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This paper is concerned with the energy efficiency maximization problem in multiple-input multiple-output interference channels. In the first part of this paper, we design the transmit beamforming matrices based on three approaches. In the first approach, each user tries to maximize their own energy efficiency, resulting in what we call the selfish method. The maximization problem corresponding to the selfish method can be implemented in a distributed manner with a semi-closed-form solution. The second approach aims to maximize the weighted sum-energy efficiency; we refer to it as the unselfish method. The proposed unselfish method has the following advantages. 1) It is easily implementable as the problem can be divided into several sub-problems and solved in a distributed manner. 2) It results in a quadratically constrained quadratic program with a semi-closed-form solution. Also, we consider fairness with the minimum-energy efficiency maximization problem, an approach that results in what we call the worst-case method. In the second part, general energy efficiency maximization in the presence of norm-bounded channel uncertainty is investigated which leads to a semi-definite program; the resulting method is called the robust method. Finally, the effect of the system parameters is evaluated through simulations. [ABSTRACT FROM AUTHOR]

In this paper, we propose a symbol encryption method based on the complex-valued symbol multiplication and design the encryption symbol placement for offset quadrature amplitude modulation based filter bank multicarrier (OQAM/FBMC) systems. Specifically, we firstly analyze the encryption and decryption effects of complex-valued symbol multiplication on the original OQAM symbols. Then, by utilizing the intrinsic interference characteristics of prototype filters, a symbol encryption method and the placement design are proposed to simultaneously achieve the encryption of all OQAM symbols and low complexity decryption. Finally, the symbol error rate (SER), average signal transmit power, computational overhead and power spectral density (PSD) are analyzed. Simulation results are consistent with the theoretical analysis and demonstrate that the proposed method outperforms the traditional method based on imaginary-valued encryption symbol insertion in terms of the SERs of both legitimate and illegitimate receivers. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) are envisioned to be a disruptive wireless communication technique that is capable of reconfiguring the wireless propagation environment. In this paper, we study a free-space RIS-assisted multiple-input single-output (MISO) communication system in far-field operation. To maximize the received power from the physical and electromagnetic nature point of view, a comprehensive optimization, including beamforming of the transmitter, phase shifts of the RIS, orientation and position of the RIS is formulated and addressed. After exploiting the property of line-of-sight (LoS) links, we derive closed-form solutions of beamforming and phase shifts. For the non-trivial RIS position optimization problem in arbitrary three-dimensional space, a dimensional-reducing theory is proved. The simulation results show that the proposed closed-form beamforming and phase shifts approach the upper bound of the received power. The robustness of our proposed solutions in terms of the perturbation is also verified. Moreover, the RIS significantly enhances the performance of the mmWave/THz communication system. [ABSTRACT FROM AUTHOR]

In Internet of Things (IoT), the freshness of status updates is crucial for mission-critical applications. In this regard, it is suggested to quantify the freshness of updates by using Age of Information (AoI) from the receiver’s perspective. Specifically, the AoI measures the freshness over time. However, the freshness in the content is neglected. In this paper, we introduce an age-based utility, named as Age of Changed Information (AoCI), which captures both the passage of time and the change of information content. By modeling the underlying physical process as a discrete time Markov chain, we investigate the AoCI in a time-slotted status update system, where a sensor samples the physical process and transmits the update packets to the destination. With the aim of minimizing the weighted sum of the AoCI and the update cost, we formulate an infinite horizon average cost Markov Decision Process. We show that the optimal updating policy has a special structure with respect to the AoCI and identify the condition under which the special structure exists. By exploiting the special structure, we provide a low complexity relative policy iteration algorithm that finds the optimal updating policy. We further investigate the optimal policy for two special cases. In the first case where the state of the physical process transits with equiprobability, we show that optimal policy is of threshold type and derive the closed-form of the optimal threshold. We then study a more generalized periodic Markov model of the physical process in the second case. Lastly, simulation results are laid out to exhibit the performance of the optimal updating policy and its superiority over the zero-wait baseline policy. [ABSTRACT FROM AUTHOR]

Digital receivers based on 1-bit quantization and oversampling w.r.t. the transmit signal bandwidth promise lower energy consumption. However, since 1-bit quantization is a highly non-linear operation, standard off the shelf receiver algorithms cannot be applied. In this paper we consider an unknown phase rotation and timing offset and a fully digital receiver. To reduce the non-linear behavior introduced by 1-bit quantization, we assume that the receiver applies uniform phase and sample dithering, which can be implemented by sampling at an irrational normalized intermediate frequency and with an irrational oversampling factor, respectively. Based on the least squares objective function we derive a typical digital matched filter receiver with a data- and timing-aided phase estimator and square time recovery based timing estimation. Our main contribution is to show that both estimators are consistent under very general assumptions, e.g., arbitrary colored noise and stationary ergodic transmit symbols. Performance evaluations are done via simulations and are compared against a numerically computable upper bound of the Cramér–Rao lower bound. For low signal-to-noise ratio the estimators perform well but for high signal-to-noise ratio they run into an error floor. The performance loss of the phase estimator due to decision-directed operation or estimated timing information is marginal. [ABSTRACT FROM AUTHOR]

One of the main challenges in diffusion-based molecular communication is dealing with the non-linearity of reaction-diffusion chemical equations. While numerical methods can be used to solve these equations, a change in the input signals or the parameters of the medium requires one to redo the simulations. This makes it difficult to design modulation schemes and practically impossible to prove the optimality of a given transmission strategy. In this paper, we provide an analytical technique for modeling the non-linearity of chemical reaction equations based on the perturbation method. The perturbation method expresses the solution in terms of an infinite power series. An approximate solution can be found by keeping the leading terms of the power series. The approximate solution is shown to track the true solution if either the simulation time interval or the reaction rate is sufficiently small. Approximate solutions for long time intervals are also discussed. An illustrative example is given. For this example, it is shown that when the reaction rate (or the total time interval) is low, instead of using a continuous release waveform, it is optimal for the transmitters to release molecules at two time instances. [ABSTRACT FROM AUTHOR]

Online fountain codes (OFC) have attracted much attention for their good intermediate performance, which is important for receivers with low-complexity requirement. However, low-complexity receivers generally have limited buffer size to store coded symbols that have not been fully decoded yet, as well as limited power budget for feedback transmissions. In this paper, we propose improved transmission schemes for online fountain codes to reduce the buffer occupancy and feedback transmissions. Firstly, we analyze the relationship between buffer occupancy and overhead as well as the relationship between recovery rate and overhead for online fountain codes. Motivated by the analysis, we propose the weighted online fountain codes (WOFC) which can adapt to various buffer sizes by adjusting the weight to control the probability that a coded symbol can be fully processed immediately, and analyze its performance. Then we further propose weighted online fountain codes with low feedback (WOFC-LF), which utilize the proposed analysis to estimate the recovery rate, and reduce feedback transmissions. Simulation results verify the effectiveness of the analysis for both OFC and WOFC, and demonstrate the superior performance of WOFC-LF with limited buffer size and feedback transmissions. [ABSTRACT FROM AUTHOR]

