM schemes that produce non-negative signals. Asymmetrically-clipped O-OFDM (ACO-OFDM) is a single-layer O-OFDM scheme, whose spectral efficiency can be enhanced by adopting multiple ACO-OFDM layers or a combination of ACO-OFDM and other O-OFDM schemes. However, since symbol detection in such enhanced ACO-OFDM (eACO-OFDM) is done iteratively, erroneous detection leads to residual clipping noise (RCN) which can degrade performance in practice. Thus, it is necessary to develop an accurate model for RCN in designing RCN-aware eACO-OFDM schemes. To this end, this paper provides a mathematical analysis of RCN leading to an accurate model of RCN power. The obtained model is used to analyse the performance of various eACO-OFDM schemes. It is shown that the model provides an accurate evaluation of symbol error rate (SER), which would be underestimated if RCN is ignored. Moreover, the model is shown to be useful for designing an RCN-aware resource allocation that increases the robustness of the system in terms of meeting a target SER, compared to an RCN-unaware design.

The continuous improvement in optical energy harvesting devices motivates the development of visible light communication systems that utilize such available free energy. In this paper, an outdoor visible light communications (VLC) system is considered where a VLC base station sends data to multiple users that are capable of harvesting optical energy. The proposed VLC system serves multiple users using time division multiple access (TDMA) with unequal time and power allocation, which are allocated to achieve the system communications and illumination objectives. In an outdoor setup, the system lighting objective is to maximize the average illumination flux, while the communication design objective is to maximize the spectral efficiency (SE). A multiobjective optimization problem is formulated to obtain the Pareto front of the SE-illumination region. To this end, the marginal optimization problems are solved first using low complexity algorithms. Then, based on the proposed algorithms, a Karush-Kuhn-Tucker-based algorithm is developed to obtain an inner bound of the Pareto front for the SE-illumination tradeoff. The inner bound for the Pareto-front is shown to be close to the optimal Pareto-frontier via several simulation scenarios for different system parameters.

A network model is considered, where Poisson distributed base stations transmit to N power-domain nonorthogonal multiple access (NOMA) users (TIEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA TIEs and consider two different ordering techniques for the NOMA TIEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical TIE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate Rtot, for general N, constrained to: 1) a minimum throughput T for each TIE, 2) identical throughput for all TIEs. We show the existence of: 1) an optimum N that maximizes the constrained Rtotgiven a set of network parameters and 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters N, the constraints, and the ordering technique to balance the Rtotand fairness requirements. We also show that interference-aware TIE clustering can significantly improve performance.

This paper investigates the secrecy performance of the multiple-input single-output visible light communication (VLC) wiretap channel. The considered system model comprises three nodes: a transmitter (Alice) equipped with multiple fixtures of LEDs, a legitimate receiver (Bob), and an eavesdropper (Eve), each equipped with one photo-diode. The VLC channel is modeled as a real-valued amplitude-constrained Gaussian channel. Eve is assumed to be randomly located in the same area as Bob. Due to this, artificial noise-based beamforming is adopted as a transmission strategy in order to degrade Eve's signal-to-noise ratio. Assuming discrete input signaling, we derive an achievable secrecy rate in a closed-form expression as a function of the beamforming vectors and the input distribution. We investigate the average secrecy performance of the system using stochastic geometry to account for the location randomness of Eve. We also adopt the truncated discrete generalized normal (TDGN) as a discrete input distribution. We present several examples through which we confirm the accuracy of the analytical results via Monte Carlo simulations. The results also demonstrate that the TDGN distribution, albeit being not optimal, yields performance close to the secrecy capacity.

The characterization of fundamental performance bounds of many-to-many communication systems in which participating nodes are active in an intermittent way is one of the major challenges in communication theory. In order to address this issue, we introduce the multiple-input multiple-output (MIMO) three-way channel (3WC) with an intermittent node and study its degrees-of-freedom (DoF) region and sum-DoF. We devise a non-adaptive encoding scheme based on zero-forcing, interference alignment, and erasure coding, and show its DoF region (and thus sum-DoF) optimality for non-intermittent 3WCs and its sum-DoF optimality for (node-) intermittent 3WCs. However, we show by example that in general some DoF tuples in the intermittent 3WC can only be achieved by adaptive schemes such as decode-forward relaying. This shows that non-adaptive encoding is sufficient for the non-intermittent 3WC and for the sum-DoF of intermittent 3WCs but adaptive encoding is necessary for the DoF region of intermittent 3WCs. This paper contributes to a better understanding of the fundamental limits of multi-way communication systems with intermittency and the impact of adaptation therein.

Visible light communications (VLCs), in general, and resource allocation for VLC networks in particular, have gained lots of attention recently. In this paper, we consider the resource allocation problem of a VLC downlink transmission system employing dynamic time division multiple access, where time and power variables are tuned to maximize the downlink spectral efficiency (SE). As for the operational conditions, we impose constraints on the average optical intensity, the energy budget, and the quality-of-service. To solve this non-convex problem, we transform the objective function into a difference of concave functions by solving a second-order differential inequality. Then, we propose a low-complexity algorithm to solve the resource allocation problem. Finally, we show by simulations the SE performance gains achieved by optimizing time and power allocation over the initial total power minimization solution for the considered system.

