This paper models the line-of-sight (LOS) channel between two continuous circular antennas (CCAs) as a bounded linear normal operator whose kernel is defined by a deployment parameter: the product of the antenna radii divided by the product of the wavelength and transmission distance. Eigendecomposition reveals that orbital angular momentum (OAM) serves as the eigenmodes, with eigenvalues given by Bessel functions of the first kind, evaluated at the deployment parameter. By linking discrete circular arrays to CCAs through spatial sampling, we derive analytical expressions for the singular values of the LOS multiple-input multiple-output (MIMO) channel. The analysis considers two configurations: one where receive antennas form a single uniform circular array (UCA) with a rotational angular offset, and one with multiple sub-UCAs having different angular offsets, in both cases with the number of receive antennas being an integer multiple of the transmit antennas. For each setup, discrete Fourier transform (DFT)-based transceiver structures are proposed to achieve channel capacity. Numerical evaluations reveal: (i) The number of effective spatial degrees of freedom generally increases with the deployment parameter, but not monotonically (for fixed angular offsets); (ii) Channel capacity does not necessarily increase with the deployment parameter when the number of antennas is fixed; (iii) Angular offset significantly impacts performance when the number of antennas is small relative to the parameter; (iv) With a large number of antennas, the singular values of both configurations approach the CCA singular values, and the impact of angular offsets diminishes; (v) The non-uniform configuration studied in this paper yield small or no gains compared to the uniform configuration when angular offsets are optimized.

Unlocking the potential of millimeter-wave (mmWave) phased array systems demands robust nonlinear transmitter modeling and digital pre-distortion (DPD) techniques. In this article, we present a novel behavioral modeling approach and the corresponding linearization solution for beamforming antenna arrays comprising multiple and mutually interacting nonlinear power amplifier (PA) units. Our non-recursive transmitter model simplifies numerical evaluations across diverse phased array/multiple-input multiple-output (MIMO) configurations under crosstalk-induced load modulation. We introduce a novel, nonlinear forward model parameter identification algorithm tailored for crosstalk-prone array systems and applicable in arbitrary MIMO transmitter configurations, enabling precise modeling and characterization using over-the-air (OTA) observations. Furthermore, we propose an offline direct learning architecture based DPD method, harnessing the estimated nonlinear array forward model and specific beam-sweeping procedure, for linearizing phased arrays under severe load modulation. Numerical assessments across various scenarios demonstrate superior performance, while physical validation on a measurement test bench reinforces our methodology’s real-world applicability. Overall, this work paves the way for advanced nonlinear array transmitter optimization and linearization, vital for next-generation wireless communication networks.

In this paper, we present a comprehensive foundation for the theory and practice of pilot-based carrier phase synchronization of OFDM symbols in the presence of phase noise. The system covers phase noise added in both the transmitter and receiver together with a frequency-selective channel. A novel, low-complexity, phase noise estimation method is presented, and we show that it is close to optimal over a wide dynamic range of phase noise. Additionally, a method for approximating the phase noise over the OFDM symbol using principal component analysis is proposed, where the number of parameters to estimate can be significantly reduced with minimal impact on performance.

We establish a solid foundation for the theory and practice of pilot-based carrier phase synchronization in line-of-sight (LOS) MIMO systems affected by phase noise. LOS MIMO is a multi-antenna technology used in fixed wireless backhaul systems. As part of this, a realistic and simple oscillator phase-locked loop model is employed. To maximize the rate, a novel pilot-based MMSE estimator is formulated to jointly estimate the received symbols and the unknown phase noise at both the transmitter and receiver. Additionally, we demonstrate that effective power allocation, considering phase noise, is crucial for maximizing the rate in phase noise-limited systems.

This article presents an algorithm to effectively model the non-ideal behavior of RF mixers employed within the structure of I/Q modulators. The proposed model is based on the memory polynomial model, which includes nonlinearities and memory effects. To evaluate the accuracy and validity of the algorithm, a comprehensive analysis is conducted using measured data. Furthermore, this study focuses on the analysis and extraction of key parameters associated with I/Q modulators based on the proposed mixer model. Experimental comparisons are performed to assess the agreement between the measured values of each parameter and their corresponding estimated values derived from the model-based analysis. The experimental validation and comparative analysis validate the effectiveness of the proposed model in accurately capturing the intricacies of the mixers’ behavior within the I/Q modulator structure.

Localization is envisioned as a key enabler to satisfy the requirements of communications and context-aware services in the fifth/sixth generation (5G/6G) communication systems. User localization can be achieved based on delay and angle estimation using uplink/downlink pilot signals. However, hardware impairments (HWIs) (such as phase noise and mutual coupling) distort the signals at both the transmitter and receiver sides and thus affect the localization performance. While this impact can be ignored at lower frequencies with less severe HWIs, and less stringent localization requirements, modeling and analysis efforts are needed for high-frequency bands to assess degradation in localization accuracy due to HWIs. In this work, we model various types of impairments for a mmWave multiple-input-multiple-output communication system and conduct a misspecified Cramér-Rao bound analysis to evaluate HWI-induced performance losses in terms of angle/delay estimation and the resulting 3D position/orientation estimation error. We also investigate the effect of individual and overall HWIs on communications in terms of symbol error rate (SER). Our extensive simulation results demonstrate that each type of HWI leads to a different level of degradation in angle and delay estimation performance, and the prominent impairment factors on delay estimation will have a dominant negative effect on SER.

A complete theoretical analysis is presented for a highly efficient power amplifier (PA) architecture based on a non-reciprocal combiner. The architecture consists of two amplifier branches and a microwave circulator acting as the output combiner, referred to as the circulator load-modulated amplifier (CLMA). The continuous-mode (CM) design technique has been further exploited for the CLMA to demonstrate the wideband capabilities of the architecture. The analysis reveals that the CLMA performs active load modulation to maintain high PA efficiency performance across a wide bandwidth and large output power dynamic range. As a proof of concept, a CLMA demonstrator circuit based on gallium nitride (GaN) transistors and a microwave circulator, is designed and characterized with continuous-wave and modulated-signal measurements. The implemented CLMA prototype circuit experimentally demonstrates Doherty-like efficiency enhancement over a large bandwidth covering 2.1 to 3.5 GHz. In measurements, the prototype exhibits a drain efficiency of 46.7-57.5% at peak output power and 35.6-50.6% at 7-dB output power back-off level, within the design bandwidth. When tested with a 60-MHz multi-carrier orthogonal frequency-division multiplexing (OFDM) signal having a 7-dB peak-to-average power ratio (PAPR), an average efficiency of 48.5% with better than −47.5-dBc adjacent channel leakage ratio (ACLR) is achieved after applying digital pre-distortion (DPD).

The Shannon capacity for the line-of-sight (LOS) multiple-input multiple-output (MIMO) channel between two perfectly aligned uniform circular arrays (UCAs) is derived from first principles in a tutorial fashion. It is well known that harmonically related complex exponentials (also known in the literature as orbital angular momentum (OAM) modes) are eigenmodes for the spatially continuous channel. We show that the corresponding eigenvalues can be expressed as Bessel functions of the first kind. We also show that the spatially discrete channel between two UCAs with the same finite number of Hertzian dipole antennas on both sides has eigenmodes that are spatially sampled continuous OAM modes, and discrete eigenvalues that are aliased versions of the continuous eigenvalues. Through numerical solution of Maxwell's equations, we verify that the discrete eigenvalues for UCAs with realistic dipole antennas are the same as with the Hertzian dipoles for the studied geometries (1 km hop distance, UCA radius 1 and 2 m, carrier frequency 70 GHz) as long as antenna spacing is not very dense.

We consider the phase noise affecting communication systems, where local oscillators are employed to obtain a reference signal for frequency and phase synchronizations. We try to fill the gap between measurements and analytical models, in case of free-running and phase-locked oscillators. In particular, we propose a closed form expression for the power spectral density of the phase noise described by few parameters that are explicitly linked to the oscillator measurements. We also propose an analytical model for the oscillator power spectral density.

We present a solid foundation for the theory and practice of using pilot tones for estimation and compensation of phase noise in a communication link. We analyze several phase estimators and illustrate their pros and cons, and we derive the necessary optimal signal-to-pilot-power relationship when the transmitted power is shared between the communication signal and the pilot tone. We show that the optimal signal-to-pilot-power ratio increases with decreasing phase noise and with increased additive noise.