TeraHertz (THz) wireless communication constitutes a promising technique of satisfying the ever-increasing appetite for high-rate services. However, the ultra-wide bandwidth of THz communications requires high-speed, high-resolution analog-to-digital converters, which are hard to implement due to their high complexity and power consumption. In this paper, a deep learning-assisted THz receiver is designed, which relies on single-bit quantization. Specifically, the imperfections of THz devices, including their in-phase/quadrature-phase imbalance, phase noise and nonlinearity are investigated. The deflection ratio of the maximum-likelihood detector used by our single-bit-quantization THz receiver is derived, which reveals the effect of phase offset on the demodulation performance, guiding the architecture design of our proposed receiver. To combat the performance loss caused by the above-mentioned distortions, a twin-phase training strategy and a neural network based demodulator are proposed, where the phase offset of the received signal is compensated before sampling. Our simulation results demonstrate that the proposed deep learning-assisted receiver is capable of achieving a satisfactory bit error rate performance, despite the grave distortions encountered. [ABSTRACT FROM AUTHOR]

This paper proposes an unmanned aerial vehicle (UAV)-aided full-duplex non-orthogonal multiple access (FD-NOMA) method to improve spectrum efficiency. Here, UAV is utilized to partially relay uplink data and achieve channel differentiation. Successive interference cancellation algorithm is used to eliminate the interference from different directions in FD-NOMA systems. Firstly, a joint optimization problem is formulated for the uplink and downlink resource allocation of transceivers and UAV relay. The receiver determination is performed using an access-priority method. Based on the results of the receiver determination, the initial power of ground users (GUs), UAV, and base station is calculated. According to the minimum sum of the uplink transmission power, the Hungarian algorithm is utilized to pair the users. Secondly, the subchannels are assigned to the paired GUs and the UAV by a message-passing algorithm. Finally, the transmission power of the GUs and the UAV is jointly fine-tuned using the proposed access control methods. Simulation results confirm that the proposed method achieves higher performance than state-of-the-art orthogonal frequency division multiple-access method in terms of spectrum efficiency, energy efficiency, and access ratio of the ground users. [ABSTRACT FROM AUTHOR]

Lossless data transfer over communication networks has traditionally been achieved by means of ARQ protocols. However, the last ten years have seen an increasing interest in using erasure-correcting codes as an alternative, with the goal of reducing latency, feedback overhead, etc. Since these two approaches possess advantages as well as drawbacks, several hybrid ARQ schemes have also been proposed as good compromise solutions, in order to attain the “best of both worlds”. Extending this principle, this paper develops new classes of hybrid ARQ protocols for erasure channels that allow for flexible trade-offs between two important cost metrics, viz., the computational complexity of coding, and the amount of feedback needed. Our hybrid schemes make use of Tornado codes – a class of low-complexity capacity-achieving erasure codes – whose coding structure is well-suited for feedback-based communications. These schemes demonstrate significant cost reductions versus coding-only and feedback-only approaches over a wide region of interest. Moreover, these schemes are easily tuned to achieve different operating points on a trade-off curve. Finally, the proposed schemes showcase novel means of interweaving coding and feedback. [ABSTRACT FROM AUTHOR]

We analyze the symbol error probability (SEP) of $M$ -ary pulse amplitude modulation ($M$ -PAM) receivers equipped with optimal low-resolution quantizers. We first show that the optimum detector can be reduced to a simple decision rule. Using this simplification, an exact SEP expression for quantized $M$ -PAM receivers is obtained when Nakagami- $m$ fading channel is considered. The derived expression enables the optimization of the quantizer and/or constellation under the minimum SEP criterion. Our analysis of optimal quantization for equidistant $M$ -PAM receiver reveals the existence of error floor which decays at a double exponential rate with increasing quantization bits, $b$. Moreover, by also allowing the transmitter to optimize the constellation based on the statistics of the fading channel, we prove that the error floor can be eliminated but at a lower decay exponent than the unquantized case. Characterization of this decay exponent is provided in this paper. We also expose the outage performance limitations of SEP-optimal uniform quantizers. To be more precise, its decay exponent does not improve with $b$. Lastly, we demonstrate that the decay exponent of a quantized receiver can be complemented by receive antenna diversity techniques. [ABSTRACT FROM AUTHOR]

Hardware impairment is inevitable in many wireless systems. It is particularly severe in low-cost applications due to the imperfect components used. In this paper, the channel estimation and non-coherent detection problems of hardware impaired signals are studied for a single-carrier, single-antenna and single-hop system. Specifically, three different cases are investigated: signals with additive distortion only, signals with in-phase and quadrature imbalance only, and signals with both impairments. The maximum likelihood and Gaussian approximation methods are used to derive the new non-coherent detectors for amplitude modulated signals, while the maximum likelihood and moment-based methods are employed to design the new channel estimators for all signals. Numerical results show that the new non-coherent detectors outperform the existing non-coherent detectors in the presence of hardware impairment. The performance gain can be as high as 8 dB. They also show that the new channel estimators have much higher accuracy than the existing estimator. In some conditions, the accuracy of the new estimator is about 100 times that of the existing estimator. [ABSTRACT FROM AUTHOR]

This paper investigates the relay-assisted wireless information and power transfer enabled hybrid visible light communication (VLC)-radio frequency (RF) network, where a light emitting diode (LED) access point (AP) serves multiple information users (IUs) and multiple energy harvesting users (EHUs). IUs are allowed to receive information from the LED AP through time-division-multiple-access (TDMA) manner by either the single-hop VLC-ONLY mode or the relay-assisted dual-hop VLC-RF mode, while EHUs harvest energy via the VLC links. An optimization problem is formulated to maximize the achievable information rate of IUs by jointly optimizing the access mode selection, the direct current (DC) offset at the LED AP, the peak amplitude of the alternating current (AC) component at the LED AP, the electrical power allocated to the LED AP and the power allocation at relay, subject to the energy harvesting (EH) requirement constraints of EHUs. To tackle the non-convex problem with binary variables, we first decompose it into two subproblems in terms of the two access modes. Then, the subproblems are equivalently transformed and solved by the proposed successive convex approximation (SCA)-based algorithms. Simulation results show that significant performance gain can be achieved by optimizing the DC offset. It is also observed that the area where the VLC-ONLY mode is superior to the VLC-RF mode is enlarged with the decrease of the minimal EH requirement. Besides, the achievable information rate of IUs by the VLC-RF mode first increases and then decreases with the increment of the distance between the relay and the LED AP. [ABSTRACT FROM AUTHOR]

