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In wireless networks, the link connectivity may be intermittent due to shadowing, burstiness of data arrival, or uncoordinated resource allocation. In this paper, we model the intermittence of links as Bernoulli distributed random channel states, termed intermittence channel states, and study the impact of the corresponding channel state information at the transmitter (CSIT) in a two-user Gaussian broadcast channel (BC). Moreover, due to the heterogeneous timeliness of intermittence channel states, the CSIT considered in this paper is hybrid. More specifically, the CSIT of each link can be perfectly (causally or non-causally) available, delayed, or not available. When the links are connected, we adopt a general setting that the received signal-to-noise ratios can be different. Our contribution is the characterization of the capacity regions of intermittent Gaussian BC to within bounded gaps for all combinations of hybrid CSIT, except for scenario DN (delayed CSIT of receiver 1, no CSIT of receiver 2). For scenario DN, we propose an opportunistic physical layer network coding scheme that achieves a strictly larger degree-of-freedom (DoF) region than the no-CSIT DoF region. As a corollary, single-user CSIT is able to increase the sum DoF for intermittent Gaussian BC (also the capacity region for the erasure BC, as a by-product). This result is in sharp contrast to the recent negative result by Davoodi and Jafar, where it is shown that for fast-fading multiple-input single-output BC with continuous channel states, single-user CSIT does not help at all in terms of sum DoF. [ABSTRACT FROM AUTHOR]

In the scalar dirty multiple-access channel, in addition to Gaussian noise, two additive interference signals are present, each known non-causally to a single transmitter. It was shown by Philosof et al. that for strong interferences, an independent identically distributed ensemble of codes does not achieve the capacity region. Rather, a structured-codes approach was presented that was shown to be optimal in the limit of high signal-to-noise ratios, where the sum capacity is dictated by the minimal (“bottleneck”) channel gain. In this paper, we consider the multiple-input multiple-output (MIMO) variant of this setting. In order to incorporate structured codes in this case, one can utilize matrix decompositions that transform the channel into effective parallel scalar dirty multiple-access channels. This approach, however, suffers from a “bottleneck” effect for each effective scalar channel and, therefore, the achievable rates strongly depend on the chosen decomposition. It is shown that a recently proposed decomposition, where the diagonals of the effective channel matrices are equal up to a scaling factor, is optimal at high signal-to-noise ratios, under an equal rank assumption. This approach is then extended to any number of transmitters. Finally, an application to physical-layer network coding for the MIMO two-way relay channel is presented. [ABSTRACT FROM AUTHOR]

In this paper, the role of feedback in two-way full-duplex Gaussian channel (TW-FD-GC) is revisited. First, we propose a practical coding scheme for the TW-FD-GC, which is based on the noisy type of the well-known Schalkwijk-Kailath (SK) feedback scheme. We show that though this scheme cannot achieve the capacity of the TW-FD-GC, the codeword length that achieves desired decoding error probability is extremely short. Then, we further prove that the proposed scheme is secure by itself, i.e., the achievable rate region of the proposed scheme is also an achievable secrecy rate region of the two-way full-duplex Gaussian wiretap channel (TW-FD-GWTC). In addition, for the TW-FD-GWTC, numerical result shows that the secrecy sum rate of our proposed scheme can be as large as those achieved by existing schemes in the literature for some cases. Next, we extend the proposed scheme to the TW-FD-GC with Gaussian state interference non-causally known by the corresponding transmitter. We show that the interference can be perfectly canceled by this extended scheme. Finally, we prove that this extended scheme is also secure by itself, and numerical result shows that this extended scheme may perform better than the existing ones in the literature. [ABSTRACT FROM AUTHOR]

The proliferation of IEEE 802.11 or WiFi networks, and the explosive growth in traffic demands call for solutions to maximize the capacity of WiFi networks. Hence, maximizing the spatial reuse of WiFi networks is critical as doing so allows multiple concurrent transmissions. In this respect, a critical network parameter, Clear Channel Assessment (CCA) threshold, plays a vital role as it dictates whether a node is allowed to transmit after sensing the channel. In this paper, we propose to use Deep Q-network (DQN) under two learning patterns to select the CCA threshold of devices. We further consider Transmit Power Control (TPC) in conjunction with CCA threshold selection to improve the capacity of a WiFi network. The simulation results show that our approach is capable of selecting the optimal CCA threshold for each device. As a result, the average throughput is 62.4% higher than that of a legacy Dynamic Sensitivity Control (DSC) algorithm. [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]

In this paper, we consider transmissions over block-fading channels and assume that adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) are implemented. Knowing that in high signal-to-noise ratio, the conventional combination of HARQ with AMC is counterproductive from the throughput point of view, we adopt the so-called layer-coded HARQ (L-HARQ). L-HARQ allows consecutive packets to share the channel and preserves a great degree of separation between AMC and HARQ; this makes the encoding and decoding very simple and allows us to use the available/optimized codes. Numerical examples shown in this paper indicate that L-HARQ can provide significant throughput gains compared to the conventional HARQ. The L-HARQ is also implemented using turbo codes, indicating that the throughput gains also materialize in practice. [ABSTRACT FROM AUTHOR]

This paper considers a Gaussian channel with one transmitter and two receivers. The goal is to maximize the communication rate at the intended/primary receiver subject to a disturbance constraint at the unintended/secondary receiver. The disturbance is measured in terms of the minimum mean square error (MMSE) of the interference that the transmission to the primary receiver inflicts on the secondary receiver. This paper presents a new upper bound for the problem of maximizing the mutual information subject to an MMSE constraint. The new bound holds for vector inputs of any length and recovers a previously known limiting (when the length of the vector input tends to infinity) expression from the work of Bustin et al. The key technical novelty is a new upper bound on the MMSE. This bound allows one to bound the MMSE for all signal-to-noise ratio (SNR) values below a certain SNR at which the MMSE is known (which corresponds to the disturbance constraint). The bound also complements the “single-crossing point property” of the MMSE that upper bounds the MMSE for all SNR values above a certain value at which the MMSE value is known. The MMSE upper bound provides a refined characterization of the phase-transition phenomenon, which manifests, in the limit as the length of the vector input goes to infinity, as a discontinuity of the MMSE for the problem at hand. For vector inputs of size n=1 , a matching lower bound, to within an additive gap of order O ( \log \log ({1}/{\sf MMSE}) ) (where {\sf MMSE}$ is the disturbance constraint), is shown by means of the mixed inputs technique recently introduced by Dytso et al. [ABSTRACT FROM PUBLISHER]