In this work, we consider a sparse code multiple access uplink system, where J users simultaneously transmit data over K subcarriers, such that J > K, with a constraint on the power transmitted by each user. To jointly optimize the subcarrier assignment and the transmitted power per subcarrier, two new iterative algorithms are proposed, the first one aims to maximize the sum-rate (Max-SR) of the network, while the second aims to maximize the fairness (Max-Min). In both cases, the optimization problem is of the mixed-integer nonlinear programming (MINLP) type, with non-convex objective functions, which are generally not tractable. We prove that both joint allocation problems are NP-hard. To address these issues, we employ a variant of the block successive upper-bound minimization (BSUM) framework, obtaining polynomial-time approximation algorithms to the original problem. Moreover, we evaluate the algorithms' robustness against outdated channel state information (CSI), present an analysis of the convergence of the algorithms, and a comparison of the sum-rate and Jain's fairness index of the novel algorithms with three other algorithms proposed in the literature. The Max-SR algorithm outperforms the others in the sum-rate sense, while the Max-Min outperforms them in the fairness sense.

In this paper, we comprehensively investigate the achievable rates of selected band-limited intensity modulation schemes, which are important for optical wireless communication applications, while accounting for the specific nature of their signal construction (non-negative, real, and baseband), and imposing identical bandwidth and average optical power constraints. Furthermore, we identify/devise methods to effectively trade between these parameters. Three variants of orthogonal frequency division multiplexing (OFDM), namely, asymmetrically clipped optical OFDM (ACO-OFDM), spectrally and energy efficient OFDM (SEE-OFDM), and dc-biased optical OFDM (DCO-OFDM), and single-carrier pulse amplitude modulation are studied. The clipping noise in ACO-OFDM and SEE-OFDM is found to consume a large excess bandwidth. The detrimental effects of this excess bandwidth on the achievable rate are evaluated. For SEE-OFDM, the problem of optimal power allocation among its components is formulated and solved using the Karush-Kuhn-Tucker method. For DCO-OFDM, the clipping noise is modeled and incorporated in the analysis. Among the existing schemes, DCO-OFDM yields the best overall performance, due to its compact spectrum. In order to improve the achievable rate, we propose and analyze two improved distortionless variants, filtered ACO-OFDM and filtered SEE-OFDM (FSEE-OFDM), which yield better spectral efficiency than ACO-OFDM and SEE-OFDM, respectively. FSEE-OFDM, being the most spectrally efficient, outperforms all schemes.

-Non-orthogonal multiple access (NOMA) is a spectrum reutilization technique that superposes messages in the power domain allowing multiple users to be served in the same time-frequency resource block. Successive interference cancellation (SIC) techniques are used for decoding NOMA. A network model is considered where Poisson distributed base stations transmit toNNOMA users each. We present a signal-to-interference-and-noise-ratio analysis for the coverage of the typical user. Due to SIC, coverage implies the ability to decode the messages of all weaker users in the SIC chain. An efficient algorithm for finding a feasible resource allocation that maximizes the cell sum rate ℛtotsubject to a minimum rate constraintTon the individual users is provided for generalN. We show the existence of an optimumNthat maximizes ℛtotgiven a set of network parameters. We also show that NOMA outperforms orthogonal multiple access if the residual intracell interference is below a certain level. The results highlight the importance in choosing network parametersNandTto balance ℛtotand fairness.

An emerging trend of next generation communication systems is to provide network edges with additional capabilities such as additional storage resources in the form of caches to reduce file delivery latency. To investigate this aspect, we study the fundamental limits of a cache-aided wireless network consisting of one central base station, M transceivers and K receivers from a latency-centric perspective. We use the normalized delivery time (NDT) to capture the per-bit latency for the worst-case file request pattern at high signal-to-noise ratios (SNR), normalized with respect to a reference interference-free system with unlimited transceiver cache capabilities. For various special cases that satisfy K+M≤4, we establish the optimal tradeoff between cache storage and latency. This is facilitated through establishing a novel converse (for arbitrary M and K) and an achievability scheme on the NDT. Our achievability scheme is a synergistic combination of multicasting, zero-forcing beamforming and interference alignment.

The capacity of the intensity-modulation direct-detection (IM-DD) multiple-input multiple-output channel is studied under average and peak intensity constraints. We focus on the low signal-to-noise ratio (SNR) regime where the constraints proportionally vanish, or alternatively, where the noise power is large. A general upper bound on the capacity of this channel is derived. Then, this bound is shown to be tight at low SNR, where it coincides with the achievable rate of (i) on-off keying (OOK), spatial repetition coding, and maximum-ratio combining under individual average constraint and (ii) OOK with maximally-correlated inputs under a sum average constraint. This leads to a low-SNR capacity characterization of the channel.

Multi-way and device-to-device (D2D) communications are currently considered for the design of future communication systems. Unmanned aerial vehicles (UAVs) can be effectively deployed to extend the communication range of D2D networks. To model the UAV-D2D interaction, we study a multi-antenna multi-way channel with two D2D users and an intermittently available UAV node. The performance in terms of sum-rate of various transmission schemes is compared. Numerical results show that for different ground environments, the scheme based on a combination of interference alignment, zero-forcing and erasure-channel treatment outperforms other schemes at low, medium and high SNRs and thus represents a viable transmission strategy for UAV-aided multi-way D2D networks.