Hardware impairments in general and amplifier nonlinearity in particular severely limit the performance of communication links. This paper analytically provides statistical results on how a nonlinear amplifier affects the quality of signals in communication systems. In particular, we propose a statistical model that describes the nonlinear distortion as a function of the input signal’s average and instantaneous power and captures the pulse-shaping and matched filters’ effects. We show through simulations and complementary measurements that the proposed model can provide an authentic connection between the communication system parameters, power amplifier nonlinearity characteristics, and the communication system performance. It serves not only as a reliable model for nonlinear distortion analysis but also as a design tool that allows optimization of signal and filter characteristics with respect to nonlinear distortion.

We propose a novel discrete-time model for the phase noise signal, in case of free-running and phase-locked oscillators. In particular, we show how the PN can be described by an autoregressive process. The strength of the proposed model is that it can be easily expressed in terms of measurement parameters of practical oscillators. We then analyse the most common discrete-time phase noise channel model with reference to the measurement parameters and to the system bandwidth. The derived analytical models for the discrete-time phase noise signal can be used for the design of estimation/detection algorithms, for performance evaluation, or simply for fast simulations.

This paper considers the uplink of a single-cell multi-user massive multiple-input multiple-output (MIMO) system. Each receiver antenna of the base station is assumed to be equipped with a pair of analog-to-digital converters (ADCs) to quantize the real and imaginary part of the received signal. We propose a novel Bussgang-based weighted zero-forcing (B-WZF) receiver, which distinguishes the clipping and granular distortion. Numerical results demonstrate that for sufficiently high SNR and users that do not experience deep large-scale fading, the B-WZF brings significant performance gain over existing linear receivers in the literature, when the training sequence length is higher than the number of users.

We present a framework for joint estimation and compensation of three major oscillator impairments, namely sampling time error (STE), carrier frequency offset (CFO) and phase noise (PN). In particular, we model these impairments as Wiener processes and introduce a pilot-aided approach which facilitates their joint estimation. The proposed solution is carried out in two steps: first, an initial estimation of the transmitted symbols is acquired by applying an extended Kalman filter (EKF) on the pilot symbols and then, a second EKF is applied on the estimated symbols which yields an accurate tracking of STE, PN and CFO over an additive white Gaussian noise channel. Our numerical results demonstrate the efficacy of the proposed solution.

This paper considers the uplink of a single-cell multiuser massive multiple-input multiple-output system. Each receiver antenna of the base station (BS) is assumed to be equipped with a pair of analog-to-digital converters to quantize the real and imaginary part of the received signal. We propose a novel clipping-aware receiver (CA-MMSE), which performs minimum mean square error (MMSE) reconstruction only on the clipped received samples, while the granular samples are left unchanged after the quantization. On this basis, we present an iterative algorithm to implement the CA-MMSE receiver and derive a sufficient condition for its geometrical convergence to a fixed point. We show that as long as the number of BS antennas or the quantization resolution is sufficiently high, then, the performance of the CA-MMSE is as good as the optimal MMSE receiver which reconstructs all quantized received symbols. Additionally, we propose a novel Bussgang-based weighted zero-forcing (B-WZF) receiver which distinguishes the clipping and granular distortion and it is shown that as long as the received training symbols per antenna are correlated, the CA-MMSE brings significant improvements compared to conventional receivers in the literature while for users that do not experience deep large-scale fading the simpler B-WZF is near to the CA-MMSE for sufficiently high signal-to-noise ratio and quantization resolution.

In this paper, we present a novel and effective linearization technique for nonlinear phased array antennas. For large phased arrays, linearization of the array using a single digital predistortion (DPD) is inevitable since one digital path is upconverted and feeds several RF transmission paths, each of which is connected to a power amplifier (PA) and an antenna element. However, a critical issue is that the PA characteristics can vary considerably within an array. Thus, linearizing individual PAs with one DPD is rather challenging. We formulate and solve an optimization problem that corresponds to jointly minimizing the maximum residuals between the input to the array and the output of individual PAs. We demonstrate that the proposed technique outperforms state-of-the-art linearization solutions while retaining the linear gain of the array.

Low complexity and spectral efficient carrier frequency offset (CFO) estimation in massive multiple input multiple output (MIMO) systems is a critical problem. Therefore, in this paper we propose a low complexity CFO estimation technique for single carrier frequency domain equalization (SC-FDE) and orthogonal frequency division multiplexing (OFDM) based Massive MIMO systems. In this technique, to increase the spectral efficiency, we use the pilots sent for channel estimation to estimate both the CFO and the channel, iteratively. Our analysis show that our proposed technique has better performance and lower complexity than previous techniques which utilize one pilot block for both CFO and channel estimation in massive MIMO systems.

In this paper, we consider the design of spiral constellations for channels affected by phase noise. The strength of the proposed constellations resides both on the performance and on the extreme simplicity of the design. The symbols can in fact be expressed in analytical form, and are uniquely defined through a single parameter that accounts for the phase and thermal noise variances. The performance of the proposed constellations are assessed in terms of information rate and error rate. Despite their simplicity, the new spiral constellations have excellent performance, especially when the constellation size grows large.

In this paper, we consider the design of spiral constellations for channels affected by phase noise. The strength of the proposed constellations resides both on the performance and on the extreme simplicity of the design. The symbols can in fact be expressed in analytical form, and are uniquely defined through a single parameter that accounts for the phase and thermal noise variances. The structure of the proposed constellations allows to easily determine the points that are closest to any point in the complex plane, therefore we also propose a low complexity detector that is suitable for phase noise channels in medium-high signal-to-noise ratio conditions. The performance of the proposed constellations are assessed in terms of information rate and error rate. Despite their simplicity, the new spiral constellations have excellent performance, especially when the constellation size grows large.

In this paper, we present a technique to model and linearize a multi-antenna transmitter using only a small set of observation receivers that perform over-the-air measurements. We assume that the transmitter suffers from distortion due to power amplifier (PA) nonlinearities but not from crosstalk. By avoiding the use of an observation receiver in every transmitter branch, the hardware complexity and cost of multi-antenna transmitters can be reduced. First, equations are developed to extract PA models from observation receivers. Based on the extracted PA models, predistorters can then be identified for every transmit branch. We present simulation results that demonstrate that it is indeed possible to model and linearize a set of PAs using only one single observation receiver.

In massive multiple-input-multiple-output base stations, power consumption and cost of the low-noise amplifiers (LNAs) can be substantial because of the many antennas. We investigate the feasibility of inexpensive, power efficient LNAs, which inherently are less linear. A polynomial model is used to characterize the nonlinear LNAs and to derive the second-order statistics and spatial correlation of the distortion. We show that, with spatial matched filtering (maximum-ratio combining) at the receiver, some distortion terms combine coherently, and that the signal-to-interference-and-noise ratio of the symbol estimates therefore is limited by the linearity of the LNAs. Furthermore, it is studied how the power from a blocker in the adjacent frequency band leaks into the main band and creates distortion. The distortion term that scales cubically with the power received from the blocker has a spatial correlation that can be filtered out by spatial processing and only the coherent term that scales quadratically with the power remains. When the blocker is in free-space line-of-sight and the LNAs are identical, this quadratic term has the same spatial direction as the desired signal, and hence cannot be removed by linear receiver processing.

The distortion from massive multiple-input multiple-output base stations with nonlinear amplifiers is studied and its radiation pattern is derived. The distortion is analyzed both in-band and out-of-band. By using an orthogonal Hermite representation of the amplified signal, the spatial cross-correlation matrix of the nonlinear distortion is obtained. It shows that, if the input signal to the amplifiers has a dominant beam, the distortion is beamformed in the same way as that beam. When there are multiple beams without any one being dominant, it is shown that the distortion is practically isotropic. The derived theory is useful to predict how the nonlinear distortion will behave, to analyze the out-of-band radiation, to do reciprocity calibration, and to schedule users in the frequency plane to minimize the effect of in-band distortion.

Hybrid beamforming (HBF) is a potential solution to reduce the baseband hardware cost in massive multiple-input multiple-output (MIMO) systems that has drawn considerable attention recently. In this paper, we consider the uplink of a multiuser massive MIMO system in the presence of blockers. Such blockers, which arise from, for example, users served by other non-cooperative base stations (BSs), can limit the system performance if not handled properly. We propose a HBF scheme that can remove the impact of blockers, while preserving signals from intended users. Specifically, in our two-step receive beamforming scheme, the analog beamformer (ABF) is designed based on channel covariance matrices to minimize the powers of blockers, while the digital beamformer (DBF) deals with inter-user interference. We propose an iterative algorithm that efficiently gives a good sub-optimal solution to the NP-hard problem in the ABF design. Moreover, we consider a more complete BS architecture by incorporating automatic gain control (AGC) and analog-to-digital converter (ADC). As we show in the simulations, for a system with full-precision ADCs, our scheme approaches the sum rate of an ideal fully-digital system. Interestingly, for a system with low-resolution ADCs, our HBF scheme can even outperform a fully-digital system.