The distributed power control algorithms available in this paper assume perfect estimation of interference power at the receivers and often, the availability of perfect local channel state information (CSI). However, perfect estimation of interference power or acquisition of channel information is impractical. In this paper, we consider a generic class of distributed power control algorithms and analyze the resulting performance loss when faced with errors in CSI and/or interference level estimation. We approximate such power control algorithms with linearized state space dynamics wherein the errors in the estimation of received interference or the CSI, can be modeled as additive observation noise. Based on the proposed model, we derive lower bounds on the norm of the errors in the transmit power vector and receive signal-to-interference-plus-noise ratio (SINR) vector. Our analysis suggests that when the target SINR vector approaches the Pareto-optimal bound, the errors in the transmit vectors could grow without bound. As a consequence, to maintain a performance loss within an acceptable range, either much longer estimation times or lower target SINRs are required. Our numerical results confirm the validity of our analysis and the validity of the proposed bounds. [ABSTRACT FROM PUBLISHER]

This paper considers that a transmitter superposes secrecy transmissions to a closer receiver with a high security level in the active MIMO-OFDM channel it is using to send data to a farther receiver with a low security level, by using NOMA techniques. A joint optimization of power allocation and beamforming is important to maximize the secrecy rate to the closer receiver, while keeping the requested data rate of the farther receiver unaffected. The optimization problem is challenging because of coupled variables, and has yet to be addressed. We propose to decouple the problem between subcarrier power allocation and beamforming. Given beamforming, we prove the subcarrier power allocation for the two receivers can be equivalently transformed to two convex problems with waterfilling structures and closed-form solutions. Given power allocation, beamforming can be decoupled between subcarriers by distributing the rate requirement of the farther receiver across the subcarriers. The per-subcarrier beamforming is convexified by applying semidefinite relaxation and the Dinkelbach method. Simulations show the proposed approach can outperform its existing alternatives in terms of secrecy rate, and holistic designs of power allocation and beamforming are critical. [ABSTRACT FROM AUTHOR]

In this paper, precoder designs are proposed for the wireless X networks aided by a relay and with no or very limited channel state information at the transmitters (CSIT). First, we derive the general feasibility conditions for interference alignment (IA) for a relay-aided symmetric multi-input-multi-output X channel (also called the X relay channel or XRC) without any CSI at the source transmitters. Next, we propose an IA-based joint beamforming approach with very limited feedback to the transmitters (referred to as “IA-LFB” in this paper), which can attain the maximum degrees of freedom (DoF) of the network under arbitrarily low relay power. Finally, we propose an iterative minimum-sum mean-square-error (MMSE) precoder design for the single-input-single-output XRC for throughput improvement in the finite signal-to-noise ratio (SNR) region. The proposed MMSE precoder also shows better bit error rate results than the IA precoder over a wide SNR range. Since the MMSE precoder can achieve only locally optimal solutions, we propose to initialize the iterative MMSE algorithm with the IA-LFB precoder which, unlike random initializations, not only improves the throughput in the finite SNR regions but also preserves the network DoF even under limited relay power. [ABSTRACT FROM AUTHOR]

The degrees of freedom (DoFs) of the $K$ -user multiple-input multiple-output (MIMO) interference channel are studied when perfect, but delayed channel state information is available at the transmitter side (delayed CSIT). Recent works have proposed schemes improving the DoF knowledge of the interference channel, but at the cost of developing transmission involving many channel uses (long delay), thus increasing the complexity at both transmitter and receiver side. This paper proposes three linear precoding strategies, limited to at most three phases, based on the concept of interference alignment, and built upon three main ingredients: delayed CSIT precoding, user scheduling, and redundancy transmission. In this respect, the interference alignment is realized by exploiting delayed CSIT to align the interference at the non-intended receivers along the space-time domain. Moreover, a new framework is proposed where the number of transmitted symbols and duration of the phases is obtained as the solution of a maximization problem, and enabling the introduction of complexity constraints, which allows deriving the achievable DoF as a function of the transmission delay, i.e., the achievable DoF-delay trade-off. Finally, the latter part of this paper settles that the assumption of time-varying channels common along all the literature on delayed CSIT is indeed unnecessary. [ABSTRACT FROM PUBLISHER]

In this paper, we propose regularized block diagonalization (RBD) precoding using artificial noise (AN) for physical layer security in downlink multi-user MIMO wireless networks. We derive secrecy sum rate and asymptotic secrecy sum rate for the proposed scheme. The optimum power allocation for legitimate users and the AN signal are derived in closed form for optimal asymptotic secrecy sum rate. Our analysis shows that to achieve best performance, it is more efficient to degrade the performance of the eavesdropper than improving legitimate users’ rates. We also study the impact of error in channel estimation on the system and derive closed-form SINR and secrecy sum-rate expressions for this case. Simulations show that the secrecy sum rate of RBD precoding outperforms the secrecy sum rate of regularized channel inversion by 0.5 bits/s/Hz. We also show that in the presence of channel estimation error, our approximate closed forms for secrecy sum rate are very closed to the actual secrecy sum rate over a wide range of SNR and channel estimation error values. [ABSTRACT FROM AUTHOR]

