Wideband Regime Research Articles

Revisiting the Capacity of Noncoherent Fading Channels in mmWave System

Millimeter wave (mmWave) communications use large transmission bandwidth and experience severe propagation conditions. This forces the communication system to operate in the so-called wideband regime , where signals must be increasingly “peaky” in order to attain a large fraction of the peak unconstrained wideband capacity. This paper investigates the capacity of the noncoherent channels as a function of bandwidth for signals with average and peak power constraints operating in the millimeter spectrum. Upper and lower bounds on capacity are provided, and the impact of features peculiar to mmWave channels is investigated. Numerical results for a scenario based on recent experimental campaigns are provided. It is shown that the rate achievable by a typical user in a mmWave cell with “non-peaky” signaling can be bounded away from the peak unconstrained wideband capacity. This suggests to reconsider the role of signaling “peakedness” in future mmWave communications.

Wideband Time Frequency Coding

In the wideband regime, the performance of many of the popular modulation schemes such as code division multiple access and orthogonal frequency division multiplexing fails quickly without channel state information. black It is known that in this regime, reliable channel state information, both imperfect and perfect, cannot be obtained owing to energy constraints and limitations. This suggests the need for schemes which can perform well without channel state information. In this work, we present one such scheme, called wideband time frequency coding, which achieves rates on the order of the additive white Gaussian noise capacity without requiring any channel state information. Wideband time frequency coding combines impulsive frequency shift keying with pulse position modulation, which allows for information to be encoded in both the transmitted frequency and the transmission time period. On the detection side, we propose a non-coherent decoder based on a square-law detector, akin to the optimal decoder for frequency shift keying based signals. The impacts of various parameters on the symbol error probability and capacity of wideband time frequency coding are investigated, and the results show that it is robust to shadowing and highly fading channels. When compared to other modulation schemes such as code division multiple access, orthogonal frequency division multiplexing, pulse position modulation, and impulsive frequency shift keying without channel state information, wideband time frequency coding achieves higher rates in the wideband regime, and performs comparably in smaller bandwidths.

A Partial Channel Reciprocity-Based Codebook for Wideband FDD Massive MIMO

The acquisition of channel state information (CSI) in Frequency Division Duplex (FDD) massive MIMO has been a formidable challenge. In this paper, we address this problem with a novel CSI feedback framework enabled by the partial reciprocity of uplink and downlink channels in the wideband regime. We first derive the closed-form expression of the rank of the wideband massive MIMO channel covariance matrix for a given angle-delay distribution. A low-rankness property is identified, which generalizes the well-known result of the narrow-band uniform linear array setting. Then we propose a partial channel reciprocity (PCR) codebook, inspired by the low-rankness behavior and the fact that the uplink and downlink channels have similar angle-delay distributions. Compared to the latest codebook in 5G, the proposed PCR codebook scheme achieves higher performance, lower complexity at the user side, and requires less feedback. We derive the feedback overhead necessary to achieve asymptotically error-free CSI feedback. Two low-complexity alternatives are also proposed to further reduce the complexity at the base station side. Simulations with the practical 3GPP channel model show the significant gains over the latest 5G codebook, which prove that our proposed methods are practical solutions for 5G and beyond.

Graphene-based wide band semi-flexible array antenna with parasitic patch for smart wireless devices

AbstractIn this paper, a semi-flexible 2 × 1 array antenna is proposed with epoxy glass fiber and graphene as patch and ground, respectively. Microstrip patch antenna with a center parasitic patch of half-wavelength and slot in the radiating patch have been incorporated for the bandwidth enhancement in order of 79.56% (2.21–5.13 GHz). The antenna has an overall size of 0.30λ × 0.24λ at a lower frequency of operation (2.45 GHz). The incorporation of slotted Graphene in radiating element leads to a wideband regime with satisfactory gain values of 2.73 and 3.744 dBi at 2.40 and 4.0 GHz, respectively. Antenna radiation efficiency in the range of 78% with linear polarization makes the antenna appropriate for WLAN band and smart wireless devices application.