This paper studies the impact of in-phase and quadrature imbalance (IQI) on the downlink of a single-cell multiuser multiple-input multiple-output (MU-MIMO) system with large antenna arrays. Moreover, we consider a time-division duplex (TDD) system where we assume uplink/downlink channel reciprocity in the downlink precoding design. We study the impact of uplink/downlink channel mismatch on the downlink rate caused by different IQI at the base station (BS) and users equipment (UEs). A tractable analytical expression to predict the achievable downlink rates is derived for the regularized zero-forcing (RZF) and based on this expression, we prove that, as the number of BS antennas grow large, the achievable downlink rate of each UE is limited either by the RX IQI at the UEs or by the simultaneous presence of the transmit/receive IQI at the BS and TX IQI at the UEs, when there is uplink/downlink channel mismatch.

In this paper, we study the impact of in-phase and quadrature imbalance (IQI) on single-cell multiuser multiple-input multiple-output systems with large antenna arrays. Moreover, we consider a time-division duplex system, where we assume uplink/downlink channel reciprocity in the downlink precoding design. First, we investigate the effect of transceiver IQI on the uplink channel estimation by deriving the linear minimum-mean-square-error estimator for the IQ-impaired model and prove that only the receiver IQI at the base station (BS) limits the estimation accuracy. Then, we study the impact of uplink/downlink channel mismatch on the downlink rate caused by different IQI at the BS and user equipments (UEs). We prove that the achievable downlink rate of each UE is limited either by the receiver IQI at the UEs or jointly by the transmit and receive IQI at the BS, when there is mismatch between the uplink and downlink channels.

The spatial characteristics of the out-of-band radiation that a multiuser MIMO system emits, due to its power amplifiers (modeled by a polynomial model) being nonlinear, are studied by deriving an analytical expression for the continuous-time cross-correlation of the transmit signals. It is shown that, at any spatial point and on any frequency, the received power averaged over many channel realizations from a MIMO base station is the same as from a SISO base station when the two radiate the same amount of power. For a specific channel realization however, the received power can deviate from this average. We show that the deviations from the average are small in a MIMO system with multiple users and that the deviations can be significant with only one user. Using an ergodicity argument, we conclude that out-of-band radiation is less of a problem in massive MIMO, where precoding and array gain let us reduce the total radiated power compared to SISO systems. The requirements on spectral regrowth can therefore be relaxed in MIMO systems without causing more total out-of-band radiation.

This paper investigates the performance of the point-to-point multiple-input-multiple-output (MIMO) systems in the presence of a large but finite numbers of antennas at the transmitters and/or receivers. Considering the cases with and without hybrid automatic repeat request (HARQ) feedback, we determine the minimum numbers of the transmit/receive antennas, which are required to satisfy different outage probability constraints. Our results are obtained for different fading conditions and the effect of the power amplifiers efficiency/feedback error probability on the performance of the MIMO-HARQ systems is analyzed. Then, we use some recent results on the achievable rates of finite block-length codes, to analyze the effect of the codewords lengths on the system performance. Moreover, we derive closed-form expressions for the asymptotic performance of the MIMO-HARQ systems when the number of antennas increases. Our analytical and numerical results show that different outage requirements can be satisfied with relatively few transmit/receive antennas.

In massive multiple-input multiple-output (MIMO), most precoders result in downlink signals that suffer from high peak-to-average ratio (PAR), independently of modulation order and whether single-carrier or orthogonal frequency-division multiplexing (OFDM) transmission is used. The high PAR lowers the power efficiency of the base-station amplifiers. To increase the power efficiency, low-PAR precoders have been proposed. In this paper, we compare different transmission methods for massive MIMO in terms of the power consumed by the amplifiers. It is found that: 1) OFDM and single-carrier transmission have the same performance over a hardened massive MIMO channel and 2) when the higher amplifier power efficiency of low-PAR precoding is taken into account, conventional and low-PAR precoders lead to approximately the same power consumption. Since downlink signals with low PAR allow for simpler and cheaper hardware, than signals with high PAR, therefore, the results suggest that low-PAR precoding with either single-carrier or OFDM transmission should be used in a massive MIMO base station.

This paper studies the performance of hybrid radio-frequency (RF) and free-space optical (FSO) links assuming perfect channel state information (CSI) at the receiver. Considering the cases with and without hybrid automatic repeat request (HARQ), we derive closed-form expressions for the message decoding probabilities as well as the throughput and the outage probability of the RF-FSO setups. We also evaluate the effect of adaptive power allocation and different channel conditions on the throughput and the outage probability. The results show the efficiency of the RF-FSO links in different conditions.

In this paper, a receiver algorithm consisting of differential transmission and a two-stage detection for a single-input multiple-output (SIMO) phase-noise channels is studied. Specifically, the phases of the QAM modulated data symbols are manipulated before transmission in order to make them more immune to the random rotational effects of phase noise. At the receiver, a two-stage detector is implemented, which first detects the amplitude of the transmitted symbols from a nonlinear combination of the received signal amplitudes. Then in the second stage, the detector performs phase detection. The studied signaling method does not require transmission of any known symbols that act as pilots. Furthermore, no phase noise estimator (or a tracker) is needed at the receiver to compensate the effect of phase noise. This considerably reduces the complexity of the receiver structure. Moreover, it is observed that the studied algorithm can be used for the setups where a common local oscillator or separate independent oscillators drive the radio-frequency circuitries connected to each antenna. Due to the differential encoding/decoding of the phase, weighted averaging can be employed at a multi- antenna receiver, allowing for phase noise suppression to leverage the large number of antennas. Hence, we observe that the performance improves by increasing the number of antennas, especially in the separate oscillator case. Further increasing the number of receive antennas results in a performance error floor, which is a function of the quality of the oscillator at the transmitter.

This paper studies the performance of the hybrid radio-frequency (RF) and free-space optical (FSO) links assuming perfect channel state information (CSI) at the receiver. Considering the cases with and without hybrid automatic repeat request (HARQ), we derive closed-form expressions for the message decoding probabilities as well as the throughput and the outage probability of the RF- FSO setups. We also evaluate the effect of different channel conditions on the throughput and the outage probability. The results show the efficiency of the RF-FSO links in different conditions.

This paper presents channel measurements and preliminary analyses from three 2x2 microwave Line-of-Sight Multi-Input Multi-Output (LOS-MIMO) outdoor test links, operating on 8 GHz and 32 GHz. The main focus is to study channel conditions and the effects of rain and clear-air fading. First, we address the diverse performance measures used in the trials. In particular we introduce the MIMO phase difference as an additional channel metric to the received power. The MIMO phase difference is mainly determined by antenna positions, ground effects and atmospheric variations. The relation between antenna positions and channel conditions was addressed in a number of earlier works, while the atmospheric impact and the resulting link availability are rarely studied. Second, we present the preliminary results from the long-term measurement campaign. The long-term statistics of channel condition from the three links show stable performance. Analysis reveals that fluctuation of the phase difference and the channel condition number is likely due to abnormal atmospheric propagation which can be modelled using a two-ray reflection model. Meanwhile, rain attenuation is strongly correlated between MIMO sub-channels and its contribution to the long-term statistics of power loss is very close to the Single-Input Single-Output (SISO) case.

In multiple antenna systems, phase noise due to instabilities of the radio-frequency (RF) oscillators, acts differently depending on whether the RF circuitries connected to each antenna are driven by separate (independent) local oscillators (SLO) or by a common local oscillator (CLO). In this paper, we investigate the high-SNR capacity of single-input multiple-output (SIMO) and multiple-output single-input (MISO) phase-noise channels for both the CLO and the SLO configurations. Our results show that the first-order term in the high-SNR capacity expansion is the same for all scenarios (SIMO/MISO and SLO/CLO), and equal to 0.5 ln(ρ), where ρ stands for the SNR. On the contrary, the second-order term, which we refer to as phase-noise number, turns out to be scenario-dependent. For the SIMO case, the SLO configuration provides a diversity gain, resulting in a larger phase-noise number than for the CLO configuration. For the case of Wiener phase noise, a diversity gain of at least 0.5 ln(M) can be achieved, where M is the number of receive antennas. For the MISO, the CLO configuration yields a higher phase-noise number than the SLO configuration. This is because with the CLO configuration one can obtain a coherent-combining gain through maximum ratio transmission (a.k.a. conjugate beamforming). This gain is unattainable with the SLO configuration.