We investigate Gaussian widely linear precoding known as improper Gaussian signaling for the cellular uplink with inter-cell interference, known as interference multiple access channel (IMAC). This transmission scheme provides extra degrees of freedom by treating the real and imaginary components of the complex Gaussian signal differently. Since current standards mainly utilize linear beamforming for waveform generation, we highlight the benefits of widely linear beamforming over multiple temporal dimensions (symbol extension in time) in the IMAC. This scheme achieves significantly higher information rates compared to conventional proper Gaussian signaling at the expense of extra complexity at the transmission phase. We study the sum-power minimization problem under rate constraints. This problem is a difference of concave functions (DC) program, hence, a non-convex problem. By numerical simulations, we observe the benefits of improper Gaussian signaling alongside symbol extension in power consumption for both single-antenna and multi-antenna base stations. Interestingly, we observe that at strong interference scenarios, the efficiency of improper Gaussian signaling outperforms conventional proper Gaussian signaling at low rate demands. Moreover, in such scenarios the sum-power required for achieving particular rate demands is significantly reduced.

The low-SNR asymptotic capacity of the multiple-input multiple-output (MIMO) optical intensity channel is studied under both average and peak intensity constraints. We focus on low SNR, which can be modeled as the scenario where both constraints proportionally vanish, or where the peak constraint is held constant while the average constraint vanishes. A capacity upper bound is derived and is shown to be tight at low SNR under both scenarios. The capacity achieving input distribution at low SNR is shown to be a maximally correlated vector-binary input distribution. Consequently, the low-SNR capacity of the channel is characterized. As a byproduct, it is shown that for a channel with peak intensity constraints only, or with peak intensity constraints and individual (per aperture) average intensity constraints, a simple scheme composed of coded ON-OFF keying, spatial repetition, and maximum-ratio combining is optimal at low SNR.

An optical wireless intensity-modulation direct-detection multiple-input multiple-output communication system is considered. The performance of $M$ -PAM rate-1 direct current offset space-time block codes is studied in terms of average worst-case pairwise error probability (WC-PEP) in quasi-static channels. It is shown that within this code class, the average WC-PEP is minimized by repetition coding (RC) under both electrical and optical individual power constraints, irrespective of channel statistics. This agrees with previously published results related to ON-OFF keying RC. This is further extended to sum power constraints, where it is shown that spatial beamforming minimizes the average WC-PEP within this code class, which simplifies to RC if the channel matrix has independent and indentically distributed columns and a sum electrical power constraint. Under a sum optical power constraint, this also holds true at high signal-to-noise ratio (SNR), but not at low SNR. Generally, the time dimension of this code class is redundant from an average WC-PEP perspective. Numerical results are provided to support the theoretical findings and to show that the average WC-PEP leads to a good approximation of the actual error probability at high SNR.

The capacity of the intensity modulation direct detection multiple-input-multiple-output channel is studied. Therein, the nonnegativity constraint of the transmit signal limits the applicability of classical schemes, including precoding. Thus, new ways are required for deriving capacity bounds for this channel. To this end, capacity lower bounds are developed in this paper by deriving the achievable rates of two precoding-free schemes: channel inversion and orthogonal-upper triangular matrix product decomposition. The achievable rate of a dc-offset singular-value decomposition-based scheme is also derived as a benchmark. Then, capacity upper bounds are derived and compared against the lower bounds. As a result, the capacity at high signal-to-noise ratio (SNR) is characterized for the case where the number of transmit apertures is not larger than the number of receive apertures, and is shown to be achievable by the QR decomposition scheme. This is shown for a channel with average intensity or peak intensity constraints. Under both constraints, the high-SNR capacity is approximated within a small gap. Extensions to a channel with more transmit apertures than receive apertures are discussed, and capacity bounds for this case are derived.

The capacity of MIMO intensity modulation channels is studied. The non-negativity of the transmit signal (intensity) poses a challenge on the precoding of the transmit signal, which limits the applicability of classical schemes in this type of channels. To resolve this issue, capacity lower bounds are developed by using precoding-free schemes. This is achieved by channel inversion or QR decomposition to convert the MIMO channel to a set of parallel channels. The achievable rate of a DC-offset SVD based scheme is also derived as a benchmark. Then, a capacity upper bound is derived and is shown to coincide with the achievable rate of the QR decomposition based scheme at high SNR, consequently characterizing the high-SNR capacity of the channel. The high-SNR gap between capacity and the achievable rates of the channel inversion and the DC-offset SVD based schemes is also characterized. Finally, the ergodic capacity of the channel is also briefly discussed.

Information-theoretic and signal processing aspects of some modulation schemes designed for intensity modulation/direct detection (IM/DD) optical wireless communication (OWC) systems are studied. Due to the constraints of IM/DD signals (non-negative real and baseband signals), the construction of these signals along with their time and frequency characteristics differ from their RF counterparts. This necessitates a careful study of such schemes under practical constraints. Three schemes are studied in this paper, namely, single carrier pulse amplitude modulation (SC-PAM), asymmetrically clipped optical OFDM (ACO-OFDM), and DC biased optical OFDM (DCO-OFDM). Our aim is to carry out a comparative study of these schemes in the presence of identical constraints on bandwidth and average optical power. The study reveals that the clipping operation required in ACO-OFDM significantly reduces its information rate, and as a result, it is outperformed by SC-PAM. Such a limitation does not apply to DCO-OFDM which has a higher information rate, even though part of the available optical power is expended in the non-information-bearing DC bias.