Kondo effect under the influence of spin–orbit coupling in a quantum wire

The analysis of the impact of spin–orbit coupling (SOC) on the Kondo state has generated considerable controversy, mainly regarding the dependence of the Kondo temperature TK on SOC strength. Here, we study the one-dimensional (1D) single impurity Anderson model (SIAM) subjected to Rashba (α) and Dresselhaus (β) SOC. It is shown that, due to time-reversal symmetry, the hybridization function between impurity and quantum wire is diagonal and spin independent (as it is the case for the zero-SOC SIAM), thus the finite-SOC SIAM has a Kondo ground state similar to that for the zero-SOC SIAM. This similarity allows the use of the Haldane expression for TK, with parameters renormalized by SOC, which are calculated through a physically motivated change of basis. Analytic results for the parameters of the SOC-renormalized Haldane expression are obtained, facilitating the analysis of the SOC effect over TK. It is found that SOC acting in the quantum wire exponentially decreases TK while SOC at the impurity exponentially increases it. These analytical results are fully supported by calculations using the numerical renormalization group (NRG), applied to the wide-band regime, and the projector operator approach, applied to the infinite-U regime. Literature results, using quantum Monte Carlo, for a system with Fermi energy near the bottom of the band, are qualitatively reproduced, using NRG. In addition, it is shown that the 1D SOC SIAM for arbitrary α and β displays a persistent spin helix SU(2) symmetry similar to the one for a 2D Fermi sea with the restriction α = β.

Sub-Nyquist Cyclostationary Detection of GFDM for Wideband Spectrum Sensing

Spectrum scarcity is a challenging problem in wireless communications: high data rates are needed to support 5G new technologies. However, the spectrum is underutilized. To address this problem, cognitive radio (CR) is proposed to exploit the underutilized spectrum. The main requirement for the future CR networks is wideband spectrum sensing, which provides secondary users with the available frequency bands across a wide frequency range. Secondary users should fill these bands without causing interference to licensed users. Thus, new waveforms are proposed for the 5G physical layer. Generalized frequency division multiplexing (GFDM) is considered to be a contender for the 5G new physical layer. The GFDM is a block-based waveform that is suitable for fragmented spectrum scenarios and is designed to overcome the drawbacks of orthogonal frequency-division multiplexing (OFDM) used in 4G. The GFDM is the perfect candidate for 5G and CR technologies. Considering the cyclostationarity properties of modulated signals, we propose an optimized recovery method for the GFDM signals in the wideband regime. By exploiting the signal sparsity, we can recover the spectral correlation function (SCF) of the GFDM from digital samples of the GFDM taken at a sub-Nyquist rate to reduce the sampling time. Furthermore, a generalized likelihood ratio test is applied to the recovered function to detect multiple signal sources and identify the spectrum occupancy. The numerical results show that our method achieves a high probability of detection at a low signal-to-noise ratio (SNR) with robustness in terms of rate reduction in wireless networks.

Energy-Efficient Routing and Link Adaptation for 2D Wireless Relay Networks in the Wideband Regime

We discuss the globally optimal energy-efficient design of a 2D relay network. Different from the existing routing protocols on energy saving, which finds the minimal energy route for a given data rate, the proposed algorithm jointly optimizes routing and data rate to maximize energy efficiency (EE) defined as the achievable data rate per power consumption. We propose a low-complexity algorithm to circumvent the huge complexity of the exhaustive search for the network EE maximization and prove its global optimality. Moreover, the proposed algorithm is implemented in a distributed fashion because each relay needs to send its routing information only to the relays in its adjacent tiers, which significantly reduces the signaling overhead of the centralized implementation. Our analysis on the worst-case complexity in a fading channel shows that the complexity of the proposed algorithm increases linearly while that of the exhaustive search increases exponentially as the tier index increases. Simulation results confirm that the proposed algorithm outperforms the existing routing protocols on energy saving and achieves the globally optimal network EE at a significantly lower complexity than the exhaustive search.

Blind Estimation of Sparse Broadband Massive MIMO Channels With Ideal and One-bit ADCs

We study the maximum likelihood problem for the blind estimation of massive mmWave MIMO channels while taking into account their underlying sparse structure, the temporal shifts across antennas in the broadband regime, and ultimately one-bit quantization at the receiver. The sparsity in the angular domain is exploited as a key property to enable the unambiguous blind separation between user's channels. The main advantage of this approach is the fact that the overhead due to pilot sequences can be dramatically reduced especially when operating at low SNR per antenna. In addition, as sparsity is the only assumption made about the channel, the proposed method is robust with respect to the statistical properties of the channel and data and allows the channel estimation and the separation of interfering users from adjacent base stations to be performed in rapidly time-varying scenarios. For the case of one-bit receivers, a blind channel estimation is proposed that relies on the Expectation Maximization (EM) algorithm. Additionally, performance limits are derived based on the clairvoyant Cramer Rao lower bound. Simulation results demonstrate that this maximum likelihood formulation yields superior estimation accuracy in the narrowband as well as the wideband regime with reasonable computational complexity and limited model assumptions.