This paper considers the downlink of a heterogeneous network, where multiple base stations (BSs) can serve the users by non-coherent multiflow beamforming. We assume imperfect channel state information at both BSs and users. The objective is to jointly optimize the precoding, load balancing, and BS operation mode (active or sleep) for improving the energy efficiency of the network. The considered problem is to minimize the weighted total power consumption (both circuit power and dynamic transmit power), while satisfying per-user quality of service constraints and per-BS transmit power constraints. This problem is non-convex, but we prove that for each combination of BS modes, the considered problem has a hidden convexity structure. Thus, the global optimal solution is obtained by an exhaustive search over all possible BS mode combinations. Furthermore, by iterative convex approximations of the non-convex power consumption functions, a heuristic algorithm is proposed to obtain a local optimal solution with low complexity. Simulation results illustrate that our proposed algorithms significantly reduce the total power consumption, compared to the scheme where all BSs are continuously active. This implies that putting a BS into sleep mode by proper load balancing is an important solution for energy savings in heterogeneous networks.

In multiple antenna systems, phase noise due to instabilities of the radio-frequency (RF) oscillators, acts differently depending on whether the RF circuitries connected to each antenna are driven by separate (independent) local oscillators (SLO) or by a common local oscillator (CLO). In this paper, we investigate the high-SNR capacity of single-input multiple-output (SIMO) and multiple-output single-input (MISO) phase-noise channels for both the CLO and the SLO configurations. Our results show that the first-order term in the high-SNR capacity expansion is the same for all scenarios (SIMO/MISO and SLO/CLO), and equal to 0.5 ln(p), where p stands for the SNR. On the contrary, the second-order term, which we refer to as phase-noise number, turns out to be scenario-dependent. For the SIMO case, the SLO configuration provides a diversity gain, resulting in a larger phase-noise number than for the CLO configuration. For the case of Wiener phase noise, a diversity gain of at least 0.5 ln(M) can be achieved, where M is the number of receive antennas. For the MISO, the CLO configuration yields a higher phase-noise number than the SLO configuration. This is because with the CLO configuration one can obtain a coherent-combining gain through maximum ratio transmission (a.k.a. conjugate beamforming). This gain is unattainable with the SLO configuration.

In this paper, the capacity of the additive white Gaussian noise (AWGN) channel, affected by time-varying Wiener phase noise is investigated. Tight upper and lower bounds on the capacity of this channel are developed. The upper bound is obtained by using the duality approach, and by considering a specific distribution over the output of the channel. In order to lower-bound the capacity, first a family of capacity-achieving input distributions is found by solving a functional optimization of the channel mutual information. Then, lower bounds on the capacity are obtained by drawing samples from the proposed distributions through Monte Carlo simulations. The proposed capacity-achieving input distributions are circularly symmetric, non-Gaussian, and the input amplitudes are correlated over time. The evaluated capacity bounds are tight for a wide range of signal-to-noise-ratio (SNR) values, and thus they can be used to quantify the capacity. Specifically, the bounds follow the well-known AWGN capacity curve at low SNR, while at high SNR, they coincide with the high-SNR capacity result available in the literature for the phase-noise channel.

This paper studies the problem of feedback resource allocation in multiple-input-single-output (MISO) channels utilizing partial channel state information (CSI) feedback. Considering low/moderate signal-to-noise ratios (SNRs), the optimal quantizers and the feedback bit allocation maximizing the throughput are obtained in the asymptotic case where the number of feedback bits increases. Moreover, the results are utilized to derive the optimal retransmission rates in the automatic repeat request (ARQ) protocols and joint CSI-ARQ schemes are proposed for the MISO setups. We show that uniform channel amplitude quantization is asymptotically optimal in terms of throughput. Also, the optimal retransmission rates of the incremental redundancy (INR) ARQ protocols follow an arithmetic progression in the exponential domain. Under certain conditions, a MISO system using quantized CSI can be mapped to a MISO or a SISO (S: single) setup using ARQ or joint CSI-ARQ feedback in the sense that they lead to the same throughput. Finally, to maximize the throughput, the optimal number of channel direction quantization bits should be (M-1) times the number of amplitude quantization bits, where M is the number of transmit antennas.

This paper considers a downlink heterogeneous network, where different types of multiantenna base stations (BSs) communicate with a number of single-antenna users. Multiple BSs can serve the users by spatial multiflow transmission techniques. Assuming imperfect channel state information at both BSs and users, the precoding, load balancing, and BS operation mode are jointly optimized for improving the network energy efficiency. We minimize the weighted total power consumption while satisfying quality-of-service constraints at the users. This problem is nonconvex, but we prove that for each BS mode combination, the considered problem has a hidden convexity structure. Thus, the optimal solution is obtained by an exhaustive search over all possible BS mode combinations. Furthermore, by iterative convex approximations of the nonconvex objective function, a heuristic algorithm is proposed to obtain a suboptimal solution of low complexity. We show that although multicell joint transmission is allowed, in most cases, it is optimal for each user to be served by a single BS. The optimal BS association condition is parameterized, which reveals how it is impacted by different system parameters. Simulation results indicate that putting a BS into sleep mode by proper load balancing is an important solution for energy savings.

This paper studies the energy-limited performance of multi-relay networks. Taking the properties of the power amplifiers (PAs) into account, we derive closed-form expressions for the optimal power allocation, the outage probability and the throughput in the cases with a sum consumed energy constraint. Moreover, we analyze the diversity and the multiplexing gains of the PA-aware systems. Finally, we investigate the performance of large-scale multi-relay networks and develop efficient multi-relay systems with low cooperation overhead. The numerical and the analytical results show that the inefficiency of the PAs affects the outage probability and the throughput of the multi-relay systems substantially.

In this semi-tutorial paper, we derive the general form of a predistorter for a concurrent multiband system. Further, we derive complexity-reduced forms, and we compare the resulting algorithms with previously proposed algorithms in the literature.

Recently, substantial attention has been paid to improve the spectral efficiency of communication setups using different spectrum sharing techniques. This paper studies the throughput of spectrum sharing channels utilizing hybrid automatic repeat request (HARQ) protocols. Considering different HARQ schemes, the unlicensed user throughput is obtained under an outage probability constraint for the licensed user. The outage-limited throughput is obtained for both independent and spatially-correlated fading conditions, where there is spatial dependency between the fading coefficients. The results show that, using HARQ and adaptive power allocation, the maximum throughput is achieved by combination of simultaneous transmission and interference-avoiding spectrum sharing paradigms. The performance of the spectrum sharing networks is not sensitive to spatial correlation, within the practical range, and the throughput changes are negligible at low/moderate correlations. Finally, there is considerable potential for data transmission of the unlicensed user with limited performance degradation of the licensed user.

This paper investigates the performance of multiple-input-multiple-output (MIMO) systems in the presence of automatic repeat request (ARQ) feedback. We show that, for a large range of performance metrics, the data transmission efficiency of the ARQ schemes is determined by a set of parameters which are scheme-dependent and not metric-dependent. Then, the results are used to study different aspects of MIMO-ARQ such as the effect of nonlinear power amplifiers, large-scale MIMO-ARQ, adaptive power allocation and different data communication models. The results, which are valid for various forward and feedback channel models, show the efficiency of the MIMO-ARQ techniques in different conditions.

We investigate multiple-input single-output channel capacity taking dissipation in the power amplifiers into account. We consider the case of a fixed channel with full channel state information (CSI) at both the transmitter and receiver. The capacity expression is given on closed form, and we show that the optimal solution is antenna selection. An algorithm for finding minimum consumed power for any given mutual information is further developed, and we show that the power-mutual information pair is capacity-achieving. We also investigate the ergodic Rayleigh fading channel with full CSI at the receiver and no instantaneous CSI at the transmitter. We devise a numerical approach which finds the global optimum given a quantization of the space of possible allocated powers. We further show that down to the simulation precision, the ergodic Rayleigh fading solution again is antenna selection. It is shown that the allocation algorithms have low computational complexity and give significant rate and total consumed power gains in comparison to previous state of the art.