In this paper, we propose primitive rateless (PR) codes. A PR code is characterized by the message length and a primitive polynomial over $\mathbf {GF}(2)$ , which can generate a potentially limitless number of coded symbols. We show that codewords of a PR code truncated at any arbitrary length can be represented as subsequences of a maximum-length sequence ($m$ -sequence). We characterize the Hamming weight distribution of PR codes and their duals and show that for a properly chosen primitive polynomial, the Hamming weight distribution of the PR code can be well approximated by the truncated binomial distribution. We further find a lower bound on the minimum Hamming weight of PR codes and show that there always exists a PR code that can meet this bound for any desired codeword length. We provide a list of primitive polynomials for message lengths up to 40 and show that the respective PR codes closely meet the Gilbert-Varshamov bound at various rates. Simulation results show that PR codes can achieve similar block error rates as their BCH counterparts at various signal-to-noise ratios (SNRs) and code rates. PR codes are rate-compatible and can generate as many coded symbols as required; thus, demonstrating a truly rateless performance. [ABSTRACT FROM AUTHOR]

Symbiotic radio (SR) is a promising technology for energy- and spectrum-efficient wireless communication, which exploits passive communication for Internet-of-Things (IoT) transmission and achieves a mutualistic spectrum sharing between the passive and active transmissions. In this paper, we study an reconfigurable intelligent surface (RIS) empowered symbiotic radio over a broadcasting system, i.e., a base station (BS) broadcasts signals to multiple primary receivers (PRs) under the assistance of an RIS, while the RIS also transmits information to an IoT receiver (IR) by riding over the broadcasting signals. We formulate a problem to minimize the BS’s transmit power by jointly optimizing the BS’s active precoding and the RIS’s passive beamforming, under the signal-to-noise-ratio constraints of the primary and IoT transmissions. However, the problem is challenging to be solved optimally, since the variables are coupled and the constraints are non-convex. An iterative algorithm based on block coordinated descent (BCD) and semidefinite relaxation (SDR) techniques is first proposed, and its convergence together with complexity are analyzed. Then, to tackle the problem of high computational complexity caused by SDR technique, we further propose an alternative algorithm based on generalized power method (GPM) technique. Simulation results validate that the proposed system outperforms the traditional broadcasting system without RIS. The GPM-based algorithm achieves nearly the same transmit power performance as SDR-based algorithm, with a significantly reduced computational complexity. [ABSTRACT FROM AUTHOR]

This paper considers the application of widely linear (WL) receivers in an uplink multi-user system using real-valued modulation schemes, where the cellular base station (BS) with multiple antennas provides connectivity for randomly deployed single-antenna users. The targeted use case is massive machine type communication (mMTC) with grant-free access in the uplink, where the network is required to host a large number of low data rate devices transmitting in an uncoordinated fashion. Four types of WL receivers are investigated, namely the WL zero-forcing (ZF) and the WL minimum mean-squared error (MMSE) receivers, along with their enhanced versions employing successive interference cancellation (SIC) with channel-dependent ordering, i.e., the WL-ZF-SIC and WL-MMSE-SIC receivers. The outage performances of these receivers are analytically characterized in the high signal-to-noise ratio (SNR) regime and compared to those of conventional linear (CL) receivers using complex-valued modulation schemes. For the non-SIC receivers, we show that, when compared to the CL counterparts, the WL receivers yield a higher diversity gain when decoding the same number of users and have the same diversity gain but a decreased coding gain when the number of users is nearly doubled. The outage performance analysis of WL-SIC receivers is facilitated by the marginal distribution of ordered eigenvalues of a real-valued Wishart matrix. It is shown that the SIC operation with channel-dependent ordering brings no additional diversity gain to the WL receivers but instead increases the coding gain. Moreover, the coding gain of WL-SIC receivers grows as the number of users increases and even exceeds that of CL-SIC receivers under suitable conditions. For the mMTC scenario with grant-free transmission, it is demonstrated that the WL receivers outperform their CL counterparts in terms of offering a lower outage (and packet drop) probability and a higher system throughput for a given packet drop probability. [ABSTRACT FROM AUTHOR]

In this paper, we propose a receiver structure for single-carrier uplink transmission with frequency domain equalization (FDE) that is exposed to power amplifier (PA) nonlinearities. A two-stage approach is adopted, in which linear communication channel is equalized at the first stage, and it is followed by post-distortion, where nonlinear distortion is reduced. In the literature, nonlinear processing techniques are proposed, which perform memoryless compensation of nonlinear distortion together with FDE. However, in this study, we show that even if memoryless nonlinearity exists, the received signal is impaired by nonlinear inter-symbol-interference. Therefore, we propose a class of symbol rate post-distortion techniques, which use neighboring received symbols to suppress the nonlinear interference. Three different post-distortion methods, Gaussian process regression (GPR), neural network (NN) and Volterra series (VS) based post-distorters, are considered. Also, a combiner, which intelligently combines the outputs of fractional delayed bank of FDE’s after post-distortion, is proposed to overcome performance degradation of FDE for frequency selective channels under nonlinear distortion. Performances of the proposed techniques are compared with state-of-the-art approaches in terms of bit error rate (BER) and achievable information rate (AIR) metrics. Simulation results demonstrate that post-distortion methods together with bank of FDE outperform state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

The problem of coding for informed receivers (IR) is considered, where a transmitter multicasts a bunch of messages to its associated receivers, each of which already has a subset of messages as side information. Which receiver has what side information is unknown to the transmitter. A family of polar codes for IR was proposed for binary-input channels in (Huang and Shieh, 2018), which was shown to provide excellent side information gain regardless of side information configuration and content. A trial extension of this scheme to high-order modulations, however, was unsatisfactory. In this paper, two families of systematic polar coded modulations for IR are proposed. In the first family, by building a connection between the message bits and modulated symbols under systematic polar codes, we leverage the bit assignments and labeling techniques such that receiver side information can be directly translated to a minimum distance gain. In the second family, a permutation operation is added before modulation such that the message bits can be properly reordered to further advance and balance the gains among different side information configurations. Simulations show that the proposed schemes provide large and balanced side information gains and significantly outperform the system directly adapted from (Huang and Shieh, 2018) onto high-order modulations. [ABSTRACT FROM AUTHOR]