NROAR: Near Real-Time Opportunistic Spectrum Access and Management in Cloud-Based Database-Driven Cognitive Radio Networks

Cognitive radio network with spectrum sensing to find idle channels and access them opportunistically is regarded as an emerging technology to deal with spectrum scarcity caused by exclusive licensing to primary systems. Simulation-based studies loose practical relevance due to assumptions and usage of simple models for defining transmission regions, multi-path propagation, and traffic intensity. In this paper, we present an experimental study for near real-time spectrum sensing and opportunistic spectrum access in database-driven cognitive radio networks (nROAR) using national instrument USRP devices in wide-band regime. We present numerical results for evaluating spectrum sensing using adaptive threshold-based joint energy and bandwidth detection. Furthermore, we evaluate the dynamic spectrum access using database-driven quorum-based rendezvous for opportunistic access for admitted unlicensed secondary users in diverse wireless bands. The proposed nROAR architecture addresses challenges related to providing spectrum access which require fast processing of a large number of spectrum-sensing measurements across diverse wireless bands, geography, and time.

WINDOW: wideband demodulator for optical waveforms.

Optical communication systems, which operate at very high rates, are often limited by the sampling rate bottleneck. The optical wideband regime may exceed analog to digital converters (ADCs) front-end bandwidth. Multi-channel sampling approaches, such as interleaved ADCs, also known as multicoset sampling in some contexts, have been proposed to sample the wideband signal using several channels. Each channel samples below the Nyquist rate such that the overall sampling rate is preserved. However, this scheme suffers from two practical limitations that make its implementation difficult. First, the inherent anti-aliasing filter of the samplers distorts the wideband signal. Second, it requires accurate time shifts on the order of the signal's Nyquist rate, which are challenging to maintain. In this work, we propose an alternative multi-channel sampling scheme, the wideband demodulator for optical waveforms (WINDOW), based on analog RF demodulation, where each channel aliases the spectrum using a periodic mixing function before integration and sampling. We show that intentionally using the inherent ADC filter to perform integration increases the signal to noise ratio (SNR). We demonstrate both theoretically and through numerical experiments that our system outperforms interleaved sampling in terms of signal recovery and symbol estimation in the presence of both thermal and quantization noise but is slightly less robust to timing jitter. The main contribution of this work is the application of RF demodulation concepts proposed in the context of sub-Nyquist sampling, e.g. random demodulator and modulated wideband converter, to optical communication signals in the Nyquist regime. We develop a sampling scheme that presents an alternative for optical links where thermal noise in the receiver is the bottleneck.

Revisiting the Capacity of Noncoherent Fading Channels in mmWave System

Millimeter wave (mmWave) communications use large transmission bandwidth and experience severe propagation conditions. This forces the communication system to operate in the so-called wideband regime , where signals must be increasingly “peaky” in order to attain a large fraction of the peak unconstrained wideband capacity. This paper investigates the capacity of the noncoherent channels as a function of bandwidth for signals with average and peak power constraints operating in the millimeter spectrum. Upper and lower bounds on capacity are provided, and the impact of features peculiar to mmWave channels is investigated. Numerical results for a scenario based on recent experimental campaigns are provided. It is shown that the rate achievable by a typical user in a mmWave cell with “non-peaky” signaling can be bounded away from the peak unconstrained wideband capacity. This suggests to reconsider the role of signaling “peakedness” in future mmWave communications.

Game Theoretic Cloud-Assisted Opportunistic Spectrum Access in Cognitive Radio Networks

Opportunistic Spectrum Access (OSA) in a Cognitive Radio Network (CRN) is regarded as emerging technology for utilizing the scarce Radio Frequency (RF) spectrum by allowing unlicensed secondary users (SUs) to access licensed spectrum without creating harmful interference to primary users (PUs). The SUs are considerably constrained by their limited power, memory and computational capacity when they have to make decision about spectrum sensing for wide band regime and OSA. The SUs in CRN have the potential to mitigate these constraints by leveraging the vast storage and computational capacity of cloud computing approaches. In this paper, the authors investigate a game theoretic approach for opportunistic spectrum access in cognitive networks. The proposed algorithm leverages the geo-locations of both SUs and spectrum opportunities to facilitate OSA to SUs. The active SUs using game theory adapt their transmit powers in a distributed manner based on the estimated average packet-error rate while satisfying the Quality-of-Service (QoS) in terms of signal-to-interference-noise-ratio (SINR). Furthermore, to control greedy SUs in distributed power control game, the authors introduce a manager/leader through a Stackelberg power adaptation game. The performance of the proposed approaches is investigated using numerical results obtained from simulations.