In this paper, we study the problem of oscillator phase noise (PN) estimation in coordinated multi-point (CoMP) transmission systems. Specifically, we investigate the effect of phase synchronization between coordinated base stations (BSs) on PN estimation at the user receiver. In this respect, the Bayesian Cramér-Rao bound for PN estimation is derived which is a function of the level of phase synchronization between the coordinated BSs. Results show that quality of BS synchronization has a significant effect on the PN estimation.

We study the power allocation problem for the downlink of a cooperative system with different node activeness, i.e., each receiving node requests for data transmission according to a certain probability. Data symbols of the active nodes are jointly transmitted from cooperative transmission points using zero-forcing precoding. The problem is cast in form of maximizing the ergodic achievable rate subject to per-transmit-point average total power constraints. The derived power allocation indicates that depending on the channel conditions and receiving nodes' activation probability, the optimal solution takes the form of either greedy power allocation or power sharing allocation.

In this paper, we address the problem of optimizing signal constellations for strong phase noise. The problem is investigated by considering three optimization formulations, which provide an analytical framework for constellation design. In the first formulation, we seek to design constellations that minimize the symbol error probability (SEP) for an approximate ML detector in the presence of phase noise. In the second formulation, we optimize constellations in terms of mutual information (MI) for the effective discrete channel consisting of phase noise, additive white Gaussian noise, and the approximate ML detector. To this end, we derive the MI of this discrete channel. Finally, we optimize constellations in terms of the MI for the phase noise channel. We give two analytical characterizations of the MI of this channel, which are shown to be accurate for a wide range of signal-to-noise ratios and phase noise variances. For each formulation, we present a detailed analysis of the optimal constellations and their performance in the presence of strong phase noise. We show that the optimal constellations significantly outperform conventional constellations and those proposed in the literature in terms of SEP, error floors, and MI.

In this paper, we address the classical problem of maximum-likelihood (ML) detection of data in the presence of random phase noise. We consider a system, where the random phase noise affecting the received signal is first compensated by a tracker/estimator. Then the phase error and its statistics are used for deriving the ML detector. Specifically, we derive an ML detector based on a Gaussian assumption for the phase error probability density function (PDF). Further without making any assumptions on the phase error PDF, we show that the actual ML detector can be reformulated as a weighted sum of central moments of the phase error PDF. We present a simple approximation of this new ML rule assuming that the phase error distribution is unknown. The ML detectors derived are also the aposteriori probabilities of the transmitted symbols, and are referred to as soft metrics. Then, using the detector developed based on Gaussian phase error assumption, we derive the symbol error probability (SEP) performance and error floor analytically for arbitrary constellations. Finally we compare SEP performance of the various detectors/metrics in this work and those from literature for different signal constellations, phase noise scenarios and SNR values.

This paper studies the problem of feedback subsampling in temporally-correlated wireless networks utilizing quantized channel state information (CSI). Under both peak and average power constraints, the system data transmission efficiency is studied in two scenarios. First, we focus on the case where the codewords span one fading block. In the second scenario, the throughput is determined for piecewise slowly-fading channels where the codewords are so long that a finite number of correlated gain realizations are experienced during each codeword transmission. Considering different temporal correlation conditions in both scenarios, substantial throughput increment is observed with feedback rates well below 1 bit per slot.

This paper addresses the problem of limited CSI feedback in coordinated multi-point (CoMP) networks. Specifically, the system throughput is obtained for block-fading CoMP channels with quantized CSI feedback, and the effect of feedback bit allocation on the system throughput is investigated for different user locations and fading distributions. The analytical and simulation results show that substantial throughput increment is achieved via CoMP joint transmission with very limited number of feedback bits per base station. The effect of optimal bit allocation becomes more important for the user that is located in the CoMP cluster edge areas. Also, the standard Zonal-sampling scheme provides the best bit allocation strategy in many cases, maximizing the system throughput.

In this work, the problem of receiver design for phase noise estimation and data detection in the presence of oscillator phase noise in a point-to-point multiple-input multiple-output (MIMO) system is addressed. First, we discuss some interesting and challenging aspects in receiver design for MIMO systems in the presence of Wiener phase noise. Then, using the variational Bayesian (VB) framework, a joint iterative phase noise estimator and symbol detector are developed based on inverse Gibbs or variational free energy maximization. Further, the symbol error probability (SEP) of the newly proposed iterative scheme is compared with the optimal maximum likelihood (ML) detector with perfect phase information for 16-phase shift keying (PSK) and 16-quadrature amplitude modulation (QAM) schemes.

This paper addresses the problem of optimal power allocation for hybrid automatic repeat request (HARQ) feedback over slowly-fading channels. We mainly focus on the repetition time diversity HARQ scheme where the results are obtained for both continuous and bursting communication models. Moreover, the effect of an outage probability constraint on the system data transmission efficiency is studied under different transmission power constraints. Simulation results show that 1) for Nakagami fading channels, the optimal HARQ-based (re)transmission powers maximizing the system throughput should be decreasing in every (re)transmission round, 2) higher rates are achieved in the continuous communication, when compared with the bursting model, and 3) HARQ feedback leads to considerable performance improvement even in outage-limited conditions.

This study proposes the performance of a scheduling scheme using two-step quantised channel state information (CSI) feedback. Considering fixed and random access networks, the results are obtained under both short- and long-term power constraints and for both single- and multi-layer transmission techniques. Further, the authors evaluate the asymptotic performance of the proposed scheme and show that, while the users scheduling is based on quantised CSI feedback in the first round, the second round of partial CSI feedback can be provided by either channel quantisation or hybrid automatic repeat request feedback, leading to the same forward channel average rate. In comparison with the case of no CSI feedback, the results indicate substantial average rate increment with limited number of feedback bits. Also, the average rate increases via successive partial CSI feedback when compared with one-step CSI feedback schemes.

Recently, substantial attention has been paid to increase the achievable rates of wireless networks using different kinds of limited channel quality information feedback. Hybrid automatic repeat request (ARQ) and quantized channel state information (CSI) feedback are two well-known approaches applied by experts to provide the limited channel quality information at the transmitter. Considering quasi-static fading channels, this paper aims to provide some comparisons between the performance of these methods from different points of view. The paper first investigates the power- and outage-limited performance of hybrid ARQ and quantized CSI schemes under short- and long-term power constraints. Then, 1) the feedback signaling load, 2) robustness and 3) the complexity of these schemes are compared under short-term transmission power constraint. Both INcremental Redundancy (INR) and Repetition Time Diversity (RTD) approaches are considered for hybrid ARQ feedback. Finally, approximate low-complexity solutions are presented for power allocation in the INR ARQ-based scheme under long-term transmission power constraint. Analytical and numerical results demonstrate the equivalency or the superiority of these approaches in different circumstances.

Spectrum sharing networks are communication setups in which unlicensed secondary users are permitted to work within the spectrum resources of primary licensees. Considering quasi-static fading environments, this paper studies the effect of hybrid automatic repeat request (HARQ) feedback on the average rate of unlicensed spectrum sharing channels. The results are obtained for different scenarios; Under both peak and average secondary user transmission power constraints, the channel average rate is determined under primary user limited received interference power conditions when there is perfect information about the interference available at the secondary user transmitter. An approximate solution for power allocation between incremental redundancy (INR) HARQ-based data retransmissions is proposed which can be applied in single-user networks as well. Then, we investigate the effect of imperfect secondary-primary channel state information on the interference-limited average rate of the secondary channel. Finally, we restudy all mentioned scenarios in the case where the data transmission is constrained to have limited outage probability. Substantial performance improvement is observed with even a single HARQ-based retransmission in all simulations.

Spectrum sharing networks are communication setups in which unlicensed secondary users (SUs) are permitted to work within the spectrum resources of licensed primary users (PUs). This paper aims to study the ergodic achievable rates of spectrum sharing networks with finite backlogged primary user and an interference indicator signal. Here, in contrast to the standard interference-avoiding schemes, the secondary user activity is not restricted within the primary user inactive periods. Considering both fading and nonfading channels, the unlicensed user ergodic achievable rate is obtained for different unlicensed user transmission power and licensed user received interference power or signal-to-interference-and-noise (SINR) constraints. In the case of fading channels, the results are obtained for both short- and long-term primary user quality-of-service requirements. Further, the results are generalized to the case of multiple interfering users. In terms of unlicensed user ergodic achievable rate, analytical results indicate that while the standard interference-avoiding approach is the optimal transmission scheme at low secondary user or high primary user transmission powers, higher rates can be achieved via simultaneous transmission at high secondary user SINRs. Moreover, numerical results show that, using an interference indicator signal, there is considerable potential for data transmission of unlicensed users under different licensed users quality-of-service requirements.