The degrees-of-freedom (DoF) of the multi-antenna three-way channel (3WC) with an intermittent node is studied. Special attention is given to the impact of adaptation when the intermittent node has the largest number of antennas. A non-adaptive transmission scheme based on interference alignment, zero-forcing, and erasure-channel treatment is proposed, and its corresponding DoF region is derived. Then, it is shown that this scheme achieves the sum-DoF of the intermittent channel, in addition to the DoF region of the nonintermittent one. Thus, adaptation is not necessary from those perspectives. To the contrary, it is shown that adaptation is necessary for achieving the DoF region of the intermittent case. This is shown by deriving an outer bound for the intermittent channel with nonadaptive encoding, and proposing an adaptive scheme which achieves DoF tuples outside this bound. This highlights the importance of cooperation in this intermittent network.

The capacity region of the class of injective semi-deterministic two-way channels (TWCs) is investigated in this paper. To characterize this capacity, two conditions under which Shannon's bounds on the capacity region of TWCs are tight are first given. Using those conditions, it is shown that the capacity of this class of TWCs is characterized by the rectangle formed by the one-way capacities. This proves that adaptation is not needed for this class. This class encompasses, among others, all memoryless additive channels with input-independent noise, and hence, adaptation is useless for all such channels. This also shows that there exist continuous additive TWCs not of the exponential family type for which adaptation is not necessary. An example of a Cauchy TWC is given, and its capacity is characterized in closed form under a logarithmic constraint. Finally, the impact of the dependence of the noise on the inputs is discussed, and it is shown that adaptation may still be useless in such cases.

In this paper, an optical wireless multiple-input single-output communication system employing intensity-modulation direct-detection is considered. Subject to a per transmit-aperture power constraint, the performance of direct current (DC) offset space-time block codes (STBC) is studied in terms of pairwise error probability (PEP). It is shown that among the class of DC-STBCs, the worst case PEP, i.e., the one corresponding to the minimum distance between two codewords, is minimized by repetition coding (RC) for any channel state. Therefore, it follows that among all DC-STBCs, RC is optimal in terms of worst case PEP under any turbulence statistics. This result agrees with previously published numerical results showing the superiority of RC in such systems. It also agrees with previously published analytical results on this topic under lognormal turbulence and further extends it to arbitrary turbulence statistics. Numerical results provided to verify this indicate that RC is not only optimal in terms of worst case PEP, but also in terms of average error probability.

This paper derives and analyzes the outage probability of mixed radio frequency (RF)/unified free space optical (FSO) dual-hop decode-and-forward (DF) relaying scheme, where heterodyne detection (HD) and intensity modulation-direct detection (IM-DD) are considered for FSO detection. In doing that, we correctly utilize, for the first time to the best of our knowledge, a precise channel capacity result for the IM-DD channel. Moreover, this is the first time that not only the (IM-DD input-independent) but also the (IM-DD cost-dependent) AWGN channel is considered in such system analysis. This work assumes that the first hop (RF link) follows Naka-gami-m fading, while the second hop (FSO link) follows Málaga (M) turbulence with pointing error. These fading and turbulence models include other ones (such as Rayleigh fading and Gamma-Gamma turbulence) as special cases, so our analysis can be considered as a generalized one from both RF and FSO fading models point of view. Additionally, the system outage probability is investigated asymptotically in high signal-to-noise ratio (SNR) regime, where a new non-reported diversity order and coding gain analysis are shown. Interestingly, we find that in the FSO hop, based on SNR, the HD or IM-DD cost-dependent results in a same diversity order which is twice the one of IM-DD input-independent. However, based on transmitted power all these FSO detectors result in a same diversity order. Furthermore, we offer simulation results which confirm the derived exact and asymptotic expressions.

Finite energy reserves and the irreplaceable nature of nodes in battery-driven wireless sensor networks (WSNs) motivate energy-aware network operation. This paper considers energy-efficiency in a WSN by investigating the problem of minimizing the power consumption consisting of both radiated and circuit power of sensor nodes, so as to determine an optimal set of active sensors and corresponding transmit powers. To solve such a mixed discrete and continuous problem, the paper proposes various sensor selection and power allocation algorithms of low complexity. Simulation results show an appreciable improvement in their performance over a system in which no selection strategy is applied, with a slight gap from derived lower bounds. The results further yield insights into the relationship between the number of activated sensors and its effect on total power in different regimes of operation, based on which recommendations are made for which strategies to use in the different regimes.

Multi-channel (MC) optical wireless communication (OWC) systems employing wave-division multiplexing for outdoors free-space optical communications, or multi-user time-division multiple access for indoors visible-light communications, e.g., can be modeled as parallel channels. Multi-input multi-output OWC systems can also be transformed, possibly with some performance loss, to parallel channels using pre-/post-coding. Studying the performance of such MC-OWC systems requires characterizing the capacity of the underlying parallel channels. In this paper, upper and lower bounds on the capacity of constant parallel OWC channels with a total average intensity constraint are derived. Then, this paper focuses on finding intensity allocations that maximize the lower bounds given channel-state information at the transmitter (CSIT). Due to its nonconvexity, the Karush-Kuhn-Tucker conditions are used to describe a list of candidate allocations. Instead searching exhaustively for the best solution, low-complexity near-optimal algorithms are proposed. The resulting optimized lower bound nearly coincides with capacity at high signal-to-noise ratio (SNR). Under a quasi-static channel model and in the absence of CSIT, outage probability upper and lower bounds are derived. Those bounds also meet at high SNR, thus characterizing the outage capacity in this regime. Finally, the results are extended to a system with both average and peak intensity constraints.