The Impact of Statistical Delay Constraints on the Energy Efficiency in Fading Channels

This work analyzes the energy efficiency in fading channels under statistical delay constraints, imposed as limitations on the maximal delay violation probabilities. The Maximum Constant Arrival Rates are characterized with the aid of the notion of effective capacity, based on which the spectral efficiency-bit energy tradeoff is analyzed in the low-SNR regime. The analysis is performed under two assumptions: 1) perfect channel side information (CSI) at receiver only and 2) perfect CSI at both the transmitter and receiver. It is proven that the bit energy required at zero spectral efficiency is indeed the minimum bit energy. The expressions for the minimum bit energy and wideband slope are obtained. It is shown that the performances of the low-power and wideband regimes are the same, while the statistical queueing constraints have different behaviors. It is found that the minimum bit energy requirements increase as the statistical delay constraints become more stringent. Moreover, it is demonstrated that the minimum bit energy required is the same as that attained when only statistical queueing constraints are enforced in the wideband regime, while the bit energy increment is larger to achieve the same nonzero spectral efficiency. Overall, the impact upon the energy efficiency of statistical delay constraints is quantified.

Single and multi‐frequency wideband spectrum sensing with side‐information

This study addresses the optimal spectrum sensing detection based on the complete or partial side-information on the signal and noise statistics. The use of the generalised-likelihood ratio test (GLRT) involves maximum-likelihood (ML) estimation of the nuisances. ML estimation of the unknowns is especially challenging for wideband cognitive radio because closed-form solutions are often not available. Based on the equivalence between the wideband regime and the low-signal-to-noise ratio regime, this study provides a general kernel framework for GLRT spectrum sensing. It is shown that any GLRT detector exclusively depends on the projection of the sample covariance matrix of the data onto a given underlying kernel that reflects the available side-information in the problem. The kernels in several scenarios of interest are derived, including the widespread single and multi-frequency channelisation cases. Theoretical interpretations and numerical results show the trade-off between detection performance and the degree of side-information on the most informative statistics for detection, that is, the modulation format and spectrum distribution of the primary users.

Secret Key Generation from Sparse Wireless Channels: Ergodic Capacity and Secrecy Outage

This paper investigates generation of a secret key from a reciprocal wireless channel. In particular we consider wireless channels that exhibit sparse structure in the wideband regime and study the impact of sparsity on the secret key capacity. We explore this problem in two steps. First, we study key generation from a state-dependent discrete memoryless multiple source. The state of the source captures the effect of channel sparsity. Secondly, we consider a wireless channel model that captures channel sparsity and correlation between the legitimate users' channel and the eavesdropper's channel. Such dependency can significantly reduce the secret key capacity. According to system delay requirements, two performance measures are considered: (i) ergodic secret key capacity and (ii) outage probability. We show that in the wideband regime when a white sounding sequence is adopted, a sparser channel can achieve a higher ergodic secret key rate than a richer channel can. For outage performance, we show that if the users generate secret keys at a fraction of the ergodic capacity, the outage probability will decay exponentially in signal bandwidth. Moreover, a larger exponent is achieved by a richer channel.

Energy Efficiency in the Wideband Regime

End-to-end communication is the fundamental building block of communication networks. In this paper, we discuss globally optimal energy efficient design for end-to-end communications. An end-to-end multiple-hop system with one sender, one receiver, and multiple relays is considered. We first study in detail energy-efficient designs in the wideband regime that is characterized by wide signal bandwidth and low spectral efficiency, and later briefly those in the narrowband regime. We will reveal the globally optimal link adaptation as well as relay deployment strategies such that the whole system can achieve the highest energy efficiency. The technologies proposed can be used in various communication systems, such as the deployment and communication of wired core networks and wireless relay networks, to improve their energy efficiency. While this paper focuses on a linear end-to-end network topology, the methodology can be easily extended to two-dimensional network topologies for energy-efficient designs of the whole network.