A deep learning assisted sum-product detection algorithm (DL-SPDA) for faster-than-Nyquist (FTN) signaling is proposed in this paper. The proposed detection algorithm works on a modified factor graph which concatenates a neural network function node to the variable nodes of the conventional FTN factor graph to approach the maximum a posterior probabilities (MAP) error performance. In specific, the neural network performs as a function node in the modified factor graph to deal with the residual intersymbol interference (ISI) that is not considered by the conventional detector with a limited complexity. We modify the updating rule in the conventional sum-product algorithm so that the neural network assisted detector can be complemented to a turbo equalization receiver. Furthermore, we propose a compatible training technique to improve the detection performance of the proposed DL-SPDA with turbo equalization. In particular, the neural network is optimized in terms of the mutual information between the transmitted sequence and the extrinsic information. We also investigate the maximum-likelihood bit error rate (BER) performance of a finite length coded FTN system. Simulation results show that the error performance of the proposed algorithm approaches the MAP performance, which is consistent with the analytical BER. [ABSTRACT FROM AUTHOR]

It has been a challenging task to derive the complementary cumulative distribution function (CCDF) of aggregate interference as closed-form in Poisson point process (PPP). In this paper, we consider wireless communication networks where transmitters are all distributed according to homogeneous PPP and study the CCDF of the interference. Mainly, we derive generalized bounds on the CCDF of aggregate interference from whole homogeneous PPP based on discretization of interference, which considerably enhance tightness compared to the previous bounds. These bounds can be used to the analysis requiring the distribution for aggregate interference, such as deployment and activation of BSs, massive MIMO, and millimeter wave communication networks. As examples of utilizing the derived bounds, we derive tractable coverage probabilities of uplink non-orthogonal multiple access (NOMA) users and downlink users in cellular networks under line-of-sight(LoS)/non-line-of-signt (NLOS) channels, respectively. In NOMA, we derive the closed-form bounds on coverage probability when successive interference cancellation is adopted for NOMA signal demodulation. Using the proposed bounds, we also obtain the bounds on coverage probability of a cellular system with LoS/NLOS channels. The tightness of bounds in this work is shown via numerical comparison. Moreover, we mathematically prove the convergence of bounds to exact CCDF. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the benefit of using intelligent reflecting surface (IRS) in multi-user multiple-input single-output (MU-MISO) systems, in the presence of eavesdroppers. We maximize the weighted sum secrecy rate by jointly designing the secure beamforming (BF), the artificial noise (AN), as well as the phase shift of the IRS. An alternating optimization (AO) method is proposed to deal with the formulated non convex problem. In particular, the secure beamforming and AN jamming matrix are optimally designed via the successive convex approximation (SCA) approach for given phase shift, which can be derived by considering the alternating direction method of multiplier (ADMM) and element-wise block coordinate decent (EBCD) methods. Finally, simulation results are presented to show the benefit of the IRS in terms of improving the secrecy performance, when compared to other methods. [ABSTRACT FROM AUTHOR]

An information source generates independent and identically distributed status update messages from an observed random phenomenon which takes $n$ distinct values based on a given probability mass function (PMF). These update packets are encoded at the transmitter node to be sent to a receiver node which wants to track the observed random variable with as little age as possible. The transmitter node implements a selective $k$ encoding policy such that rather than encoding all possible $n$ realizations, the transmitter node encodes the most probable $k$ realizations. We consider three different policies regarding the remaining $n-k$ less probable realizations: highest $k$ selective encoding which disregards whenever a realization from the remaining $n-k$ values occurs; randomized selective encoding which encodes and sends the remaining $n-k$ realizations with a certain probability to further inform the receiver node at the expense of longer codewords for the selected $k$ realizations; and highest $k$ selective encoding with an empty symbol which sends a designated empty symbol when one of the remaining $n-k$ realizations occurs. For all of these three encoding schemes, we find the average age and determine the age-optimal real codeword lengths, including the codeword length for the empty symbol in the case of the latter scheme, such that the average age at the receiver node is minimized. Through numerical evaluations for arbitrary PMFs, we show that these selective encoding policies result in a lower average age than encoding every realization, and find the corresponding age-optimal $k$ values. Since we focus on real-valued codeword lengths in this paper, the resulting age value obtained in each case studied here serves as a lower bound to what can be attained by integer-valued codeword lengths in that case. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a physics-consistent analytical characterization of the free-space path-loss of a wireless link in the presence of a reconfigurable intelligent surface. The proposed approach is based on the vector generalization of Green’s theorem. The obtained path-loss model can be applied to two-dimensional homogenized metasurfaces, which are made of sub-wavelength scattering elements and that operate either in reflection or transmission mode. The path-loss is formulated in terms of a computable integral that depends on the transmission distances, the polarization of the radio waves, the size of the surface, and the desired surface transformations. Closed-form expressions are obtained in two asymptotic regimes that are representative of far-field and near-field deployments. Based on the proposed approach, the impact of several design parameters and operating regimes is unveiled. [ABSTRACT FROM AUTHOR]

Slotted Aloha provides a simple way for accommodating the massive access of Machine-to-Machine (M2M) communications. Yet, the delay performance of slotted Aloha has long been observed to significantly deteriorate as the network size grows. It is therefore important to study how to optimize the delay performance of slotted Aloha in a large-scale network. This paper focuses on the optimization of access delay of a buffered slotted Aloha network, where $n$ nodes transmit to a common receiver in fading channels. Specifically, by deriving the closed-form expressions of the network steady-state points in both unsaturated and saturated conditions, the first and second moments of access delay of each packet are obtained as explicit functions of system parameters, and minimized by optimizing the transmission probability of each node. The analysis shows that to achieve the minimum mean access delay, the transmission probability of each node should be reduced as the network size increases, leading to a diminishing node data rate unless the information encoding rate is jointly optimized. The minimum mean access delay for a given data rate requirement is further characterized, and effects of key parameters such as the minimum required data rate for each node, the mean received signal-to-noise ratio of each packet and the number of nodes on the rate-constrained minimum mean access delay are discussed. The practical insights of the analysis are also demonstrated by taking the example of an LTE-M system with smart grid applications. [ABSTRACT FROM AUTHOR]

This paper proposes unprecedented Expectation Propagation (EP)-based receivers for Circular Faster-Than-Nyquist (CFTN) signaling. This concept yields a Minimum Mean-Square-Error equalizer for InterSymbol Interference (ISI) processing combined with a block which we call Constellation Matcher in charge of the symbol estimates realignment with the constellation. From this framework, we explore different scheduling strategies leading to iterative EP-based receivers with our without decision feedback. Then, by extending the family of the EP process to a subset of non-circular Gaussian distributions results in a Widely Linear (WL) equalization. This new WL-EP receiver best fits the CFTN model, allowing enhanced performance at the cost of a slightly increased complexity. Also, we propose to restrict the Gaussian family to circular Gaussian distributions with identity covariance matrices up to a scaling factor. Combined with CFTN, this particular family allows a low-complexity Frequency-Domain processing of the equalization without requiring any cyclic prefix. The proposed EP-based receivers for CFTN are then evaluated for different spectral efficiencies and computational complexities. Our simulations show that they completely handle the ISI up to 5 bits/s/Hz and double the spectral efficiency compared to Nyquist signaling with almost no performance loss. [ABSTRACT FROM AUTHOR]