Previous results in the literature have shown that derivation of the optimum maximum-likelihood (ML) receiver for symbol-by-symbol (SBS) detection of an uncoded data sequence based on all received signals in the presence of random phase noise is an intractable problem. This is because it involves the computation of the conditional probability distribution function (PDF) of the phase noise process. In this paper, we seek to minimize symbol error probability (SEP), which is achieved by SBS detection of the sequence based on all received signals. We show that the ML detector for this problem can be formulated as a weighted sum of central moments of the conditional PDF of phase noise. Given that the central moments of the conditional PDF of phase noise can be estimated, this new optimal structure is tractable with respect to the previously known optimal ML receiver. Furthermore, based on the new receiver structure, we propose a simple approximate method for SBS detection and investigate its scope and applicability. Simulation results demonstrate that SEP performance close to optimality can be obtained through the proposed method for a wide range of phase noise variances and low signal-to-noise ratio (SNR).

In this paper, we address the problem of designing a joint scheduling and power control algorithm in a downlink coordinated multi-point (CoMP) cluster supporting CoMP joint transmission. The objective is to maximize the cell-edge throughput under per-point power constraints. By an analytical derivation, binary power control is proved to be the optimal solution for any given selected user group. Utilizing this analytical result, a centralized and a semi-distributed version of joint user selection and power control algorithms are proposed. Compared to algorithms without considering joint transmission and algorithms without considering power control, simulation results show that the proposed algorithms achieve a good trade-off between joint transmission and interference coordination, which helps to improve the cell-edge performance.

Recently, substantial attention has been paid to increase the achievable rates of wireless networks using different kinds of limited channel state information (CSI) feedback. This paper aims to investigate the effect of limited noisy CSI feedback on the achievable rates of power-limited block fading channels constrained to have limited outage probability. Considering different power allocation strategies and various fading conditions, the results are obtained for different outage probabilities and are compared with the case where there is no outage limitation. Moreover, considering different outage probability constraints, the effect of feedback channel noise on the average rates of the forward channel is studied and compared with the ones obtained under noise-free feedback link assumption. Simulation results show that 1) although the outage probability constraint reduces the channel average rate, its influence diminishes as the channel state information feedback or the input power increases, 2) the effect of the outage probability constraint decreases as the forward channel fading severity or the feedback channel noise is reduced.

Recently, substantial attention has been paid to compress the channel quality information feedback while preserving most of its relevant information, as required for Adaptive Modulation and Coding (AMC). This paper compares the performance of some lossy feedback compression methods and, particularly, investigate the effect of bit allocation on their performance. Simulation results show that the Discrete Cosine Transform (DCT) approach, along with our proposed bit allocation method, leads to the best feedback compression performance.

Recently, substantial attention has been paid to increase the achievable rates of wireless networks using different kinds of limited channel state information (CSI) feedback. This paper aims to investigate the effect of limited CSI feedback on the achievable rates of power-limited block fading channels constrained to have limited outage probability. Considering different power allocation strategies and various fading conditions, the results are obtained for different outage probabilities and are compared with the case where there is no outage limitation. Simulation results show that 1) although the outage probability constraint reduces the channel average rate, its influence diminishes as the channel state information feedback or the input power increases, 2) the effect of the outage probability constraint decreases as the channel fading severity is reduced.

We have investigated the performance in terms of overall efficiency and maximum output power of a real high power amplifier with various modulated signals, ranging from constant envelope signals to orthogonal frequency division multiplexing based signals having large envelope variations. We show that there are large differences on the overall amplifier efficiency as well as its maximum output power depending on the modulated signal and also on the operation mode. In particular, we show that for high overall efficiency it is important to operate the amplifier close to the maximum output power level as often as possible, and we show that this has consequences for the resource allocation in especially packet based multicarrier systems. We also show that the amplifier performance with various Single-Carrier Frequency Division Multiple Access signals is very similar, and that the peak-to-average-power ratio can be used to predict the overall efficiency for the traditional amplifier drive method. Finally, we show that with advanced, today infeasible, amplifier operation methods the overall amplifier efficiency depends less on the modulation scheme, thus motivating further research in that domain.

This paper presents an iterative interference suppression technique to cancel power amplifier (PA) distortion at the receiver. The focus is mainly on single carrier frequency division multiple access systems, and on removing the distortion created by adjacent users' power amplifier. It is assumed that the receiver has perfect knowledge of all the users' transmitter power amplifier nonlinearities. By relaxing the requirement on PA linearity at the mobile terminals, the PA power efficiency can be improved. The simulations show that by utilizing the successive interference cancelation technique, the require signal to noise ratio required to achieve 10-3symbol error rate is decreased by 3 - 4 dB. By using a clipped communication signal instead of backing off the power in the transmitter PA, we are able to improve the power added efficiency by 8 percentage points.

In this letter, the linear predictability of discrete-time stationary stochastic processes with 1/|f|α-shaped power spectral density (PSD) is considered. In particular, the spectral flatness measure (SFM)-which yields a lower bound for the normalized mean-squared-error (NMSE) of any linear one-step-ahead (OSA) predictor-is obtained analytically as a function of α ∈ [0, 1]. By comparing the SFM bound to the NMSE of thep-tap linear minimum-mean-square error (LMMSE) predictor, it is shown that close to optimal NMSE performance may be achieved for relatively moderate values ofp. The performance of the LMMSE predictor for the discrete-time fractional Gaussian noise (DFGN), which may be viewed as the conventional discrete-time counterpart of continuous-time processes with 1/|f|α-shaped PSD, shows that the DFGN is more easily predicted than the discrete-time processes considered herein.

A recently proposed method for transmission of correlated sources under noise-free conditions, power series quantization (PSQ), uses a separate linear or nonlinear predictor for each quantizer region, and has shown to increase performance compared to several common quantization schemes for sources with memory. In this paper, it is shown how to apply PSQ for transmission of a source with memory over a noisy channel. A channel-optimized PSQ (COPSQ) encoder and codebook optimization algorithms are derived. The suggested scheme is shown to increase performance compared with previous state-of-the- art methods.

We propose a framework for multiple description coding (MDC) of sources with memory. A new source coding method for lossless transmission of correlated sources, power series quantization (PSQ), was recently suggested. PSQ uses a separate linear or non-linear predictor for each quantizer region, and has shown increased performance compared to several common quantization schemes for sources with memory. We propose multiple description PSQ as a special case within our framework. The suggested scheme is shown to increase performance compared with previous state-of-the-art MDC methods.

A Gaussian mixture model (GMM)-based spatio-temporal error concealment approach has recently been proposed for packet video. The method improves peak signal-to-noise ratio (PSNR) compared to several famous error concealment methods, and it is asymptotically optimal when the number of mixture components goes to infinity. There are also drawbacks, however. The estimator has high online computational complexity, which implies that fewer surrounding pixels to the lost area than desired are used for error concealment. Moreover, GMM parameters are estimated without considering maximization of the error concealment PSNR. In this paper, we propose a mixture-based estimator and a least squares approach for solving the spatio-temporal error concealment problem. Compared to the GMM scheme, the new method may base error concealment on more surrounding pixels to the loss, while maintaining low computational complexity, and model parameters are found by an algorithm that increases PSNR in each iteration. The proposed method outperforms the GMM-based scheme in terms of computation-performance tradeoff.

In this paper we propose a method for reducing nonlinearity distortion by limiting the envelope fluctuations of an OFDM signal. The method is based on tone reservation, and the free tones are assigned in a way to limit the variations of the instantaneous power of the time domain signal. The problem is shown to be convex, and by adding an equality constraint, zero constellation error is guaranteed. We present an iterative solution for this problem, and show that the globally optimal point can be approached by only a few iterations. Both in-band and out-of-band distortions are reduced at the expense of a small increase in bandwidth of the signal. The corrected signal is less sensitive to nonlinearities, and therefore the distortion is reduced for all input backoff values.

Orthogonal Frequency Division Multiplexing has become a key element of todays wireless communication systems. However, its sensitivity to oscillator phase noise is responsible for common phase error (CPE) and inter-carrier interference (ICI) which greatly degrades the overall system performance. In this contribution, we address the problem of reducing the effects of phase noise in an OFDM system operating over a frequency selective fading channel. We propose a method for jointly estimating the channel and CPE in a first step and removing ICI in a second step, using a power series expansion of the phase noise process. The algorithm is simulated on both coded and uncoded systems with phase noise over a fading channel.