Treating interference as noise (TIN) as the most appropriate approach in dealing with interference and the conditions on its optimality has attracted the interest of researchers recently. However, our knowledge on necessary and sufficient conditions of TIN is restricted to a few setups with limited number of users. In this paper, we study the optimality of TIN in terms of the generalized degrees of freedom (GDoF) for a fundamental network, namely, the M × 2 X-channel. To this end, the achievable GDoF of TIN with power allocations at the transmitters is studied. It turns out that the transmit power allocation maximizing the achievable GDOF is given by ON-OFF signaling as long as the receivers use TIN. This leads to two variants of TIN, namely, P2P-TIN and 2-IC-TIN. While in the first variant the M × 2 X-channel is reduced to a point-topoint (P2P) channel, in the second variant, the setup is reduced to a two-user interference channel in which the receivers use TIN. The optimality of these two variants is studied separately. To this end, novel genie-aided upper bounds on the capacity of the X-channel are established. The conditions on the optimality of P2P-TIN can be summarized as follows. P2P-TIN is GDoF-optimal if there exists a dominant multiple access channel or a dominant broadcast channel embedded in the X channel. Furthermore, the necessary and sufficient conditions on the GDoF-optimality of 2-IC-TIN are presented. Interestingly, it turns out that operating the M × 2 X-channel in the 2-IC-TIN mode might be still GDOF optimal, although the conditions given by Geng et al. are violated. However, 2-IC-TIN is sub-optimal if there exists a single interferer which causes sufficiently strong interference at both receivers. The comparison of the results with the state of the art shows that the GDOF optimality of TIN is expanded significantly.

Optical wireless communications (OWC) is a promising technology for closing the mismatch between the growing number of connected devices and the limited wireless network capabilities. Similar to downlink, uplink can also benefit from OWC for establishing connectivity between such devices and an optical access point. In this context, the incoherent intensity-modulation and direct-detection (IM-DD) scheme is desirable in practice. Hence, it is important to understand the fundamental limits of communication rates over an OWC uplink employing IM-DD, i.e., the channel capacity. This uplink, modeled as a Gaussian multiple-access channel (MAC) for indoors OWC, is studied in this paper, under the IM-DD constraints, which form the main difference with the standard Gaussian MAC commonly studied in the radio-frequency context. Capacity region outer and inner bounds for this channel are derived. The bounds are fairly close at high signal-to-noise ratio (SNR), where a truncated-Gaussian input distribution achieves the capacity region within a constant gap. Furthermore, the bounds coincide at low SNR showing the optimality of ON-OFF keying combined with successive cancellation decoding in this regime. At moderate SNR, an optimized uniformly spaced discrete input distribution achieves fairly good performance.

We improve upon our previous upper bound on the secrecy capacity of the wiretap channel with multiple transmit antennas and single-antenna receivers, with noisy main channel state information (CSI) at the transmitter (CSI-T). Specifically, we show that if the main CSI error does not scale with the power budget at the transmitter P̅, then the secrecy capacity is )bounded above essentially by log log (P̅ yielding a secure degree of freedom (sdof) equal to zero. However, if the main CSI error scales as O(P̅-β), for β ∈ [0,1], then the sdof is equal to β.

A system consisting of parallel intensity-modulation direct-detection optical wireless channels with a total average intensity constraint is studied. Capacity upper and lower bounds for this system are derived. If channel-state information is available at the transmitter, the bounds have to be optimized with respect to intensity allocation over the parallel channels. The optimization of the lower bound is non-convex, however, the Karush-Kuhn-Tucker conditions can be used to find a list of possible solutions one of which is optimal. The optimal solution can then be found by an exhaustive search algorithm, which is computationally expensive. To overcome this, we propose a low-complexity intensity allocation algorithm which is nearly optimal. The optimized capacity lower bound coincides with the capacity at high signal-to-noise ratio.

Optical wireless communications (OWC) is a potential solution for coping with the mismatch between the users growing demand for higher data-rates and the wireless network capabilities. In this paper, a multi-user OWC scenario is studied from an in formation-theoretic perspective. The studied network consists of two users communicating simultaneously with one access point using OWC, thus establishing an optical uplink channel. The capacity of this network is an important metric which reflects the highest possible communication rates that can be achieved over this channel. Capacity outer and inner bounds are derived, and are shown to be fairly tight in the high signal-to-noise ratio regime.

Self interference (SI) in full duplex (FD) systems is the interference caused by the transmission stream on the reception stream. Being one of the main restrictive factors for performance of practical full duplex systems, however, not too much is known about its effect on the fundamental limits of relaying systems. In this work, we consider the full duplex three-node relay channel with SI where SI is modeled as an additive Gaussian noise whose variance is dependent on instantaneous input power. The classical achievable rates and upper bounds for the single three-node relay channel no longer apply due to the structure of SI. Achievable rates for Decode-and-Forward (DF) and Compress-and-Forward (CF) and upper bounds on the capacity are derived assuming Gaussian inputs and SI. The deterministic model is also introduced and its capacity is characterized. The optimal joint source-relay distributions is discussed. Numerical results are provided comparing the achievable rates and upper bound.

The capacity of the free-space optical channel is studied. A new recursive approach for bounding the capacity of the channel based on sphere-packing is proposed. This approach leads to new capacity upper bounds for a channel with a peak intensity constraint or an average intensity constraint. Under an average constraint only, the derived bound is tighter than an existing sphere-packing bound derived earlier by Farid and Hranilovic. The achievable rate of a truncated-Gaussian input distribution is also derived. It is shown that under both average and peak constraints, this achievable rate and the sphere-packing bounds are within a small gap at high SNR, leading to a simple high-SNR capacity approximation. Simple fitting functions that capture the best known achievable rate for the channel are provided. These functions can be of practical importance especially for the study of systems operating under atmospheric turbulence and misalignment conditions.