This paper proposes a novel convolutional neural network (CNN) based joint classification method to characterize the signal-to-noise power ratio (SNR) and Doppler shift using spectrogram images, in order to enable efficient adaptive modulation and coding (AMC) designs. It is necessary to maintain high communication performances even in stringent environments where transceivers move at high speed due to the diversification of wireless applications. To optimize the transmission rate in such dynamic environments, AMC scheme is known to be effective. AMC is generally designed based on feedback information (FBI) such as the SNR and Doppler shift acquired on the receiving side. Here, the challenge is an increase in calculation burden, processing delay and estimation accuracy of the FBI. We focused on the spectrogram which is composed of power values in the time and frequency domains. Its two-dimensional fluctuation represents the Doppler shift as well as noise values. In the proposed method, such key information for AMC can be simultaneously extracted from a single spectrogram via a trained CNN. Therefore it is expected to contribute to reducing the computational burden and speeding up the signal processing. Simulation results are presented to demonstrate that the proposed method achieves better performance than traditional methods. [ABSTRACT FROM AUTHOR]

In this paper, we consider non-coherent detection schemes for molecular communication systems in the presence of inter-symbol-interference. In particular, we study non-coherent detectors based on memory-bits-based thresholds in order to achieve low bit-error-ratio (BER) transmission. The main challenge of realizing detectors based on memory-bits-based thresholds is to obtain the channel state information based only on the received signals. We tackle this issue by reformulating the thresholds through intermediate variables, which can be obtained by clustering multi-dimensional data from the received signals, and by using the K-means clustering algorithm. In addition to estimating the thresholds, we show that the transmitted bits can be retrieved from the clustered data. To reduce clustering errors, we propose iterative clustering methods from one-dimensional to multi-dimensional data, which are shown to reduce the BER. Simulation results are presented to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Hardware distortions (HWDs) render drastic effects on the performance of communication systems. They are recently proven to bear asymmetric signatures; and hence can be efficiently mitigated using improper Gaussian signaling (IGS), thanks to its additional design degrees of freedom. Discrete asymmetric signaling (AS) can practically realize the IGS by shaping the signals’ geometry or probability. In this paper, we adopt the probabilistic shaping (PS) instead of uniform symbols to mitigate the impact of HWDs and derive the optimal maximum a posterior detector. Then, we design the symbols’ probabilities to minimize the error rate performance while accommodating the improper nature of HWD. Although the design problem is a non-convex optimization problem, we simplified it using successive convex programming and propose an iterative algorithm. We further present a hybrid shaping (HS) design to gain the combined benefits of both PS and geometric shaping (GS). Finally, extensive numerical results and Monte Carlo (MC) simulations highlight the superiority of the proposed PS over conventional uniform constellation and GS. Both PS and HS achieve substantial improvements over the traditional uniform constellation and GS with up to one order magnitude in error probability and throughput. [ABSTRACT FROM AUTHOR]

In this paper, an intelligent reflecting surface (IRS) assisted spectrum sharing underlay cognitive radio (CR) wiretap channel (WTC) is studied, and we aim at enhancing the secrecy rate of secondary user in this channel subject to total power constraint at secondary transmitter (ST), interference power constraint (IPC) at primary receiver (PR) as well as unit modulus constraint at IRS. Due to extra IPC and eavesdropper (Eve) are considered, all the existing solutions for enhancing secrecy rate of IRS-assisted non-CR WTC as well as enhancing transmission rate in IRS-assisted CR channel without eavesdropper fail in this work. Therefore, we propose new numerical solutions to optimize the secrecy rate of this channel under full primary, secondary users’ channel state information (CSI) and three different cases of Eve’s CSI: full CSI, imperfect CSI with bounded estimation error, and no CSI. To solve the difficult non-convex optimization problem, an efficient alternating optimization (AO) algorithm is proposed to jointly optimize the beamformer at ST and phase shift coefficients at IRS. In particular, when optimizing the phase shift coefficients during each iteration of AO, a Dinkelbach based solution in combination with successive approximation and penalty based solution is proposed under full CSI and a penalty convex-concave procedure solution is proposed under imperfect Eve’s CSI. For no Eve’s CSI case, artificial noise (AN) aided approach is adopted to help enhancing the secrecy rate. Simulation results show that our proposed solutions for the IRS-assisted design greatly enhance the secrecy performance compared with the existing numerical solutions with and without IRS under full and imperfect Eve’s CSI. And positive secrecy rate can be achieved by our proposed AN aided approach given most channel realizations under no Eve’s CSI case so that secure communication also can be guaranteed. All of the proposed AO algorithms are guaranteed to monotonic convergence. [ABSTRACT FROM AUTHOR]

In this paper, we investigate multi user chirp spread spectrum with noncoherent detection as a continuation of our work on coherent detection. We derive the analytical bit error ratio (BER) expression for binary chirp spread spectrum (BCSS) in the presence of multiple access interference (MAI) caused by correlation with other user signals because of either asynchronism or Doppler shifts, or both, and validate with simulations. To achieve this we analyze the signal cross correlations, and compare traditional linear chirps with our recently-proposed nonlinear chirps introduced and with other nonlinear chirps from the literature. In doing so we illustrate the superior performance of our new nonlinear chirp designs in these practical conditions, for the noncoherent counterpart. [ABSTRACT FROM AUTHOR]

In this paper, we design a NOMA-based spectrum leasing scheme by considering the following three assumptions for the successive interference cancellation (SIC): (i) the primary network performs the SIC (PSIC), (ii) the secondary network performs the SIC (SSIC), (iii) either the primary or secondary network adaptively performs the SIC depending on the channel conditions (ASIC). We first analyze the achievable rate regions of these schemes. Then, we optimize the power allocation to different layers of the superimposed signal by maximizing the achievable rate of the secondary network under a QoS constraint for the primary network. Finally, we analyze these schemes in terms of the outage probability. The analysis shows that: (i) In terms of the primary network, the PSIC and ASIC schemes perform the same and these schemes outperform the SSIC scheme. (ii) In terms of the secondary network, the ASIC scheme outperforms the other two schemes. (iii) In terms of the primary network, the NOMA-based and OMA-based schemes perform the same, provided that the SIC is performed either adaptively or in a fixed manner at the primary network. (iv) In terms of the secondary network, the NOMA-based scheme outperforms the OMA-based scheme, provided that the SIC is performed adaptively. [ABSTRACT FROM AUTHOR]