This paper considers a wireless communication network consisting of multiple interfering multicast sessions. Different from a unicast system where each transmitter has only one receiver, in a multicast system, each transmitter has multiple receivers and broadcasts a common message to all of them. It is a well-known result for wireless unicast systems that the feasibility of a signal-to-interference-plus-noise power ratio (SINR) without power constraint is decided by the spectral radius of a nonnegative matrix. We generalize this result and obtain necessary and sufficient conditions for the feasibility of an SINR in a wireless multicast system with and without power constraint. The feasible SINR region and its geometric properties are studied. Besides, an iterative algorithm is proposed, which can efficiently check the feasibility condition and compute the boundary points of the feasible SINR region. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) based simultaneous positioning and orientating (SPAO), using received signal strength (RSS) measurements, is studied in this paper. RSS-based SPAO for VLCs of great challenge as it is essentially a non-convex optimization problem due to the nonlinear RSS model. To address this non-convexity challenge, a novel particle-assisted stochastic search (PASS) algorithm is proposed. The proposed PASS-based SPAO scheme does not require the knowledge of the height of receiver, the perfect alignment of transceiver orientations or inertial measurements. This is a huge technical improvement over the existing VLC localization solutions. The algorithmic convergence is established to justify the proposed PASS algorithm. In addition, a closed-form Cramer–Rao lower bound (CRLB) on localization error is derived and analyzed to gain insights into how the VLC-based SPAO performance is related to system configurations. It is shown that the receiver's position and orientation accuracy is linear with signal-to-noise ratio and direction information. In addition, the position accuracy decays with six powers of the transceiver distance, while the orientation accuracy decays with four powers of the transceiver distance. Finally, simulation results verify the performance gain of the proposed PASS algorithm for VLC-based SPAO. [ABSTRACT FROM AUTHOR]

Two of the main drawbacks of the current broadcasting services are, on the one hand, the lack of flexibility to adapt to the new generation systems requirements, and on the other hand, the incapability of taking a piece of the current mobile services market. In this paper, layered division multiplexing (LDM), which grew out of the concept of Cloud Txn, is presented as a very promising technique for answering those challenges and enhancing the capacity of broadcasting systems. The major contribution of this paper is to present the first comprehensive study of the LDM performance behavior. In particular, in this paper, the theoretical considerations of the LDM implementation are completed with the first computer based simulations and laboratory tests, covering a wide range of stationary channels and the mobile TU-6 channel. The results will support LDM as a strong candidate for multiplexing different services in the next generation broadcasting systems, increasing both flexibility and performance. [ABSTRACT FROM PUBLISHER]

This paper considers the corner points of the capacity region of a two-user Gaussian interference channel (GIC). In a two-user GIC, the rate pairs where one user transmits its data at the single-user capacity (without interference), and the other at the largest rate for which reliable communication is still possible are called corner points. This paper relies on existing outer bounds on the capacity region of a two-user GIC that are used to derive informative bounds on the corner points of the capacity region. The new bounds refer to a weak two-user GIC (i.e., when both crosslink gains in standard form are positive and below 1), and a refinement of these bounds is obtained for the case where the transmission rate of one user is within \varepsilon > 0 of the single-user capacity. The bounds on the corner points are asymptotically tight as the transmitted powers tend to infinity, and they are also useful for the case of moderate SNR and INR. Upper and lower bounds on the gap (denoted by \Delta ) between the sum-rate and the maximal achievable total rate at the two corner points are derived. This is followed by an asymptotic analysis analogous to the study of the generalized degrees of freedom [where the SNR and INR scalings are coupled such that (\log (\text INR)/\log (\text SNR)) = \alpha \geq 0 ], leading to an asymptotic characterization of this gap which is exact for the whole range of \alpha . The upper and lower bounds on $\Delta $ are asymptotically tight in the sense that they achieve the exact asymptotic characterization. Improved bounds on $\Delta $ are derived for finite SNR and INR, and their improved tightness is exemplified numerically. [ABSTRACT FROM PUBLISHER]

The degrees of freedom (DoF) of the 3-user multiple-input multiple-output (MIMO) interference channel (IC) with full channel state information and constant channel coefficients are investigated when $(p,p+1)$ antennas are deployed at the transmitters and receivers, respectively. The point of departure of this paper is the work of Wang et al., which conjectured but did not prove the DoF for the antenna settings with $p>1$. Here the achievability of the DoF outer bound is formally proved using linear methods, thereby avoiding the use of the rational dimensions framework. The proposed transmission scheme exploits asymmetric complex signaling together with symbol extensions in time and space interference alignment concepts. While the paper deals with the $p=2,3,\ldots,6$ cases, providing the specific transmit and receive filters, there are also provided the tools needed for proving the achievability of the optimal DoF for $p>6$, whose DoF characterization is conjectured. [ABSTRACT FROM PUBLISHER]

In this paper, optimal deterministic encoding of a scalar parameter is investigated in the presence of an eavesdropper. The aim is to minimize the expectation of the conditional Cramér–Rao bound at the intended receiver while keeping the mean-squared error (MSE) at the eavesdropper above a certain threshold. First, optimal encoding functions are derived in the absence of secrecy constraints for any given prior distribution on the parameter. Next, an optimization problem is formulated under a secrecy constraint and various solution approaches are proposed. Also, theoretical results on the form of the optimal encoding function are provided under the assumption that the eavesdropper employs a linear minimum mean-squared error (MMSE) estimator. Numerical examples are presented to illustrate the theoretical results and to investigate the performance of the proposed solution approaches. [ABSTRACT FROM AUTHOR]

This paper studies symbol error rate (SER) analysis of a user scheduling and space-time block coding (i.e., scheduled STBC) with power allocation using statistical channel state information (CSI) in cognitive radio multiple-input multiple-output (CR-MIMO) systems. The exact SER of the proposed scheme with the statistical CSI is derived for CR-MIMO systems including asymptotic analysis under nonfeedback delay. From analytical results, we observe that the proposed scheduled STBC scheme with the statistical CSI provides the transmit and receive spatial diversity, as well as the multiuser diversity, while the conventional transmit antenna selection (TAS)-based scheme with the statistical CSI only provides the receive spatial diversity. Furthermore, the exact SER of the scheduled STBC with the statistical CSI in CR-MIMO systems is derived under feedback delay between the transmitter and the receiver of the CR system. From the analysis, we find that though the multiuser diversity is diminished by feedback delay, the proposed scheme with feedback delay still provides the transmit and receive spatial diversity, which results in diversity order gain over the conventional TAS-based scheme with nonfeedback delay. Also, the signal-to-noise ratio gain is getting better as the power correlation coefficient and the number of user terminals increase under feedback delay. [ABSTRACT FROM AUTHOR]

