In this paper, we investigate the impedance matching problem for realistic arrays of lossy and mutually coupled antennas, aiming to enhance the beamforming performance of the system. We develop a novel method to optimize the characteristic and load impedances in the transmit circuit that drives the antenna array. Numerical results are provided to show that the developed method has a faster convergence speed with considerably lower computational complexities than an existing impedance optimization method, while it can achieve almost the same favorable performance as the latter.

We investigate the beamforming performances of holographic surfaces implemented as arrays of densely deployed, lossy, and identical antennas. We first develop a general model to characterize the mutual coupling effect among the antennas arbitrarily distributed in a holographic surface, and then discuss the beamforming design as well as the characteristic and load impedance optimization of the holographic radio system. CST-based electromagnetic simulations indicate that the proposed beamforming design with impedance optimization significantly increases the realized beamforming gain of a conventional halfwavelength spaced antenna array, and array densification within the same surface aperture further enhances this benefit. The enhancement is particularly noticeable when the target direction is close to the spatial direction in which the array is densified.

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

In this paper, we investigate the beamforming performance of holographic surfaces implemented as lossless antenna arrays with less than half-wavelength spacing. We first develop a method to quantify the mutual coupling effect among the antennas in an array. The developed coupling model is general and applicable to arrays with arbitrary distribution of any type of antennas with arbitrary structure, physical size and radiation power pattern. In particular, it reduces to a neat analytical expression for arbitrarily deployed isotropic antenna arrays. We then discuss the beamforming design for holographic surfaces, and in particular provide analytical beamforming characterizations for arrays with two arbitrarily spaced isotropic antennas. Numerical results indicate that, by accounting for the mutual coupling effect between antennas, the array densification by packing more antennas in a given surface aperture can significantly enhance both the beamforming gain and spatial resolution of the system. The beamforming gain enhancement and beamwidth reduction can be several dBs higher than, and more than half of, those achieved by the conventional half-wavelength spaced antenna arrays in the same surface aperture. The gains of densification become saturated when the antenna spacing is below a critical value, and the saturated gain reduces as the surface aperture increases.

We investigate the performances of line-of-sight (LoS) holographic transmission links. To this end, we first develop a simple channel model for LoS holographic radio systems. This model can be reduced to represent the conventional LoS multiple-input multiple-output (MIMO) channel, and further used to make a fair comparison between them. We then analytically show that, in the far-field scenario when both the transmitter and receiver are equipped with holographic surfaces to form a LoS holographic-input holographic-output (HIHO) system, the achievable power gain can be up to π2times higher than the corresponding LoS MIMO system with half-wavelength spaced isotropic antenna arrays deployed in the same transmit/receive apertures. Furthermore, numerical results indicate that concurrent transmissions of multiple signal streams can be supported in both the LoS HIHO and MIMO systems at communication distances shorter than that in the far-field scenario. Specifically, by moving from isotropic antenna arrays to holographic surfaces we virtually keep the same spatial sub-channels as those of the LoS MIMO system but with notably boosted power gains.

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

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

We propose a novel framework to enable concurrent transmission of multiple users to an access node equipped with a massive multiple-input multiple-output (mMIMO), which encompasses and extends the conventional time-division duplex (TDD) protocol and the recently proposed semi-orthogonal multiple-access (SOMA). The new solution is referred to generalized semi-orthogonal multiple-access (GSOMA). To enable GSOMA, the users are grouped such that the users within each group are assigned mutually orthogonal pilot sequences. However the pilot sequences can be reused in different groups and the users in different group are coordinated such that their pilot sequences do not interfere by a semi-orthogonal mechanism enabled by a resource-offset sequence. We describe the general framework and analyze a case of GSOMA and show that a properly designed GSOMA can outperform the conventional TDD and SOMA.

This paper considers the ergodic block fading multi-user Gaussian interference channel (IC) in which each source desires to communicate to an intended destination. We assume that there is no CSI a priori available at terminals. We develop achievable rate results and compute the associated degrees of freedom by using a pilot-assisted interference alignment scheme. In this scheme, each source first sends known pilot symbols via which the destinations estimate channel gains, and the destinations then broadcast the estimated channel gains via orthogonal feedback channels. The estimated channel gains are used to perform interference alignment for data transmission. The pilot transmission power can be different from the data transmission power. By allocating more power to pilot transmission, channel gains can be estimated more accurately which implies less power left for data transmission. We find the optimum power allocation to pilot symbols and data symbols. Our study recommends, in large networks, to allocate more power to channel training instead of data transmission. In addition, our results reveal that for a K-user ergodic IC with a coherence time T, the total degrees of freedom 1/2 Kopt(1-Kopt/T) is achievable, where Kopt= min {K, T/2} is the optimum number of users selected to be active in the network. This recommends to perform a user selection in large networks (K > T/2), and apply channel training and interference alignment within the set of selected users.