Channel modeling is a challenging vital step towards the development of diffusion-based molecular communication networks (DMCNs). Analytical approaches for diffusion channel modeling are limited to simple and specific geometries and boundary conditions. Also, simulation- and experiment-driven methods are very time-consuming and computationally complex. In this paper, the channel model for DMCN employing the fundamental concentration Green’s function (CGF) is characterized. A general homogeneous boundary condition framework is considered that includes any linear reaction systems at the boundaries in the environment. To obtain the CGF for a general DMCN including multiple transmitters, receivers, and other objects with arbitrary geometries and boundary conditions, a semi-analytical method (SAM) is proposed. The CGF linear integral equation (CLIE) is analytically derived. By employing the numerical method of moments, the problem of CGF derivation from CLIE is transformed into an inverse matrix problem. Moreover, a sequential SAM is proposed that converts the inversion problem of a large matrix into multiple smaller matrices reducing the computational complexity. Particle-based simulator confirms the results obtained from the proposed SAM. The convergence and run time for the proposed method are examined. Further, the error probability of a simple diffusion-based molecular communication system is analyzed and examined using the proposed method. [ABSTRACT FROM AUTHOR]

Underwater environments create a challenging channel for communications. In this paper, we design a novel receiver system by exploring the machine learning technique–Deep Belief Network (DBN) – to combat the signal distortion caused by the Doppler effect and multi-path propagation. We evaluate the performance of the proposed receiver system in both simulation experiments and sea trials. Our proposed receiver system comprises of DBN based de-noising and classification of the received signal. First, the received signal is segmented into frames before the each of these frames is individually pre-processed using a novel pixelization algorithm. Then, using the DBN based de-noising algorithm, features are extracted from these frames and used to reconstruct the received signal. Finally, DBN based classification of the reconstructed signal occurs. Our proposed DBN based receiver system does show better performance in channels influenced by the Doppler effect and multi-path propagation with a performance improvement of 13.2dB at 10−3 Bit Error Rate (BER). [ABSTRACT FROM AUTHOR]

Age of information (AoI) is gaining attention as a valuable performance metric for many IoT systems, in which a large number of devices report time-stamped updates to a central gateway. This is the case, for instance, of remote sensing, monitoring, or tracking, with broad applications in the industrial, vehicular, and environmental domain. In these settings, AoI provides insights that are complementary to those offered by throughput or latency, capturing the ability of the system to maintain an up-to-date view of the status of each transmitting device. From this standpoint, while a good understanding of the metric has been reached for point-to-point links, relatively little attention has been devoted to the impact that link layer solutions employed in IoT systems may have on AoI. In particular, no result is available for modern random access protocols, which have recently emerged as promising solutions to support massive machine-type communications. To start addressing this gap we provide in this paper the first study of the AoI of a scheme in this family, namely irregular repetition slotted ALOHA (IRSA). By means of a Markovian analysis, we track the AoI evolution at the gateway, prove that the process is ergodic, and derive a compact closed form expression for its stationary distribution. Leaning on this, we compute exact formulations for the average AoI and the age violation probability. The study reveals non-trivial design trade-offs for IRSA and highlights the key role played by the protocol operating frame size. Moreover, a comparison with the performance of a simpler slotted ALOHA strategy highlights a remarkable potential for modern random access schemes in terms of information freshness. [ABSTRACT FROM AUTHOR]

We consider the problem of joint channel estimation and data decoding in uplink massive multiple input multiple output systems with low resolution analog-to-digital converters (ADCs) at the base station. The nonlinearities introduced by the ADCs make the problem challenging: in particular, the existing linear detectors perform poorly. Also, the channel coding used in commercial wireless systems necessitates soft symbol detection to obtain satisfactory performance. In this paper, we present a low-complexity variational Bayesian (VB) inference procedure to jointly solve the (possibly correlated) channel estimation and soft symbol decoding problem. We present the approach in progressively more complex scenarios, including the case where even the channel statistics are not available at the receiver. Finally, we combine our proposed VB procedure with a belief propagation (BP) based channel decoder, which further enhances the performance without any additional complexity. We numerically evaluate the bit error rate (BER) and the normalized mean squared error (NMSE) in the channel estimates obtained by our algorithm as a function of various system parameters, and benchmark the performance against genie-aided and state-of-the-art receivers. The results show that VB procedure is a promising technique for the design of low-complexity advanced receivers in low resolution ADC based systems. [ABSTRACT FROM AUTHOR]

This paper studies distributed power control for the uplink of multi-cell non-orthogonal multiple access (NOMA) systems. Within a cell, the transmissions of different users are modeled as a Gaussian multiple access channel, treating inter-cell interference as additive Gaussian noise. By analyzing the geometry of the feasible power region, using successive interference cancellation at each base station is proved to be optimal in minimizing the total transmission power of all users under rate constraints. The decoding order at each base station, however, remains to be determined. If the decoding order is decided without base station cooperation, the overall control algorithm is fully distributed but is suboptimal in general. To achieve optimality, a partially distributed algorithm is designed, which requires base stations to exchange control messages. Given any feasible instance, the algorithm is proved to converge to the optimal solution. The performance of the fully distributed and partially distributed power control algorithms is compared by computer simulations. The fully distributed algorithm is nearly optimal in terms of outage probability. When a high data rate is required, the partially distributed algorithm is able to reduce the total power consumption by about 20%. [ABSTRACT FROM AUTHOR]

Impulse noise presents a severe performance bottleneck in multicarrier systems. For digital subscriber lines (DSL), the use of a common-mode (CM) sensor is a viable technique to mitigate the impulse noise that couples into the useful differential-mode (DM) signal. In this paper, we use time and frequency domain approaches to develop algorithms using the joint processing of CM and DM signals and analyze the performance of dual-sensor based interference cancellation schemes for downstream DSL systems. First, we consider the frequency domain approach and analyze the performance of a per-tone impulse noise canceler without requiring an impulse detector. We derive closed-form expressions on the performance of canceler in various interference scenarios in terms of system parameters. Next, we develop a novel per-symbol time-domain impulse noise canceler by simultaneous estimation of the CM2DM transfer function and the CM impulse noise using a limited number of null carriers. The proposed algorithm eliminates the issues of convergence of the per-tone canceler and stationarity of the impulse noise over multiple symbols. Using derived analytical expressions, we show that the proposed canceler effectively mitigates the impulse noise on a per-symbol basis. We also demonstrate the performance of the considered canceler schemes using measurement and simulation results. [ABSTRACT FROM AUTHOR]