A network of three nodes mutually communicating with each other is studied. This multi-way network is a suitable model for three-user device-to-device communications. The main goal of this paper is to characterize the capacity region of the underlying Gaussian three-way channel (3WC) within a constant gap. To this end, a capacity outer bound is derived using cut-set bounds and genie-aided bounds. For achievability, the 3WC is first transformed into an equivalent star channel. This latter is then decomposed into a set of “successive” sub-channels, leading to a sub-channel allocation problem. Using backward decoding, interference neutralization, and known results on the capacity of the star-channel relying of physical-layer network coding, an achievable rate region for the 3WC is obtained. It is then shown that the achievable rate region is within a constant gap of the developed outer bound, leading to the desired capacity approximation. Interestingly, in contrast to the Gaussian two-way channel (TWC), adaptation is necessary in the 3WC. Furthermore, message splitting is another ingredient of the developed scheme for the 3WC, which is not required in the TWC. The two setups are, however, similar in terms of their sum-capacity pre-log, which is equal to 2. Finally, some interesting networks and their approximate capacities are recovered as special cases of the 3WC, such as the cooperative broadcast channel and multiple access channel.

The symmetric K-user interference channel (IC) is studied with the goal of characterizing its capacity region in the strong interference regime within a constant gap. The achievable rate region of a scheme combining rate splitting at the transmitters and interference alignment and successive decoding/computation at the receivers is derived. Next, it is shown that this scheme achieves the so-called greedy-max corner points of the capacity region within a constant gap. By combining this result with previous results by Ordentlich et al. on the sum-capacity of the symmetric IC, a constant gap characterization of the capacity region for the strong interference regime is obtained. This leads to the first approximate characterization of the capacity region of the symmetric K-user IC. Furthermore, a new scheme that achieves the sum-capacity of the channel in the strong interference regime within a constant gap is also proposed, and the corresponding gap is calculated. The advantage of the new scheme is that it leads to a characterization within a constant gap without leaving an outage set contrary to the scheme by Ordentlich et al.

Despite the simplicity of the scheme of treating interference as noise (TIN), it was shown to be sum-capacity optimal in the Gaussian interference channel (IC) with very-weak (noisy) interference. In this paper, the two-user IC is altered by introducing an additional transmitter that wants to communicate with one of the receivers of the IC. The resulting network thus consists of a point-to-point channel interfering with a multiple access channel (MAC) and is denoted by PIMAC. The sum-capacity of the PIMAC is studied with main focus on the optimality of TIN. It turns out that TIN in its naive variant, where all transmitters are active and both receivers use TIN for decoding, is not the best choice for the PIMAC. In fact, a scheme that combines both time division multiple access and TIN (TDMA-TIN) strictly outperforms the naive-TIN scheme. Furthermore, it is shown that in some regimes, TDMA-TIN achieves the sum-capacity for the deterministic PIMAC and the sum-capacity within a constant gap for the Gaussian PIMAC. In addition, it is shown that, even for very-weak interference, there are some regimes where a combination of interference alignment with power control and TIN at the receiver side outperforms TDMA-TIN. As a consequence, on the one hand, TIN in a cellular uplink is approximately optimal in certain regimes. On the other hand, those regimes cannot be simply described by the strength of interference.

The impact of cooperation on interference management is investigated by studying an elemental wireless network, the so-called symmetric interference relay channel (IRC), from a generalized degrees of freedom (GDoF) perspective. This is motivated by the fact that the deployment of relays is considered as a remedy to overcome the bottleneck of current systems in terms of achievable rates. The focus of this paper is on the regime in which the interference link is weaker than the source-relay link in the IRC. Our approach toward studying the GDoF goes through the capacity analysis of the linear deterministic IRC (LD-IRC). New upper bounds on the sum capacity of the LD-IRC based on genie-aided approaches are established. These upper bounds together with some existing upper bounds are achieved by using four novel transmission schemes. Extending the upper bounds and the transmission schemes to the Gaussian case, the GDoF of the Gaussian IRC is characterized for the aforementioned regime. This completes the GDoF results available in the literature for the symmetric GDoF. It turns out that even if the incoming and outgoing links of the relay are both weaker than the desired channel, involving a relay can increase the GDoF. Interestingly, utilizing the relay in this case can increase the slope of the GDoF from -2 [in the interference channel (IC)] to -1 or 0. This shrinks the regime where ignoring the interference by treating it as noise is optimal. Furthermore, the analysis shows that if the relay ingoing and outgoing links are sufficiently strong, the relay is able to neutralize the interference completely. In this case, the bottleneck of the transmission will be the interference links, and hence, the GDoF increases if the interference link gets stronger. It is shown that in the strong interference regime, in contrast to the IC, the GDoF can be a monotonically decreasing function of the interference level.

The capacity of the intensity-modulation direct-detection optical broadcast channel (OBC) is investigated, under both average and peak intensity constraints. An outer bound on the capacity region is derived by adapting Bergmans' approach to the OBC. Inner bounds are derived by using superposition coding with either truncated-Gaussian (TG) distributions or discrete distributions. While the discrete distribution achieves higher rates, the TG distribution leads to a simpler representation of the achievable rate region. At high signal-to-noise ratio (SNR), it is shown that the TG distribution is nearly optimal. It achieves the symmetric-capacity within a constant gap (independent of SNR), which approaches half a bit as the number of users grows. It also achieves the capacity region within a constant gap. At low SNR, it is shown that on-off keying (OOK) with time-division multiple-access (TDMA) is optimal. This is interesting in practice since both OOK and TDMA have low complexity. At moderate SNR (typically [0,8] dB), a discrete distribution with a small alphabet size achieves fairly good performance.