This paper is concerned with the sum-rate maximization problem in multiple-input multiple-output interference channels. We design the transmit covariance matrix, associated with each transmitter to maximize the sum-rate of the network when the number of data symbols is unknown. The design problem is nonconvex and then hard to be solved. We devise a semidistributed design methodology according to majorization–minimization technique to deal with the optimization problem. This leads us to a convex quadratically constrained quadratic program at each iteration with a semiclosed form solution. The proposed method is computationally efficient and converges to stationary points of the problem. The fact that the method is based on a distributed processing framework along with relatively low computational burden ( $\mathcal{O}(\max \lbrace M,N\rbrace ^{2.3})$ per iteration with $M$ and $N$ being the number of antennas at the transmitter and receiver, respectively) for the user terminals can make it a potential candidate for practical implementations. Finally, we extend the proposed method for the case with channel estimation errors. Simulation results verify the efficiency of the proposed method, and in a typical scenario we have around 60 times lower run-time when compared to the counterparts of the method. [ABSTRACT FROM AUTHOR]

In this paper, the capacity region of the linear deterministic interference channel with noisy channel-output feedback (LD-IC-NF) is fully characterized. The proof of achievability is based on random coding arguments and rate splitting, block-Markov superposition coding, and backward decoding. The proof of the converse reuses some of the existing outer bounds and includes new ones obtained using genie-aided models. Following the insight gained from the analysis of the LD-IC-NF, an achievability region and a converse region for the two-user Gaussian interference channel with noisy channel-output feedback (G-IC-NF) are presented. Finally, the achievability region and the converse region are proven to approximate the capacity region of the G-IC-NF to within 4.4 bits. [ABSTRACT FROM AUTHOR]

In this paper, a pen detection analog system for an electromagnetic resonance (EMR) touch panel is presented. An adaptive charge pump is proposed in the transmitter to drive a high current to the EMR panel and achieve a high signal-to-noise ratio (SNR) in the receiver. To compensate for the mismatches between the channels due to fabrication variations of the EMR panels and process variations of the analog front-ends (AFEs), a transmitter driver with an adaptive controller is proposed, and an AFE calibration is implemented in the transmitter and the receiver, respectively. Also, a 9-bit, 2-MS/s time-interleaved flash successive-approximation-register (SAR) analog-to-digital converter (ADC) with 3-bit flash and 6-bit SAR ADCs is proposed to increase the frame rate with small area and power consumption. External noises, such as display and charger noises, can be rejected by the differential processing, analog low-pass filter, and digital filters in the digital signal processor (DSP). This read-out integrated circuit is implemented in a 0.18-μm Bipolar-CMOS-DMOS (BCD), and the die area is \text40 mm^\text2 including DSP and ADCs. The power consumptions are 110 and 45 mW in the transmitter and receiver modes, respectively. The SNR is about 39.5 dB and the frame rate is about 300 Hz in the 56 × 70 touch panel. [ABSTRACT FROM PUBLISHER]

In practical massive MIMO systems, a substantial portion of system resources are consumed to acquire channel state information (CSI), leading to a drastically lower system capacity compared with the ideal case, where perfect CSI is available. In this paper, we show that the overhead for CSI acquisition can be largely compensated by the potential gain due to the sparsity of the massive MIMO channel in a certain transformed domain. To this end, we propose a novel blind detection scheme that simultaneously estimates the channel and data by factorizing the received signal matrix. We show that by exploiting the channel sparsity, our proposed scheme can achieve a degree of freedom (DoF) very close to the ideal case, provided that the channel is sufficiently sparse. Specifically, the achievable DoF has a fractional gap of only $1/T$ from the ideal DoF, where $T$ is the channel coherence time. This is a remarkable advance for understanding the performance limit of the massive MIMO system. We further show that the performance advantage of our proposed scheme in the asymptotic SNR regime carries over to the practical SNR regime. Numerical results demonstrate that our proposed scheme significantly outperforms its counterpart schemes in the practical SNR regime under various system configurations. [ABSTRACT FROM PUBLISHER]

In this paper, the benefits of channel-output feedback in the Gaussian interference channel (G-IC) are studied under the effect of additive Gaussian noise. Using a linear deterministic (LD) model, the signal to noise ratios (SNRs) in the feedback links beyond which feedback plays a significant role in terms of increasing the individual rates or the sum-rate are approximated. The relevance of this work lies in the fact that it identifies the feedback SNRs for which in any G-IC, one of the following statements is true: (a) feedback does not enlarge the capacity region; (b) feedback enlarges the capacity region and the sum-rate is greater than the largest sum-rate without feedback; and (c) feedback enlarges the capacity region but no significant improvement is observed in the sum-rate. [ABSTRACT FROM PUBLISHER]

This paper investigates the physical layer security in a multiple-input-single-output multicast channel, where a common message is transmitted to multiple receivers and only statistical channel state information of the eavesdropper is available. We consider transmitting some artificial noise (AN) along with the information-bearing signal to improve secrecy. To find the optimal AN design, we formulate a secrecy outage probability (SOP) constrained secrecy rate maximization problem. For solving this problem, we adopt a novel transformation of the intractable SOP constraint and establish an efficient algorithm which solves the transformed problem to global optimality. We also propose a low-complexity refinement method to reduce the conservatism incurred by the transformation and an efficient algorithm to find a suboptimal solution when the information-bearing signal is transmitted using single-stream beamforming. Our solution is found to be a valuable generalization of the traditional null-space AN scheme. According to our simulation results, when the number of receivers is less than that of transmit antennas, distributing AN uniformly in the null space of the legitimate channel vectors is near-optimal. When there is no valid null space, transmitting AN will interfere with some legitimate receivers, and the secrecy performance can also be improved with carefully designed AN. [ABSTRACT FROM PUBLISHER]