This paper introduces circular color shift keying (CSK) constellations in a visible light communications (VLC) system using a camera-based receiver with applications to vehicular communications, where vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications are required to improve the safety of vehicles in high traffic density. The circular CSK constellations are shown to outperform the geometric and IEEE 802.15.7 constellations in terms of bit-error probability. Afterward, the noise at the receiver is investigated and transferred from the spatial domain to an angular noise in the International Commission on Illumination (CIE) color domain, where it is shown to behave similarly to a Gaussian distribution. Based on this noise model, a closed-form expression of the bit-error rate (BER) of circular CSK constellations is derived and shown to be accurate for BER ranges corresponding to VLC applications of practical interest. Diversity techniques are also investigated, and interesting differences are noted during the analysis compared to traditional radio frequency (RF) communication scenarios. Finally, the design of a link adaptation approach maximizing the number of bits per transmitted symbol, while meeting a target BER, is proposed. Hence, this paper presents a detailed design and analysis of a novel VLC modulation technique and demonstrates its efficiency and superiority. [ABSTRACT FROM AUTHOR]

The universal filtered multicarrier (UFMC) modulation is among the most considered solutions for the realization of beyond orthogonal frequency division multiplexing (OFDM) air interfaces for future wireless networks. This paper focuses on the design and analysis of a UFMC transceiver equipped with multiple antennas and operating at millimeter-wave carrier frequencies. This paper provides the full mathematical model of an MIMO-UFMC transceiver, taking into account the presence of hybrid analog/digital beamformers at both ends of the communication links. Then, several detection structures are proposed, both for the case of single-packet isolated transmission and for the case of multiple-packet continuous transmission. In the latter situation, this paper also considers the case in which no guard time among adjacent packets is inserted, trading off an increased level of interference with higher values of spectral efficiency. At the analysis stage, several considered detection structures and transmission schemes are compared in terms of bit-error rate, root-mean-square error, and system throughput. The numerical results show that the proposed transceiver algorithms are effective and that the linear minimum mean-square error (MMSE) data detector is capable of well managing the increased interference brought by the removal of guard times among consecutive packets, thus yielding throughput gains of about 10%–13%. The effect of phase noise at the receiver is also numerically assessed, and it is shown that the recursive implementation of the linear MMSE exhibits some degree of robustness against this disturbance. [ABSTRACT FROM AUTHOR]

In this paper, we consider diffusion-based molecular communication with and without drift between two static nano-machines. We employ type-based information encoding, releasing a single molecule per information bit. At the receiver, we consider an asynchronous detection algorithm which exploits the arrival order of the molecules. In such systems, transposition errors fundamentally undermine reliability and capacity. Thus, in this paper, we study the impact of transpositions on the system performance. Toward this, we present an analytical expression for the exact bit error probability (BEP) caused by transpositions and derive computationally tractable approximations of the BEP for diffusion-based channels with and without drift. Based on these results, we analyze the BEP when background is not negligible and derive the optimal bit interval that minimizes the BEP. Simulation results confirm the theoretical results and show the error and goodput performance for different parameters such as block size or noise generation rate. [ABSTRACT FROM AUTHOR]

Analog least mean square (ALMS) loop is a promising method to cancel self-interference (SI) in in-band full-duplex (IBFD) systems. In this paper, the steady state analyses of the residual SI powers in both analog and digital domains are firstly derived. The eigenvalue decomposition is then utilized to investigate the frequency domain characteristics of the ALMS loop. Our frequency domain analyses prove that the ALMS loop has an effect of amplifying the frequency components of the residual SI at the edges of the signal spectrum in the analog domain. However, the matched filter in the receiver chain will reduce this effect, resulting in a significant improvement of the interference suppression ratio (ISR). It means that the SI will be significantly suppressed in the digital domain before information data detection. This paper also derives the lower bounds of ISRs given by the ALMS loop in both analog and digital domains. These lower bounds are joint effects of the loop gain, tap delay, number of taps, and transmitted signal properties. The discovered relationship among these parameters allows the flexibility in choosing appropriate parameters when designing the IBFD systems under given constraints. [ABSTRACT FROM AUTHOR]

This paper addresses point-to-point communication over block-fading channels with independent fading blocks. When both channel state information at the transmitter and receiver (CSIR) are available, most achievable schemes use separable coding, i.e., coding independently and in parallel over different fading states. Unfortunately, separable coding has drawbacks, including large memory requirements at both communication ends. In this paper, a lattice coding and decoding scheme is proposed that achieves the ergodic capacity without separable coding, with lattice codebooks and decoding decision regions that are universal across channel realizations. We first demonstrate this result for fading distributions with discrete, finite support whose sequences are robustly typical. Results are then extended to continuous fading distributions, as well as multiple-input multiple-output (MIMO) systems. In addition, a variant of the proposed scheme is presented for the MIMO ergodic fading channel with CSIR only, where we prove the existence of a universal codebook that achieves rates within a constant gap to capacity for finite-support fading distributions. The gap is small compared with other schemes in the literature. Extension to continuous-valued fading is also provided. [ABSTRACT FROM AUTHOR]

Faster-than-Nyquist (FTN) transmission employing antenna polarization multiplexing and higher order modulation (HoM) schemes can significantly increase the spectral efficiency (SE) of the existing wireless backhaul links. However, the benefits of each of these SE enhancement techniques come with a price. While FTN introduces inter-symbol interference, a dual-polarized (DP) transmission suffers from cross-polarization interference (XPI), and HoM makes a communication system vulnerable to phase-noise (PN) distortions. In this paper, we investigate, for the first time, a DP-FTN HoM transmission system. We propose a XPI cancellation and PN mitigation structure, coupled with adaptive decision-feedback equalization or linear precoding, to jointly mitigate interference and accomplish carrier-phase tracking. The DP systems combined with the FTN signaling presented in this paper offer more than 150% increase in SE compared with a single-polarized Nyquist transmission. The effectiveness of the proposed algorithms is demonstrated through computer simulations of a coded DP-FTN microwave communication system in the presence of PN. Numerical results suggest that with the proposed interference cancellation methods, a DP-FTN transmission can yield a 3–5.5-dB performance improvement over an equivalent DP-Nyquist system that employs a higher modulation order to achieve the same data rate. [ABSTRACT FROM AUTHOR]