The impact of multi-hopping schemes on the communication latency in a relay channel is studied. The main aim is to characterize conditions under which such schemes decrease the communication latency given a reliability requirement. Both decode-forward (DF) and amplify-forward (AF) with block coding are considered, and are compared with the point-to-point (P2P) scheme which ignores the relay. Latency expressions for the three schemes are derived, and conditions under which DF and AF reduce latency are obtained for high signal-to-noise ratio (SNR). Interestingly, these conditions are more strict when compared to the conditions under which the same multi-hopping schemes achieve higher long-term (information-theoretic) rates than P2P. It turns out that the relation between the source-destination SNR and the harmonic mean of the SNR's of the channels to and from the relay dictates whether multi-hopping reduces latency or not.

A full-duplex wireless network with three users that want to establish full message exchange via a relay is considered. Thus, this network which is known as the Y-channel has a total of six messages, two outgoing, and two incoming at each user. The users are not physically connected, and thus the relay is essential for their communication. The deterministic Y-channel is considered first, its capacity region is characterized, and shown not to be given by the cut-set bounds. The capacity achieving scheme has three different components (strategies): 1) a bidirectional; 2) a cyclic; and 3) a unidirectional strategy. Network coding is used to realize the bidirectional and the cyclic strategies, and thus to prove the achievability of the capacity region. The result is then extended to the Gaussian Y-channel where the capacity region is characterized within a constant gap independent of the channel parameters.

The K-user multiple-input multiple-output (MIMO) multi-way relay channel (Y-channel) consisting of K users with M antennas each and a common relay node with N antennas is studied in this paper. Each user wants to exchange messages with all the other users through the relay. A transmission strategy is proposed for this channel. The proposed strategy is based on two steps: 1) channel diagonalization and 2) cyclic communication. The channel diagonalization is applied by using zero-forcing beam-forming. After the channel diagonalization, the channel is decomposed into parallel sub-channels. Cyclic communication is then applied, where signal-space alignment for network-coding is used over each sub-channel. The proposed strategy achieves the optimal degree-of-freedom (DoF) region of the channel if N ≤ M. To prove this, a new DoFs outer bound is derived. As a by-product, we conclude that the MIMO Y-channel is not separable, i.e., independent coding on separate sub-channels is not enough, and one has to code jointly over several sub-channels.

A 3-user device-to-device (D2D) communications scenario is studied where each user wants to send and receive a message from each other user. This scenario resembles a 3-way communication channel. The capacity of this channel is unknown in general. In this paper, a sum-capacity upper bound that characterizes the degrees-of-freedom of the channel is derived by using genie-aided arguments. It is further shown that the derived upper bound is achievable within a gap of 2 bits, thus leading to an approximate sum-capacity characterization for the 3-way channel. As a by-product, interesting analogies between multi-way communications and multi-way relay communications are concluded.

The sum-capacity of a three user interference wired network for time-varying channels is considered. Due to the channel variations, it is assumed that the transmitters are only able to track the connectivity between the individual nodes, thus only the (alternating) state of the network is known. By considering a special subset of all possible states, we show that state splitting combined with joint encoding over the alternating states is required to achieve the sum-capacity. Regarding upper bounds, we use a genie aided approach to show the optimality of this scheme. This highlights that more involved transmit strategies are required for characterizing the degrees of freedom even if the transmitters have heavily restricted channel state information.

We investigate the symmetric Degrees-of-Freedom (DoF) of a homogeneous multiple-input multiple-output (MIMO) 3-way channel with MTtransmit antennas and MRreceive antennas at each user. The 3-way channel extends the two-way channel to three users, who exchange six messages in total, i. e., there is one message from each user to each of the two other users. We assume that each user operates in a perfect full-duplex mode. Genie-aided upper bounds on the DoF of the channel are derived and it is shown that those are achievable by combining MIMO interference alignment, null-space beam-forming and zero-forcing. A particular gain from this homogeneous setup is that the symmetric DoF allocation providing complete fairness among all users is sum-DoF optimal.

The degrees of freedom (DoF) of the MIMO Y-channel, a multi-way communication network consisting of 3 users and a relay, are characterized for arbitrary number of antennas. The converse is provided by cut-set bounds and novel genie-aided bounds. The achievability is shown by a scheme that uses beamforming to establish network coding on-the-fly at the relay in the uplink, and zero-forcing pre-coding in the downlink. It is shown that the network has min{2M2+2M3, M1+ M2+ M3,2N} DoF, where Mjand N represent the number of antennas at user j and the relay, respectively. Thus, in the extreme case where M1+M2+M3dominates the DoF expression and is smaller than N, the network has the same DoF as the MAC between the 3 users and the relay. In this case, a decode and forward strategy is optimal. In the other extreme where 2N dominates, the DoF of the network is twice that of the aforementioned MAC, and hence network coding is necessary. As a byproduct of this work, it is shown that channel output feedback from the relay to the users has no impact on the DoF of this channel.