Enabling device-to-device (D2D) communications in millimeter-wave (mm-wave) networks is of critical importance for the next-generation mobile networks to support very high data rates (multi-gigabits-per-second) for mobile devices. In this paper, we provide a fine-grained performance analysis of the mm-wave D2D communication networks. Specifically, we first establish a general and tractable framework to investigate the performance of mm-wave D2D networks using the Poisson bipolar model integrated with several features of the mm-wave band. To show what fraction of users in the network achieve target reliability if the required signal-to-interference-plus-noise ratio (SINR) (or QoS requirement) is given, we derive the meta distributions of the SINR and the data rate. Interestingly, in mm-wave D2D networks, the standard beta approximation for the meta distribution does not work very well when highly directional antenna arrays are used or the node density is small. To resolve this issue, we provide a modified approximation by using higher moments of the conditional SINR distribution, which is shown to be closer to the exact result. On this basis, we also derive the mean local delay and spatial outage capacity to provide a comprehensive investigation on the impact of mm-wave features on the performance of D2D communication. [ABSTRACT FROM AUTHOR]

The capacity of multiple-input multiple-output (MIMO) Rayleigh fading channels with full knowledge of channel state information (CSI) at both the transmitter and the receiver (CSI-TR) has been shown recently to scale at low signal-to-noise ratio (SNR) essentially as SNR log(1/SNR), independently of the number of transmit and receive antennas. In this paper, we investigate the ergodic capacity of MIMO Rayleigh fading channel with estimated channel state information at the transmitter (CSI-T) and possibly imperfect channel state information at the receiver (CSI-R). Our framework can be seen as a generalization of previous works as it can capture the perfect CSI-TR as a special case when the estimation error variance goes to zero. In this paper, we mainly focus on the low SNR regime, and we show that the capacity scales as $(1-\alpha)$ SNR log(1/SNR), where $\alpha$ is the estimation error variance. This characterization shows the loss of performance due to error estimation over the perfect channel state information at both the transmitter and the receiver. As a by-product of our new analysis, we show that our framework can be also extended to characterize the capacity of MIMO Rician fading channels at low SNR with possibly imperfect CSI-T and CSI-R. [ABSTRACT FROM AUTHOR]

This paper addresses a decentralized wireless networks of K separate transmitter-receiver pairs. Users treat each other as noise and there is no central controller to assign the resources to the users. Each user randomly spreads the symbols in its Gaussian codewords by the so-called signatures of spreading gain N . Any receiver is aware of the signatures of its affiliated transmitter, however, it is unaware of the signatures of other users. This makes the interference plus noise at each receiver be mixed Gaussian, and hence, there is no closed expression for the achievable rates of users. Invoking conditional entropy power inequality and a key upper bound on the differential entropy of a mixed Gaussian random vector, we develop a lower bound on the achievable rates of users. This lower bound has the same signal-to-noise ratio (SNR) scaling as that of the exact achievable rate. It is shown that the sum multiplexing gain (SMG) in the network can be made arbitrarily close to (K/N) for any finite values of K and N where K\leq N . The effect of matched filtering is studied in the particular case where the signatures are constructed over a binary alphabet. It is established that the SMG of the network is larger than (1/2e) regardless of the value of K as long as $N=2$ and the signatures are generated according to a proper nonuniform distribution. This paper is concluded by a section on signature design in the finite SNR regime. The main observation is that for any two different methods A and B of designing the signatures, if method A results in a larger achievable rate per user for sufficiently large SNR values, then construction B is likely to yield larger achievable rates for sufficiently small values of SNR. This behavior is attributed to the interplay between two critical factors, namely, the multiplexing gain per user and what we refer to as the interference entropy factor. [ABSTRACT FROM AUTHOR]

Gomadam recently proposed two distributed interference alignment algorithms, namely the zero-forcing and the maximal signal to interference plus noise ratio (max-SINR) algorithms. Both of them only require local channel state information and no symbol extension is needed. Then, Ning showed that when only one stream of information symbols is sent by each user, interference alignment may achieve receive diversity using the max-SINR algorithm. This result was, however, derived only based on an assumption. In this paper, using a different approach, we prove that interference alignment using the max-SINR algorithm indeed achieves receive diversity without the assumption used by Ning The result in this paper not only completes the proof of the result by Ning , but also generalizes it by allowing more than one stream of information symbols to be sent by each user. [ABSTRACT FROM AUTHOR]

Second order cone (SOC) restrictions have been widely employed in the design of wireless communication systems to recast precoding optimizations in convex form. This paper highlights the flexibility of this framework to handle various transmit power and interference limitations also in the multistream multiple-input multiple-output broadcast channel with imperfect channel state information at the transmitter. In particular, we propose an iterative solution for mean square error (MSE) balancing with such constraints via the Lagrangian dual formulation. The MSE balancing criteria, contrary to signal-to-interference plus-noise ratio and rate criteria, exhibit an interesting property when considering different targets for the receivers. Users with low target values are strictly prioritized in comparison to users with large MSE targets that can even be switched off. Therefore, only a subset of the receivers is served at the solution with stringent limitations for the precoders. An example of such stringent limitations are small power constraints and probabilistic interference temperature constraints that set a measurable threshold on the generated interference in a cognitive radio system. We provide four different approaches to approximate these probabilistic constraints with deterministic SOC constraints, and compare their accuracy. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a coding strategy designed to enhance the throughput of hybrid automatic repeat request (HARQ) transmissions over independent identically distributed block-fading channels with the channel state information unknown at the transmitter. We use a joint packet coding where the same channel block is logically shared among many packets. To reduce the encoding and decoding complexity, we use a two-layer coding where, first, packets are punctured, mixed, and then passed to the conventional channel encoder. We show how to optimize the puncturing rates on the basis of the empirical error-rate curves. We also discuss how the parameters of the practical turbo-codes may be modified to take advantage of the proposed HARQ scheme. Finally, simple and pragmatic rate adaptation strategies are developed. In numerical examples, our scheme is compared with the conventional incremental redundancy HARQ (IR-HARQ), which remains a strategy of choice in the region of small throughput; however, our scheme shows a notable gain of 1-2~\textrm dB in the region of high throughput, where IR-HARQ fails to provide any improvement. [ABSTRACT FROM AUTHOR]