Optimal Transmission for the MIMO Bidirectional Broadcast Channel in the Wideband Regime

This paper considers a transmit strategy for an AWGN MIMO bidirectional broadcast channel in the wideband regime. In order to characterize the boundaries of the wideband capacity and energy per bit regions, the transmit strategy at the relay is designed to maximize the weighted wideband rate sum. A closed form of the optimal transmit covariance matrix is derived, which shows that a single beam transmit strategy is optimal. The transmit strategies for some special cases are also analyzed. The fairness versus energy efficiency tradeoff is then discussed. In addition, an extension to multipair MIMO bidirectional broadcast channel is studied in which we show that serving a certain pair with full power is optimal in the sense of maximizing the achievable weighted wideband rate sum. Finally, a discussion on the conjecture of the minimum energy per bit for multi-pair systems is provided.

Optimizing Constellations for Single-Subcarrier Intensity-Modulated Optical Systems

We optimize modulation formats for the additive white Gaussian noise channel with nonnegative input, also known as the intensity-modulated direct-detection channel, with and without confining them to a lattice structure. Our optimization criteria are the average electrical, average optical, and peak power. The nonnegative constraint on the input to the channel is translated into a conical constraint in signal space, and modulation formats are designed by sphere packing inside this cone. Some dense packings are found, which yield more power-efficient modulation formats than previously known. For example, at a spectral efficiency of 1.5 bit/s/Hz, the modulation format optimized for average electrical power has a 2.55 dB average electrical power gain over the best known format to achieve a symbol error rate of 10^-6. The corresponding gains for formats optimized for average and peak optical power are 1.35 and 1.72 dB, respectively. Using modulation formats optimized for peak power in average-power limited systems results in a smaller power penalty than when using formats optimized for average power in peak-power limited systems. We also evaluate the modulation formats in terms of their mutual information to predict their performance in the presence of capacity-achieving error- correcting codes, and finally show numerically and analytically that the optimal modulation formats for reliable transmission in the wideband regime have only one nonzero point.

Nonparaxial wave analysis of three-dimensional Airy beams

The three-dimensional Airy beam (AiB) is thoroughly explored from a wave-theory point of view. We utilize the exact spectral integral for the AiB to derive local ray-based solutions that do not suffer from the limitations of the conventional parabolic equation (PE) solution and are valid far beyond the paraxial zone and for longer ranges. The ray topology near the main lobe of the AiB delineates a hyperbolic umbilic catastrophe, consisting of a cusped double-layered caustic. In the far zone this caustic is deformed and the field loses its beam shape. The field in the vicinity of this caustic is described uniformly by a hyperbolic umbilic canonical integral, which is structured explicitly on the local geometry of the caustic. In order to accommodate the finite-energy AiB, we also modify the conventional canonical integral by adding a complex loss parameter. The canonical integral is calculated using a series expansion, and the results are used to identify the validity zone of the conventional PE solution. The analysis is performed within the framework of the nondispersive AiB where the aperture field is scaled with frequency such that the ray skeleton is frequency independent. This scaling enables an extension of the theory to the ultrawideband regime and ensures that the pulsed field propagates along the curved beam trajectory without dispersion, as will be demonstrated in a subsequent publication.

Energy efficiency in multiaccess fading channels under QoS constraints

In this article, transmission over multiaccess fading channels under quality-of-service (QoS) constraints is studied in the low-power and wideband regimes. QoS constraints are imposed as limitations on the buffer violation probability. The effective capacity, which characterizes the maximum constant arrival rates in the presence of such statistical QoS constraints, is employed as the performance metric. A two-user multiaccess channel model is considered, and the minimum bit energy levels and wideband slope regions are characterized for different transmission and reception strategies, namely time-division multiple-access (TDMA), superposition coding with fixed decoding order, and superposition coding with variable decoding order. It is shown that the minimum received bit energies achieved by these different strategies are the same and independent of the QoS constraints in the low-power regime, while they vary with the QoS constraints in the wideband regime. When wideband slope regions are considered, the suboptimality of TDMA with respect to superposition coding is proven in the low-power regime. On the other hand, it is shown that TDMA in the wideband regime can interestingly outperform superposition coding with fixed decoding order. The impact of varying the decoding order at the receiver under certain assumptions is also investigated. Overall, energy efficiency of different transmission strategies under QoS constraints are analyzed and quantified.