A network where three users want to establish multiple unicasts between each other via a relay is considered. This network is called the Y-channel and resembles an elemental ingredient of future wireless networks. The sum-capacity of this network is studied. A characterization of the sum-capacity within an additive gap of 2 bits, and a multiplicative gap of 4, for all values of channel gains and transmit powers is obtained. Contrary to similar setups where the cut-set bounds can be achieved within a constant gap, they cannot be achieved in our case, where they are dominated by our new genie-aided bounds. Furthermore, it is shown that a time-sharing strategy, in which at each time two users exchange information using coding strategies of the bidirectional relay channel, achieves the upper bounds to within a constant gap. This result is further extended to the${\rm K}$-user case, where it is shown that the same scheme achieves the sum-capacity within$2\log (K-1)$bits.

It was shown recently that the 2-user interference channel with a cognitive relay (IC-CR) has full degrees of freedom (DoF) almost surely, that is, 2 DoF. The purpose of this work is to check whether the DoF of the K-user IC-CR, consisting of K user pairs and a cognitive relay, follow as a straight forward extension of the 2-user case. As it turns out, this is not the case. The k-user IC-CR is shown to have 2K/3 DoF if K >; 2 for the when the channel is time varying, achievable using interference alignment. Thus, while the basic k-user IC with time varying channel coefficients has 1/2 DoF per user for all K, the k-user IC-CR with varying channels has 1 DoF per user if K = 2 and 2/3 DoF per user if K >; 2. Furthermore, the DoF region of the 3-user IC-CR with constant channels is characterized using interference neutralization, and a new upper bound on the sum-capacity of the 2-user IC-CR is given.

The generalized degrees of freedom (GDoF) of the symmetric two-user Gaussian interference relay channel (IRC) is studied. While it is known that the relay does not increase the DoF of the IC, this is not known for the more general GDoF. For the characterization of the GDoF, new sum-capacity upper bounds and lower bounds are derived. The lower bounds are obtained by a new scheme, which is based on functional decode-and-forward (FDF). The GDoF is characterized for the regime in which the source-relay link is weaker than the interference link, which constitutes half the overall space of channel parameters. It is shown that the relay can indeed increase the GDoF of the IRC and that it is achieved by FDF.

A multi-way communication network with three nodes and a relay is considered. The three nodes in this so-called Y-channel, communicate with each other in a bi-directional manner via the relay. Studying this setup is important due to its being an important milestone for characterizing the capacity of larger networks. A transmit strategy for the Gaussian Y-channel is proposed, which mimics a previously considered scheme for the deterministic approximation of the Y-channel. Namely, a scheme which uses nested-lattice codes and lattice alignment is used, to perform network coding. A new mode of operation is introduced, named `cyclic communication', which interestingly turns out to be an important component for achieving the capacity region of the Gaussian Y-channel within a constant gap.

The symmetric two-user Gaussian interference relay channel (IRC) is studied from a generalized degrees of freedom (GDoF) perspective. While it is known that the relay does not in crease the DoF of the IRC, such a characterization has not been reported for the GDoF yet. The focus of this paper is on all cases where the interference link is stronger than the link from the source to the relay. This regime basically covers half the space of all possible parameters of the IRC. By using genie-aided approaches, new sum-capacity upper bounds are derived. These bounds are then compared with rates achieved with a novel transmission scheme, which is based on a functional decode-and-forward (FDF) strategy. It is shown that the GDoF of the IRC is achieved by FDF in the given regime, and that a relay can indeed increase the GDoF of IRC. Finally, the FDF scheme is compared with other schemes like decode-and-forward as well as compress-and-forward at low, moderate, and high signal-to-noise ratios.

The capacity region of the Gaussian cognitive interference network consisting of a primary multiple access channel and a secondary point-to-point system is considered. Its capacity region with weak interference is known. In this paper, the capacity region of a sub-regime of the strong interference regime is studied. An outer bound on the capacity region of this setup with strong interference is derived. An inner bound is shown to coincide with the strong interference outer bound under some conditions, thus characterizing the capacity of this setup for a set of channel parameters.

The linear shift deterministic Y-channel is studied. That is, we have three users and one relay, where each user wishes to broadcast one message to each other user via the relay, resulting in a multi-way relaying setup. The cut-set bounds for this setup are shown to be not sufficient to characterize its capacity region. New upper bounds are derived, which when combined with the cut-set bounds provide an outer bound on the capacity region. It is shown that this outer bound is achievable, and as a result, the capacity region of the linear shift deterministic Y-channel is characterized.

Consider a code C with Hamming distance d. Assume we have a decoder ¿ that corrects ¿ errors and ¿ erasures if ¿¿ + ¿ ¿ d - 1, where a real number 1qlof length nq, where l ¿ {1, 2, . . .} and ¿ = 1+1/l. We propose an m-trial generalized minimum distance (GMD) decoder based on ¿. Our approach extends results of Forney and Kovalev (obtained for ¿ = 2) to the whole given range of ¿. We consider both fixed erasing and adaptive erasing GMD strategies. For l > 1 the following approximations hold. For the fixed erasing strategy the error correcting radius is ¿F¿ d/2 (1 - l-m/2). For the adaptive erasing strategy, ¿A¿ d/2 (1 - l-2m) quickly approaches d/2 if l or m grows. The minimum number of decoding trials required to reach an error correcting radius d/2 is mA= 1/2 (logld + 1). This means that 2 or 3 trials are sufficient to reach ¿A= d/2 in many practical cases if l > 1.

A systems approach is used to model the "telecommunications system". The system elements, actors and processes are briefly described, together with the interrelations of the elements and their theoretical optimum status. Practical restrictions and limitations exist as factors that take the system away from the optimum, and some recommendations to get some equilibrium point, are presented.