High Peak-to-Average-Power Ratio (PAPR) of transmitted signals is a common problem in broadband telecommunication systems using an orthogonal frequency division multiplexing (OFDM) modulation scheme, as it increases transmitter power consumption. In consumer applications where it impacts mobile terminal battery life and infrastructure running costs, this is a major factor in customer satisfaction. Companding techniques have been recently used to alleviate this high PAPR. In this paper, a companding scheme with an offset, amidst two nonlinear companding levels, is proposed to achieve better PAPR reduction while maintaining an acceptable bit error rate (BER) level, resulting in electronic products of higher power efficiency. Study cases have included the effect of companding on the OFDM signal with and without an offset. A novel closed-form approximation for the BER of the proposed companding scheme is also presented, and its accuracy is compared against simulation results. A method for choosing best companding parameters is presented based on contour plots. Practical emulation of a real time OFDM-based system has been implemented and evaluated using a Field Programmable Gate Array (FPGA). [ABSTRACT FROM PUBLISHER]

In this paper, we investigate a coding strategy devised to increase the throughput in hybrid ARQ (HARQ) transmission over a block fading channel. In our approach, the transmitter jointly encodes a variable number of bits for the each round of HARQ. The parameters (rates) of this joint coding can vary and may be based on the negative acknowledgment provided by the receiver or, on the past (outdated) information about the channel states. These new degrees of freedom allow us to improve the match between the codebook and the channel states experienced by the receiver. The results indicate that gains obtained using the proposed cross-packet coding strategy are particularly notable for the large values of the throughput. In this region, the conventional HARQ fails to offer throughput improvement even if the number of transmission rounds is increased. We implement the proposed cross-packet HARQ using turbo codes, where we show that the theoretically predicted throughput gains materialize in practice; the implementation challenges are also discussed. [ABSTRACT FROM PUBLISHER]

Lattice codes used under the compute-and-forward paradigm suggest an alternative strategy for the standard Gaussian multiple-access channel (MAC): the receiver successively decodes the integer linear combinations of the messages until it can invert and recover all messages. In this paper, a multiple-access technique called compute-forward multiple access (CFMA) is proposed and analyzed. For the two-user MAC, it is shown that without time-sharing, the entire capacity region can be attained using CFMA with a single-user decoder as soon as the signal-to-noise ratios are above 1+\sqrt 2 . A partial analysis is given for more than two users. Finally, the strategy is extended to the so-called dirty MAC, where two interfering signals are known non-causally to the two transmitters in a distributed fashion. Our scheme extends the previously known results and gives new achievable rate regions. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of optimal power allocation over flat fading additive white Gaussian noise channels is considered for maximizing the average detection probability of a signal emitted from a power constrained transmitter in the Neyman–Pearson framework. It is assumed that the transmitter can perform power adaptation under peak and average power constraints based on the channel state information fed back by the receiver. Using results from measure theory and convex analysis, it is shown that this optimization problem, which is in general nonconvex, has an equivalent Lagrangian dual that admits no duality gap and can be solved using dual decomposition. Efficient numerical algorithms are proposed to determine the optimal power allocation scheme under peak and average power constraints. Furthermore, the continuity and monotonicity properties of the corresponding optimal power allocation scheme are characterized with respect to the signal-to-noise ratio for any given value of the false alarm probability. Simulation examples are presented to corroborate the theoretical results and illustrate the performance improvements due to the proposed optimal power allocation strategy. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a general centralized feedback model for interference alignment (IA) algorithms of which precoders and decoders are designed with quantized channel state information (CSI) at a central unit and then fed back to corresponding transmitters and receivers via finite-rate links. The significant difference of this model from existing models is that all the realizations of channels, precoders, and decoders are fed back by finite rates. The signal-to-interference-plus-noise ratio (SINR) characteristic of this model is analyzed, which helps derive an upper bound of average throughput loss relative to perfect IA. The upper bound is shown to be tight by simulation, particularly in the high-feedback regime. Based on this result, the scaling laws of feedback bits for channels, precoding, and decoding vectors to obtain full degree of freedom are derived, which are backward compatible to the existing results for quantized CSI only or quantized precoder only. Simulation results show that the system is interference limited at a high signal-to-noise ratio (SNR) if the three scaling laws are not simultaneously satisfied, and the throughput performance is dominantly limited by the worst feedback links among the channels, precoders, and decoders. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a distributed multiple-input–multiple-output (D-MIMO) system, where the channel is flat fading and may be correlated, and experiences both small- and large-scale fading. We assume that full knowledge of channel state information (CSI) is available at the receiver and that only the first-and second-order statistics of the channel are available at the transmitter. For such a system with square quadrature amplitude modulation (QAM), an asymptotic symbol error probability (SEP) is derived for the linear zero-forcing (ZF) receiver. Then, we propose an optimal diagonal power loading (PL) strategy that minimizes the dominant term of the asymptotic SEP subject to either a total transmission power constraint when the total power normalization coefficient can be fed back to the transmitter from the receiver or an individual transmission power constraint. A simple closed-form solution is obtained. Computer simulations show that our presented optimal system attains significant performance gains over the currently available equal PL system. [ABSTRACT FROM PUBLISHER]

In emerging heterogeneous networks (HetNets), a wide range of the underlying performance evaluation problems is related to wireless interference characterization and can be reduced to investigating the distribution of a side length in a random triangle. In this paper, we address the task of calculating the side-length distribution in such a triangle determined by the known distributions of its two other sides and the distribution of the angle between them. No restrictions on the distributions of input random variables (RVs) are imposed except for their statistical independence. Our solution delivers a crucial building block for interference analysis in multitier and multiradio HetNets, including mobile device-to-device communication as one of the most extreme interference-limited cases. [ABSTRACT FROM AUTHOR]

The aim of this paper is to study the achievable rates for a K-user Gaussian interference channel (G-IFC) for any signal-to-noise ratio using a combination of lattice and algebraic codes. Lattice codes are first used to transform the G-IFC into a discrete input--output noiseless channel, and subsequently algebraic codes are developed to achieve good rates over this new alphabet. In this context, a quantity called efficiency is introduced which reflects the effectiveness of the algebraic coding strategy. This paper first addresses the problem of finding high-efficiency algebraic codes. A combination of these codes with Construction-A lattices is then used to achieve nontrivial rates for the original G-IFC. [ABSTRACT FROM PUBLISHER]