The authors study a two‐user state‐dependent generalised multiple‐access channel (GMAC) with correlated states. It is assumed that each encoder has ‘non‐causal’ access to channel state information (CSI). They develop an achievable rate region by employing rate‐splitting, block Markov encoding, Gelfand–Pinsker multicoding, superposition coding and joint typicality decoding. In the proposed scheme, the encoders use a partial decoding strategy to collaborate in the next block, and the receiver uses a backward decoding strategy with joint unique decoding at each stage. The author's achievable rate region includes several previously known regions proposed in the literature for different scenarios of multiple‐access and relay channels. Then, they consider two Gaussian GMACs with additive interference. In the first model, they assume that the interference is known non‐causally at both of the encoders and construct a multi‐layer Costa precoding scheme that removes ‘completely’ the effect of the interference. In the second model, they consider a doubly dirty Gaussian GMAC in which each of interferences is known non‐causally only at one encoder. They derive an inner bound and analyse the achievable rate region for the latter model and interestingly prove that if one of the encoders knows the full CSI, there exists an achievable rate region which is ‘independent’ of the power of interference.

We investigate the time-varying Gaussian interference channel (IC) in which each source desires to communicate to an intended destination. For the ergodic time-varying IC with global perfect CSI at all terminals, it has been known that with an interference alignment technique each source-destination pair can communicate at half of the interference-free achievable rate. In practice, the channel gains are estimated by transmitting known pilot symbols from the sources, and the channel estimation procedure is hence prone to errors. In this paper, we model the channel estimation error at the destinations by an independent additive Gaussian noise and study the behavior of the ergodic interference alignment scheme with the global noisy CSI at all terminals. Toward this end, we present a closed-form inner bound on the achievable rate region by which we conclude that the achievable degrees of freedom with global perfect CSI can be preserved, if the variance of channel estimation error is proportional to the inverse of the transmitted power.

This paper considers the problem of communicating over a relay channel with state when noncausal state information is partially available at the nodes. We first establish a lower bound on the achievable rates based on noisy network coding and Gelfand-Pinsker coding, and show that it provides an alternative characterization of a previously known bound. We then introduce the class of state-decoupled relay channels and show that our lower bound is tight for a subclass of semideterministic channels. We also compute the capacity for two specific examples of this subclass - a channel with multiplicative binary fading and a channel with additive Gaussian interference. These examples are not special cases of previous classes of semideterministic relay channels with known capacity.

An achievable rate region based on Shannon's inner bound is given for the two-way relay channel. The relaying scheme operates on noisy received signals and generates new analog values to be transmitted to a destination. The scheme is therefore referred to as noisy analog network coding. The achievable rates are then optimized for a Gaussian two-way relay channel, when the relay is memoryless (this type of relaying is also known as instantaneous relaying). For one particular instance of the channel when the received signal at the relay is noiseless, it is shown that instantaneous noisy analog network coding can be optimal. For the noisy case, a numerical optimization algorithm is presented in order to optimize the instantaneous coding strategy. The optimized analog mapping turns out to be nonlinear and periodic. Finally, it is demonstrated that the achievable rates associated with optimized mappings can outperform those achieved by linear relaying, compress-and-forward, and can operate close to the recently proposed noisy network coding scheme.

We consider the three-node Gaussian relay channel where the relay observes a noisy version of the interference present in the source--destination link. We investigate three fundamental relaying approaches: linear relaying, memoryless nonlinear relaying, and compress-and-forward (CF). For interference-limited cases, we illustrate that optimized memoryless nonlinear relaying almost achieves the capacity.

The Gaussian, three-node relay channel with orthogonal receive components (i.e., the transmitted signals from the source and the relay do not interfere with each other) is investigated. For such channels, linear relaying is a suboptimal strategy in general. This is because a linear scheme merely repeats the received noisy signal and does not utilize the available degrees of freedom efficiently. At this background, nonlinear, symbol-wise (as opposed to block-wise) relaying strategies are developed to compensate for the shortcomings of the linear strategy. Optimal strategies are presented for two special cases of the general scenario, and it is shown that memoryless relaying can achieve the capacity. Furthermore, for the general Gaussian relay channel, a parametricpiecewise linear(PL) mapping is proposed and analyzed. The achievable rates obtained by the PL mapping are computed numerically and optimized for a certain number of design parameters. It is concluded that optimized PL relaying always outperforms conventional instantaneous linear relaying (amplify-and-forward). It is also illustrated that the proposed PL relaying scheme can improve on sophisticated block Markov encoding (i.e., decode-and-forward) when the source-relay link is ill-conditioned (relative to other links). Furthermore, PL relaying can work at rates close to those achieved by side-information encoding (i.e., compress-and-forward), but at a much lower complexity.