In this paper, Gaussian mixture modeling is applied to error concealment for block-based packet video. A Gaussian mixture model for video data is obtained offline and is thereafter utilized online in order to restore lost blocks from spatial and temporal surrounding information. We propose estimators on closed form for missing data in the case of varying available neighboring contexts. Our error concealment strategy increases peak signal-to-noise ratio compared to previously proposed schemes. Examples of improved subjective visual quality by means of the proposed method are also supplied.

In speaker recognition applications, speaker identification is the process of automatic recognizing who is speaking based on statistical information obtained from speech signals. Considering the limited number of tests in real situations during the classification phase, it is more useful to have an estimator of the probability of error for speaker recognition systems. In this work, we propose a method based on the log-likelihood of each speaker to estimate the probability of error of a speaker recognition system. We assess the performance of the estimator with experimental trials and compare with the actual number of errors. The results show that the performance of our estimator is comparable to the conventional method. The proposed method presents better reliability and fast convergence compared to the counting case. Indeed, we attain an analytical expression for the probability of error that can be used as a gradient for other optimization methods in speaker recognition applications.

In this paper, a minimum mean square error-optimized mixture-based estimator is used for packet video error concealment. At the same time as on-line computational complexity is reduced, performance in peak signal-to-noise ratio (PSNR) is increased in comparison with a Gaussian mixture-based estimator that obtains its parameters through probability density estimation by means of the expectation maximization algorithm. Moreover, our method increases performance in PSNR compared to several other previous error concealment algorithms.

In this paper, a spatio-temporal Markov random field method is proposed for block-based packet video error concealment. We suggest the combined usage of two estimators, one for lost pixels, and one for lost motion vectors. The estimator for the lost pixel field takes surrounding pixels in the same frame where the loss occurred and motion-compensated pixels from a previous frame based on a motion field estimate into account, while the optimal estimator of the motion field takes surrounding pixels in the same frame where the loss occurred, pixels from a previous frame, and the estimator function for the pixel field into account. Our method increases performance in peak signal-to-noise ratio as well as subjective visual performance compared to several other previous error concealment algorithms.

In this paper we introduce a new method to limit the peak factor of a multicarrier signal based on tone reservation. A peak-reducing signal is computed by clipping the original OFDM symbol. The peak-reducing signal is forced to have the constraints of tone reservation, so that when added to the original signal, the peak factor is reduced without increasing the BER and the out-of-band radiation. The proposed method has low computational complexity requirements and is fast-converging. Moreover, simulation results show that it has higher PAPR-reduction capabilities than other PAPR-reducing methods based on TR in the literature.

For wireless systems with adaptive modulation and/or scheduling, feedback of channel quality information is often necessary. It has been questioned whether the increased system performance is worth the additional feedback rate and the increased algorithm complexity. In this paper, we study how the feedback rate can be minimized, without losing the gains due to adaptive modulation and multiuser diversity. We present an in-depth study of the literature in the area, and evaluate the performance of several state-of-the-art channel quality feedback schemes. By illustrating the compromise between system throughput and feedback channel rate for various schemes, we are able to give valuable insight in choice of method for feedback rate reduction. A major conclusion is that for multicarrier systems, a lossy compression scheme is the best choice, while for single-carrier systems, schemes limiting feedback to only high-SNR users show good performance. Another conclusion is that there are still many issues to study before the schemes can be used in practice.

In this paper, memory-based quantization is studied in detail. We propose a new framework, power series quantization (PSQ), for memory-based quantization. With linear spectral frequency (LSF) quantization as the application, several common memory-based quantization methods (FSVQ, predictive VQ, VPQ, safety-net, etc.) are analyzed and compared with the proposed method, and it is shown that the proposed method performs better than all other tested methods. The proposed PSQ method is fully general, in that it can simulate all other memory-based quantizers if it is allowed unlimited complexity

This paper presents the maximum a posteriori (MAP) detector for a multicarrier system with nonlinearity at the transmitter front-end. The analysis is based on block detection of multicarrier symbols. Since implementation of the MAP detector for a system with a large number of subcarriers is far too complex, a sub-optimum algorithm that can be implemented with acceptable complexity is also presented. It will be shown that when the nonlinearity distortion dominates the channel noise, without knowledge of the nonlinearity, the proposed detector outperforms the conventional ML detector.

We have developed a Gaussian mixture model-based technique for the compensation of lost pixel blocks during real time transmission of video. In this paper, we pursue an argument in order to better understand how the Gaussian mixture model-based estimator works. The discussion is supported with subjective evaluations and examples. Naive viewers preferred the result of our proposed technique 72 percent of the time in comparison with the linear minimum mean square error estimator. Our scheme increases performance measured in peak signal-to-noise ratio for all the 11 standard evaluation movie clips that were used

Multiband OFDM (MB-OFDM) has been envisioned for ultrawide-band (UWB) systems. In this paper we discuss the aspects of designing a channel estimator for such a system, using the Saleh-Valenzuela (S-V) channel model specified by the UWB IEEE 802.15.3a standard body. In a first step, the time-frequency correlation properties of the channel are derived based on the S-V model. In a second step we derive an iterative MMSE channel estimation algorithm, adapted for a UWB system using multiband OFDM and a channel code. The algorithm is tested using pilot-based and decision-directed iterative estimation on the four channel models specified by the IEEE 802.15.3a model. The performance of the proposed algorithm is presented with simulation of its bit error rate as well as its estimation error variance and shows a significant improvement compared with previously published UWB channel estimators

In this paper we study some statistical properties of a multicarrier signals using the order statistics. Analytical expressions for the probability density function of different order statistics of a sampled OFDM system is presented. We then find the amount of power which is clipped from each order of the signal when the signal is passed through a clipping nonlinearity. This is used to represent the relevance of peak-to-average power ratio (PAPR) to evaluate the effect of nonlinearity on the performance of a multicarrier system. The agreements between the theoretical results and the simulated ones demonstrate the validity of the analysis. We will also study different metrics for the signal envelope variations in terms of the sensitivity of each metric to amplitude nonlinearities. In the end the performance of an OFDM system with selected mapping based on different metrics is evaluated and compared with each other

A noise-robust pitch synchronous feature extraction algorithm for speaker recognition systems is proposed in this paper. Since the pitch synchronous algorithms utilize pitch information, which is meaningful only for periodic segments, we propose a new scheme to deal with non-periodic ones such as unvoiced and noise-corrupted. The experimental results show that the proposed algorithm outperforms the conventional algorithm us- ing fixed length of analysis window in actual identification tasks even in low SNR noisy environments.

This letter studies feature selection in speaker recognition from an information-theoretic view. We closely tie the performance, in terms of the expected classification error probability, to the mutual information between speaker identity and features. Information theory can then help us to make qualitative statements about feature selection and performance. We study various common features used for speaker recognition, such as mel-warped cepstrum coefficients and various parameterizations of linear prediction coefficients. The theory and experiments give valuable insights in feature selection and performance of speaker-recognition applications.

The paper presents a novel feature extraction method to improve the performance of speaker identification systems. The proposed feature has the form of a typical conventional feature, Mel frequency cepstral coefficients (MFCC), but a flexible segmentation to reduce spectral mismatch between training and testing processes. Specifically, the length and shift size of the analysis frame are determined by a pitch synchronous method, pitch synchronous MFCC (PSMFCC). To verify the performance of the new feature, we measure the cepstral distortion between training and testing and also perform closed set speaker identification tests. With text-independent and text-dependent experiments, the proposed algorithm provides 44.3% and 26.7% relative improvement, respectively.

In this paper we investigate split quantization of the LSF source from an information theoretic perspective. It is a well known fact that split quantization is inferior to unconstrained quantization, due to the independent treatment of sub vectors. Here, we quantify lower bounds for the split loss, and suggest conditional quantization of splits as a method to reduce the losses. The investigation is based on information theoretic estimates of performance, rather than on the performance of actual quantization schemes. Simulations for a 10-dimensional LSF source point at a loss of around 8 bits if scalar quantization is performed, and a loss of approximately 2 bits for a 2-split quantization, both compared to 10 dimensional vector quantization. Furthermore, the results suggest that these losses can be considerably reduced using conditional quantization, down to as low as 0 to 2 bits.