In a companion paper, we have studied the zero-forcing (ZF) transceiver with decision feedback equalizer (DFE) over slowly time-varying narrowband multiinput multioutput (MIMO) channels. The space-time generalized triangular decomposition (ST-GTD) was used for the design of ZF-DFE transceivers. The space-time geometric mean decomposition (ST-GMD) ZF transceiver minimizes both the arithmetic mean square error (MSE) at the feedback detector and the average uncoded bit error rate (BER) in moderate high signal-to-noise ratio (SNR). This paper addresses the design problem of DFE transceiver without zero-forcing constraint. In the first part, a channel independent temporal precoder is superimposed on the conventional block-wise GMD-based minimum mean square error (MMSE) DFE transceiver to take advantage of the temporal diversity. In the second part, ST-GTD is applied for the design of MMSE DFE transceivers. With accurate channel prediction and space-time powerloading, the proposed ST-GMD MMSE transceiver minimizes the arithmetic MSE at the feedack detector, and maximizes Gaussian mutual information. For practical applications, the ST-GTD MMSE transceiver which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD MMSE system is also developed. In the convex region, our analysis shows that the proposed MMSE transceivers has better BER performance than the conventional GMD-based MMSE transceiver; the average BERs of the proposed systems are nonincreasing functions of the ST-block size. The superior performance of ST-GMD MMSE transceiver over the ST-GMD ZF transceiver is also verified analytically. [ABSTRACT FROM PUBLISHER]

For space communication circumstances, long-distance transmission significantly deteriorates the received signal-to-noise ratio (SNR) at the receiver. Moreover, the high-speed relative movement between the transmitter and the receiver causes a very large Doppler shift, thus imposing a new challenge for the acquisition. To address the Doppler shift acquisition problem under not only the very low SNR but under the very high relative movement scenarios as well, in this paper, we develop one search range correction (SRC)-based acquisition scheme, which includes three algorithms called single SRC, overlapping SRC, and iterative SRC, respectively, to significantly increase the acquisition probability for space communications. First, the single SRC algorithm, which has a simple closed-form expression for the net increment of acquisition probability, uses multiple combination periods to correct the search range for the succeeding period. Moreover, the special case using two combination periods for the single SRC algorithm is already verified to increase the acquisition probability. Second, the overlapping SRC algorithm, which is based on the period overlapping of the single SRC algorithm, enjoys much implementation feasibility and saves many received signals. Third, the iterative SRC algorithm, which builds on the iteration of the overlapping SRC algorithm, can further increase the acquisition probability as compared with that of the overlapping SRC algorithm. Simulations results show that our proposed scheme can obtain much higher acquisition probability of Doppler shift, compared with existing acquisition schemes, including the fast Fourier transform (FFT), time–frequency, and single SRC using two combination periods. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of a multiple-input–multiple-output (MIMO) maximal ratio combining (MRC) system with feedback delay and channel estimation error. By taking these practical imperfect factors into account, we first formulate the system model and derive the moment-generating function of the output signal-to-noise ratio (SNR), which serves as the basis for further system performance analysis. Then, we compute the probability density function (pdf) and the cumulative distribution function (cdf) of the output SNR. Furthermore, we derive the analytical expressions of the exact and approximate average symbol error rates (SERs) of the MIMO MRC system, which are used to investigate the performance loss in terms of the array gain and diversity order. Finally, computer simulations are conducted to show the efficacy of the analytical results and the effect of feedback delay and channel estimation error on the system performance. [ABSTRACT FROM PUBLISHER]

In this paper, we give a unified performance analysis of interference alignment (IA) over multiple-input–multiple-output (MIMO) interference channels. Rather than the asymptotic characterization, i.e., degree of freedom (DOF) at high signal-to-noise ratio (SNR), we focus on the other practical performance metrics, namely, outage probability, ergodic rate, and symbol error rate (SER). In particular, we consider imperfect IA because the transmitters usually have only imperfect channel state information (CSI) in a practical scenario. By characterizing the impact of imperfect CSI, we derive the exact closed-form expressions of outage probability, ergodic rate, and SER in terms of CSI accuracy, transmit SNR, channel condition, number of antennas, and the number of data streams of each communication pair. Furthermore, we obtain some important guidelines for performance optimization of IA under imperfect CSI by minimizing the performance loss over IA with perfect CSI. Finally, our theoretical claims are validated by simulation results. [ABSTRACT FROM PUBLISHER]

In this paper, we study the problem of per-stream maximum sum-rate joint precoder and minimum mean-squared error equalizer design for the multi-input multi-output interference channel. We consider the general case of more than three users with more than one stream per user. We propose a generalized iterative algorithm which directly maximizes the sum-rate without assuming the signal-to-noise ratio to be infinite. To reduce complexity, which can become prohibitive for large network size, we examine the performance-complexity tradeoffs involved in a sparse equalizer design. Joint precoder and equalizer optimization requires alternation between the forward and reverse links and assumes perfect synchronization between the transmitters and receivers at each network node, resulting in extensive overhead and spectral efficiency loss. To overcome this serious drawback, we propose a new design approach based on weighted-sum-rate maximization assuming a virtual equalizer type at the transmitter to limit the optimization process to the transmitter side. In addition, we quantify the sum-rate loss due to mismatched equalizer types and demonstrate the robustness of our proposed sum-rate weighting strategy to such mismatches with perfect or imperfect channel knowledge. Finally, we derive asymptotic performance expressions and verify their accuracy numerically even for a moderate number of users. [ABSTRACT FROM PUBLISHER]