We study a three-node Gaussian relay channel with interference which is non-causally known at the source. It is assumed that the interference affects only the relay-destination link. This model is motivated by a downlink scenario, where the source (base station), communicates with two destinations. We present several transmission strategies for this class of relay channels. Our proposed relaying schemes can be divided into two main categories: instantaneous relaying and causal relaying. In the former, the relay functionality is restricted to a memoryless, symbol-by-symbol mapping (linear as well as non-linear). While in the latter, the relay has an infinite memory and utilizes past received blocks to cooperate in the present block. For causal relaying, we investigate decode-and-forward (DF), compress-and-forward (CF), and combined DF and CF. To utilize the knowledge of the interference at the source, superposition coding at the source and Costa encoding at the relay are employed. One interesting observation is that instantaneous relaying can achieve higher rates than those achieved with causal relaying.

We study the problem of optimal design of relay mappings for the Gaussian relay channel in order to maximize the reliable transmission rate. We consider both Gaussian and modulation constrained signaling at the source. To optimize the relay mapping, we use an iterative integral equation as a necessary condition for optimality. The optimized relay mappings demonstrate significant rate improvement over conventional linear relaying (amplify-and-forward). The optimized mappings allow an efficient utilization of the side information received via the source-destination link at the destination. Hence, the proposed mappings can be considered as an analog, memoryless approach to implementing compress-and-forward relaying with Wyner-Ziv compression in the relay.

We consider a Gaussian relay channel, with the source and relay operating in different frequency bands. Hence, the received signals at the destination are orthogonal. We also assume that the source reuses the frequency band in which the relay is operating, to communicate with another destination. This results in a scenario that can be modeled in such a way that the relay-destination link suffers from an additive interference which is non-causally known at the source. We present different achievable rates for this model, focusing on instantaneous relaying, i.e., the relay output depends solely on the current received signal at the relay. The main conclusion of our work is that to achieve high rates, one should resort to joint design of precoding with non-linear relaying.

We propose a novel half-duplex decode-and-forward relaying scheme based on partial repetition coding at the relay. In the proposed scheme, if the relay decodes the received message successfully, it re-encodes the message using the same channel code as the one used at the source, but retransmits only a fraction of the codeword. We analyze the proposed scheme and optimize the cooperation level (i.e., the fraction of the message that the relay should transmit). We compare our scheme with conventional repetition in which the relay retransmits the entire decoded message, with parallel coding, and additionally with dynamic decode-and-forward (DDF). We provide a finite-SNR analysis for all the collaborative schemes. The analysis reveals that the proposed partial repetition method can provide a gain of several dB over conventional repetition. It also shows that in general, power allocation is less important provided that one optimally allocates bandwidth. Surprisingly, the proposed scheme is able to achieve the same performance as that of parallel coding for some relay network configurations, but at a much lower complexity.

We propose a spectrally efficient transmission scheme for the half-duplex relay channel. In the proposed scheme, the relay combines N detected r-dimensional symbols and generates M new r-dimensional symbols, where M < N, using a linear transformation. The proposed linear transformation preserves the signal energy, and it facilitates decoupled symbol detection at the receiver. We also present an optimized design for the case of complex scalar modulation (r = 2) with N = 2 and M = 1. This design increases the spectral efficiency by 33 % compared to conventional decode- or amplify-and-forward relaying.

We develop a general framework for design of receivers for the wireless relay channel. We derive the optimum detectors for various degrees of channel state information (CSI) at the destination. We consider both the case when the destination has access to full knowledge of the CSI and the case when it only knows the statistics of the channel. High-SNR and low-SNR approximations of the detectors are presented as well.

The paper proposed an enhancement to cooperative transmit diversity based on uncoded detect-and-forward, by using so-called constellation rearrangement (CR) at the relay. With CR, the relay uses a bit-symbol mapping that is different from the one used by the source. The authors find the optimal bit-symbol mappings for both the source and the relay and the associated optimal detectors, and show that the improvement over conventional relaying with Gray mapping at the source and the relay can amount to a power gain of several dB. This performance improvement comes at no additional power or bandwidth expense, and at virtually no increase in complexity.