This paper investigates the design and analysis of minimum mean square error (MMSE) turbo decision feedback equalization (DFE), with expectation propagation (EP), for single carrier modulations. Classical non iterative DFE structures have substantial advantages at high-data rates, even compared with turbo linear equalizers-interference cancellers (LE-IC), hence making turbo DFE-IC schemes an attractive solution. In this paper, we derive an iterative DFE-IC, capitalizing on the use of soft feedback based on expectation propagation, along with the use of prior information for improved filtering and interference cancellation. This turbo iterative DFE-IC significantly outperforms turbo LE-IC, especially at high-spectral efficiency and also exhibits performance improvements over existing DFE-IC variants. The proposed scheme can also be self-iterated, as done in the recent trend on EP-based equalizers, and it is shown to be an attractive alternative to linear self-iterated receivers. For time-varying (TV) filter equalizers, an efficient matrix inversion scheme is also proposed, considerably reducing the computational complexity relative to existing methods. Using finite-length and asymptotic analysis on a severely selective channel, the proposed DFE-IC is shown to achieve higher rates than known alternatives, with better waterfall thresholds and faster convergence, while keeping a similar computational complexity. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the impacts of transmitter and receiver windows on the performance of orthogonal time-frequency space (OTFS) modulation and propose window designs to improve the OTFS channel estimation and data detection performance. In particular, assuming ideal pulse shaping filters at the transceiver, we derive the impacts of windowing on the effective channel and its estimation performance in the delay-Doppler (DD) domain, the total average transmit power, and the effective noise covariance matrix. When the channel state information (CSI) is available at the transceiver, we analyze the minimum squared error (MSE) of data detection and propose an optimal transmitter window to minimize the detection MSE. The proposed optimal transmitter window can be interpreted as a mercury/water-filling power allocation scheme, where the mercury is firstly filled before pouring water to pre-equalize the time-frequency (TF) domain channels. When the CSI is not available at the transmitter but can be estimated at the receiver, we propose to apply a Dolph-Chebyshev (DC) window at either the transmitter or the receiver, which can effectively enhance the sparsity of the effective channel in the DD domain. Thanks to the enhanced DD domain channel sparsity, the channel spread due to the fractional Doppler is significantly reduced, which leads to a lower error floor in both channel estimation and data detection compared with that of rectangular window. Simulation results verify the accuracy of the obtained analytical results and confirm the superiority of the proposed window designs in improving the channel estimation and data detection performance over the conventional rectangular window design. [ABSTRACT FROM AUTHOR]

Because of the potential applications in quantum information processing tasks, discrimination of binary coherent states using generalized Kennedy receiver with maximum a posteriori probability (MAP) detection has attracted increasing attentions in recent years. In this paper, we analytically study the performance of the generalized Kennedy receiver having optimally displaced threshold detection (ODTD) in a realistic situation with noises and imperfect devices. We first prove that the MAP detection for a generalized Kennedy receiver is equivalent to a threshold detection in this realistic situation. Then we analyze the properties of the optimum threshold and the optimum displacement for ODTD, and propose a heuristic greedy search algorithm to design these parameters. We prove that the ODTD asymptotically approaches the Kennedy receiver with threshold detection when the signal power is large, and we also clarify the connection between the generalized Kennedy receiver with threshold detection and the one-port homodyne detection. Numerical results show that the proposed heuristic greedy search algorithm can obtain a lower and smoother error probability than the existing methods. [ABSTRACT FROM AUTHOR]

In a majority of research on covert communications, knowledge about channel state information (CSI) of main channel and/or warden channel is assumed to be known or partially known. However, a covert user may not afford to perform channel estimation in practice, and acquiring the warden’s CSI is even impossible. In this paper, we investigate covert communications over non-coherent Rayleigh fading channels, in both i.i.d. fast fading and slow fading cases. We observe that the purpose of covert communication in many scenarios is to hide the existence of the sender, not the receiver. Therefore, we allow the receiver to work in full-duplex mode such that it can emit artificial noise (AN) while receiving signals simultaneously. We analyse the achievable covert rates with fixed and varying AN power and show that in both fast and slow fading cases, it is possible to achieve a positive covert rate. For the slow fading case, we further extend the proposed strategy to a multi-user scenario, in which multiple other users share the same spectral resource and cause interference at the warden. Extensive simulations are performed to verify the correctness of our analysis, which provide new insights on the AN design problem in non-coherent channels. [ABSTRACT FROM AUTHOR]

In this paper, we propose a Sparse Code Spreading-aided Multi-Carrier Differential Chaos Shift Keying (SCS-MC-DCSK) transceiver to improve the efficiency and reliability performances for multiuser transmissions. With the aim to improve the spectrum efficiency and enhance the reliability, we construct a multi-dimension codebook based on a factor graph matrix to spread information bits in a non orthogonal way, thus the signals could overlap and multiple users are allowed to share all sub-carrier resources via the non orthogonal spreading. The information bits using the same codebook are regarded as a layer, while each user could choose to use one or multiple layers. Then the resultant symbols are spread by the reference chaotic sequence and its quadrature version generated by Hilbert transform in the time domain. At the receiver, reverse operations are conducted, and we propose the Minimum Distance (MD) detection method to retrieve the estimates. Furthermore, theoretical performances, including the Symbol Error Rate (SER), capacity, energy efficiency, spectrum efficiency and computational complexity, are analyzed and compared among the proposed design and benchmarks. Simulation results are then provided to validate the theoretical analysis. Moreover, the Bit Error Rate (BER) performances under different channel conditions demonstrate the superior reliability and efficiency to benchmarks. [ABSTRACT FROM AUTHOR]

This paper investigates a cache-aided cloud radio access network (C-RAN), comprising a central unit, $K$ base stations (BSs) each with $N_{T}$ antennas, and $M$ users each with $N_{R}$ antennas, where each BS and user have local caches to store some popular contents from the central unit. For this cache-aided network, we propose the linear network coded (NC) wireless caching that consists of linear wireless network coding assisted cache placement phase and signal-space alignment (SSA) enabled content delivery phase. In the cache placement phase, we design a joint NC caching function at the BSs to store linear combinations of messages from the central unit, as a form of linear wireless network coding. In the content delivery phase, we design the SSA pattern based on the NC caching to guide the precoding designs at BSs. Then, each user can reliably decode its requested messages by receiver shaping and reverse NC operation. The primary contribution of this work is to achieve the coding gain induced by the integration of linear wireless network coding and SSA, which has been not exploited in the field of wireless coded caching. In particular, to deal with high temporal variability of user requests, we show that the proposed cache placement is invariant to different user requests in the worst-case caching, without any shared caching messages at different BSs. Furthermore, we verify that the proposed scheme is also compatible with the insufficient caching scenario at the BSs. In addition, we analyze the achievable sum degrees of freedom (DoF) for the proposed caching network. Both analytical and numerical results verify that the proposed caching scheme achieves a higher sum DoF than the existing related works. [ABSTRACT FROM AUTHOR]

Within the framework of 5G, blockage effects occurring in the mmWave band are critical. Previous works describe the effects of blockages in isolated and multiple links for simple blocking objects, modeled with mathematical tools such as stochastic geometry and random shape theory. Our study uses these tools to characterize a scenario with $N$ links, including the possible correlation among them in terms of blocking for several models of blocking objects. We include numerical evaluations highlighting that assuming independence among the links’ blocking elements is a too-brief simplification and does not accurately describe the real scenario. This paper also applies the formulation developed for the case of $N$ links to optimize the relay positioning in mmWave cells for coverage enhancement, that is, to minimize the communication failure probability. We also show that both link budget and blockages affect the optimum positioning of the relays as they are both essential for successful transmission. [ABSTRACT FROM AUTHOR]