We address the subject of reducing the impact of phase noise on a QAM-OFDM system transmitting over an AWGN channel. Phase noise is known to have two effects on OFDM systems, rotating each symbol by a different common phase rotation (CPR) and producing an intercarrier interference term (ICI) that adds to the channel noise. We present two novel algorithms that remove CPR and reduce the amount of ICI using different approaches to the ICI problem. Their performance in terms of bit error rate (BER) are evaluated by simulation using symbol by symbol or maximum likelihood sequence detection (MLSD). The results show that these algorithms can significantly reduce the BER floor of the system while still maintaining an acceptable throughput.

Many current speech coders use a source-filter model in which the signal is decomposed on a frame-wise basis into an excitation component and a filter component. The filter component is then parameterized and coded by a separate spectrum encoder. The performance of such spectrum encoders is often evaluated in terms of a spectral distortion measure that treats each frame independently. Doing this therefore neglects the time evolution of quantization errors. In this paper, we focus on the time evolution of spectrum vectors in speech spectrum coding. We show that the human auditory system prefers a slowly evolving spectrum quantization noise, resulting in smooth spectrum trajectories. This result is the basis for a new distortion criterion for spectrum coding which introduces interframe memory into the standard spectral distortion measure, thereby having the ability to penalize a poor spectrum evolution. Further, a number of coding schemes for explicit spectrum evolution control are evaluated, and we show gains in the order of 2-4 bits, compared to schemes with no evolution control.

In this semitutorial paper, a comprehensive survey of closest point search methods for lattices without a regular structure is presented. The existing search strategies are described in a unified framework, and differences between them are elucidated. An efficient closest point search algorithm, based on the Schnorr-Euchner (1995) variation of the Pohst (1981) method, is implemented. Given an arbitrary point x /spl isin/ /spl Ropf//sup m/ and a generator matrix for a lattice /spl Lambda/, the algorithm computes the point of /spl Lambda/ that is closest to x. The algorithm is shown to be substantially faster than other known methods, by means of a theoretical comparison with the Kannan (1983, 1987) algorithm and an experimental comparison with the Pohst (1981) algorithm and its variants, such as the Viterbo-Boutros (see ibid. vol.45, p.1639-42, 1999) decoder. Modifications of the algorithm are developed to solve a number of related search problems for lattices, such as finding a shortest vector, determining the kissing number, computing the Voronoi (1908)-relevant vectors, and finding a Korkine-Zolotareff (1873) reduced basis.

We present a novel spectral distortion measure with interframe memory. The memory gives the possibility to take into account the dynamics of the time evolution of the speech spectrum, which has shown to have a significant importance on the perceived speech quality. Memory is introduced by linear filtering of the time evolution of the difference log spectrum. This facilitates smoothing of spectrum with an ability to track quick transitions. Our results point at a substantially improved performance when rapidly evolving spectrum errors are punished in the measure.

In this paper, we generalize the standard blockwise linear predictive (LP) coding by introducing low-pass filtering and downsampling of the LPC vectors at the encoder side, accompanied by interpolation at the decoder. Several concepts in LP coding, such as overlapping frames, interpolation and long analysis frames, can be described in the proposed framework. We also note that the proposed methods are in agreement with previous work on spectral dynamics, which indicates that spectral dynamics is (at least) as important as spectral distortion for speech quality. We have applied the proposed method to low-rate quantization of spectrum parameters. Objective and subjective performance of the new approach is compared to a standard blockwise LP coding, at various rates. We show that both the subjective and objective quality of the new method compare favorably with standard methods. Even at as low rate as 500 bit/s, the proposed method has a good quality.

This paper describes a new pitch quantization method for low bit-rate speech coding systems. The logarithm of the pitch period is quantized in a combination of two uniform quantizers, one working directly on logarithmic pitch values and the other working on the difference between current and previous logarithmic pitch. The best of the two output values is transmitted to the receiver. This scheme can exploit: both redundancy in the signal and properties of the ear to achieve an efficient quantization. Listening tests show that the proposed scheme allows the pitch parameter to be quantized using 4 bits, with no degradation in audible quality.

In linear predictive speech coding algorithms, transmission of linear predictive coding (LPC) parameters-often transformed to the line spectrum frequencies (LSF) representation-consumes a large part of the total bit rate of the coder. Typically, the LSF parameters are highly correlated from one frame to the next, and a considerable reduction in bit rate can be achieved by exploiting this interframe correlation. However, interframe coding leads to error propagation if the channel is noisy, which possibly cancels the achievable gain. In this paper, several algorithms for exploiting interframe correlation of LSF parameters are compared. Especially, performance for transmission over noisy channels is examined, and methods to improve noisy channel performance are proposed. By combining an interframe quantizer and a memoryless "safety-net" quantizer, we demonstrate that the advantages of both quantization strategies can be utilized, and the performance for both noiseless and noisy channels improves. The results indicate that the best interframe method performs as good as a memoryless quantizing scheme, with 4 bits less per frame. Subjective listening tests have been employed that verify the results from the objective measurements.

In an effort to efficiently code the spectral envelope of speech signals for wideband speech coding based on sinusoidal models, a robust computation of the discrete cepstrum coefficients and their quantization is investigated. A parameterization of the spectral envelope has been proposed which is based on discrete cepstral coefficients using regularization techniques. This paper presents an efficient quantization scheme for these coefficients in order to use them in applications like speech coding. We present results which show a 35% reduction in the bit rate when compared to simple scalar quantization. To verify the efficiency of the proposed quantization schemes, informal listening tests were performed in the context of a sinusoidal coder.

A training algorithm for the design of lattices for vector quantization is presented. The algorithm uses a steepest descent method to adjust a generator matrix, in the search for a lattice whose Voronoi regions have minimal normalized second moment. The numerical elements of the found generator matrices are interpreted and translated into exact values. Experiments show that the algorithm is stable, in the sense that several independent runs reach equivalent lattices. The obtained lattices reach as low second moments as the best previously reported lattices, or even lower. Specifically, we report lattices in nine and ten dimensions with normalized second moments of 0.0716 and 0.0708, respectively, and nonlattice tessellations in seven and nine dimensions with 0.0727 and 0.0711, which improves on previously known values. The new nine- and ten-dimensional lattices suggest that Conway and Sloane's (1993) conjecture on the duality between the optimal lattices for packing and quantization might be false. A discussion of the application of lattices in vector quantizer design for various sources, uniform and nonuniform, is included.

This paper addresses the problem of efficient transmission of the LSF parameters in speech coding using vector quantization (VQ). By performing a comparison of several memory VQ methods on the same database, we investigate what gains can be achieved by exploiting interframe correlation. The memory VQ methods studied are finite-state VQ and linear predictive VQ. By combining the memory VQ with a fixed memoryless VQ, called the safety-net, further improvements in performance can be obtained. It is found that memory VQ can improve the performance with 3-5 bits compared to memoryless VQ for error-free transmission. The best method in this study is a safety-net extended predictive VQ. For noisy channels, most memory methods perform worse than memoryless VQ, but the safety-net predictive VQ outperforms memoryless VQ for all tested channel error rates, with 4 bits less.

A procedure is presented where the conventional innovation codebook approach of CELP coding is replaced by an interpolative scheme. A generalized LTP-codebook constitutes the basis for the interpolation. A pre-requisite to efficient interpolation concerns establishing the neighboring vectors of a given LTP entry. We discuss several working approximations for establishing a suitable neighborhood concept. By simulations we have found that the interpolative scheme leads to 17-20 bits for the excitation coding of one block. In addition to this, some 3-4 bits are required for block gain. A standard CELP typically spends 25 bits or more for one block of excitation coding. The subjective quality of our proposed coding scheme compares favorably with standard CELP. In particular, the interpolation improves the pitch-related properties giving a less noisy subjective impression.

An efficient codebook driven voiced excitation coding method producing natural sounding speech is proposed. It can be incorporated as an essential part in a complete speech coder working at low bit rates. The inter-pulse correlation of such a coding scheme is investigated and exploited using linear predictive vector quantization and finite state vector quantization (FSVQ). A new and more robust FSVQ method that is able to more efficiently exploit this correlation is proposed. The new method dynamically combines two memoryless vector quantizers. This dynamic combination method is not restricted to pulse codebooks but can be employed for any coding scheme with inter vector correlation. 1. INTRODUCTION Most modern speech coders are based on the source-filter concept which tries to separate the excitation source waveform from the spectral characteristics of the vocal tract. For voiced speech, the excitation waveform essentially describes the airflow through the vocal folds. For coders op...