In this paper, we study the codebook size design strategies in the multiple-input–multiple-output (MIMO) broadcast channel (BC) systems. We adopt the nonlinear Tomlinson–Harashima precoder (THP), which is designed by the imperfect channel direction information (CDI) acquired from the random vector quantization (RVQ) feedback mechanism. Under the limitation of the total feedback rate, we flexibly allocate the size of each user's codebook so that the overall channel capacity is maximized. Since the design problem is not convex, directly finding out the optimum allocation of codebook size is not attainable. However, by sophisticatedly using the discrete majorization theory, we can derive the codebook size allocation strategies for the high- and the low-signal-to-noise-ratio (SNR) regions. Interestingly, the results show that the equal size codebook is preferable in the low-SNR region, whereas the codebook allocates the whole available codebook size to a single user in the high-SNR region. Simulations certify the theoretical result of our design. [ABSTRACT FROM PUBLISHER]

To enhance the multiplexing gain of two-receiver Multiple-Input-Single-Output Broadcast Channel with imperfect channel state information at the transmitter (CSIT), a class of Rate-Splitting (RS) approaches has been proposed recently, which divides one receiver's message into a common and a private part, and superposes the common message on top of Zero-Forcing precoded private messages. In this paper, with quantized CSIT, we study the ergodic sum rate of two schemes, namely RS-S and RS-ST, where the common message(s) are transmitted via a space and space-time design, respectively. Firstly, we upper-bound the sum rate loss incurred by each scheme relative to Zero-Forcing Beamforming (ZFBF) with perfect CSIT. Secondly, we show that, to maintain a constant sum rate loss, RS-S scheme enables a feedback overhead reduction over ZFBF with quantized CSIT. Such reduction scales logarithmically with the constant rate loss at high Signal-to-Noise-Ratio (SNR). We also find that, compared to RS-S scheme, RS-ST scheme offers a further feedback overhead reduction that scales with the discrepancy between the feedback overhead employed by the two receivers when there are alternating receiver-specific feedback qualities. Finally, simulation results show that both schemes offer a significant SNR gain over conventional single-user/multiuser mode switching when the feedback overhead is fixed. [ABSTRACT FROM AUTHOR]

This paper develops a novel analytical framework for asynchronous wireless networks deploying multicarrier transmission over flat-fading channels. Nodes in the network have different notions of timing; therefore, from the viewpoint of a typical receiver, the received signals from different transmitters are asynchronous, leading to a loss of orthogonality between subcarriers. We first develop a detailed link-level analysis based on OFDM, based on which we propose a tractable system-level signal-to-interference-plus-noise ratio (SINR) model for asynchronous OFDM networks. The proposed model is used to analytically characterize several important statistics in asynchronous networks with spatially distributed transmitters, including: (i) the number of decodable transmitters; (ii) the decoding probability of the nearest transmitter; and (iii) the system throughput. The system-level loss from lack of synchronization is quantified, and to mitigate the loss, we compare and discuss four possible solutions including extended cyclic prefix, advanced receiver timing, dynamic receiver timing positioning, and semi-static receiver timing positioning with multiple timing hypotheses. The model and results are general, and apply to ad hoc networks, cellular systems, and neighbor discovery in device-to-device (D2D) networks. [ABSTRACT FROM PUBLISHER]

This paper studies the throughput of spectrum sharing networks utilizing rate adaptation. We use some recent results on the achievable rates of finite block-length codes to analyze the secondary user (SU) throughput with a constraint on the primary user (PU) codeword drop probability. With codewords of finite length, we derive closed-form expressions for the SU activation probability and throughput. The results are obtained in different scenarios with perfect or no channel state information at the SU transmitter. As demonstrated numerically and analytically, using finite-length codewords and rate adaptation, there is considerable potential for the data transmission of unlicensed secondary users under different quality-of-service requirements of the licensed primary users. [ABSTRACT FROM PUBLISHER]

In many wireless networks, link strengths are affected by many topological factors, such as different distances, shadowing, and intercell interference, thus resulting in some links being generally stronger than other links. From an information theoretic point of view, accounting for such topological aspects is still a novel approach, that has been recently fueled by strong indications that such aspects can crucially affect transceiver and feedback design, as well as the overall performance. This paper here takes a step in exploring this interplay between topology, feedback, and performance. This is done for the two user broadcast channel with random fading, in the presence of a simple two-state topological setting of statistically strong versus weaker links, and in the presence of a practical ternary feedback setting of alternating channel state information at the transmitter [alternating channel state information at the transmitter (CSIT)] where for each channel realization, this CSIT can be perfect, delayed, or not available. In this setting, the work derives generalized degrees-of-freedom bounds and exact expressions, that capture performance as a function of feedback statistics and topology statistics. The results are based on novel topological signal management schemes that account for topology in order to fully utilize feedback. This is achieved for different classes of feedback mechanisms of practical importance, from which we identify specific feedback mechanisms that are best suited for different topologies. This approach offers further insight on how to split the effort—of channel learning and feeding back CSIT—for the strong versus for the weaker link. Further intuition is provided on the possible gains from topological spatio-temporal diversity, where topology changes in time and across users [ABSTRACT FROM PUBLISHER]

This paper studies a decentralized wireless network of asynchronous transmitter–receiver pairs with burst transmissions. Each receiver learns about the number of active users, channel coefficients, and mutual delays based on locally available measurements. The estimates for the mutual delays are not perfect, however, they are reliable enough to guarantee successful decoding. Two signalling schemes are addressed, namely, randomized masking (RM) and reduced cycle transmission (RCT). Under RM, the $n$ symbols of a codeword are generated according to a Bernoulli–Gaussian distribution with activity factor $0<\theta \leq 1$ . This is in contrast to RCT where each codeword consists of $\lfloor \theta n\rfloor $ Gaussian symbols followed by $n-\lfloor \theta n\rfloor $ zeros. Assuming the transmitters are unaware of the number of users, channel coefficients, and mutual delays, the probability of outage under RM is considerably lower compared with RCT if the signal-to-noise ratio (SNR) is sufficiently large. A generalized RCT scheme is also examined where the $n-\lfloor \theta n\rfloor $ zero symbols are not necessarily located at the end of a codeword. In the asymptote of large SNR, the outage probability becomes vanishingly small under RM, however, it is bounded away from zero for generalized RCT regardless of the value of SNR. [ABSTRACT FROM PUBLISHER]