In this paper, we focus on a self-organizing horizontal placement problem of unmanned aerial vehicles (UAVs) which offer network coverage to selected user devices (UDs) in large areas. Specifically, we apply a virtual force field (FF) concept to allow a swarm of UAVs to autonomously locate themselves in proximity to UDs. Unlike the previous work on the FF approach for the selected scenario, we address the incomplete connectivity of network nodes in terms of temporal and spatial couplings under the condition where the UD associations need to be prioritized. We propose a layered FF approach that combines two loosely coupled but complementary FFs. These include a remote FF (RFF) built upon outdated network status information of the whole network and a proximate FF (PFF) that relies on the prompt status of a local subset of nodes in proximity to a particular UAV. We also derive balancing conditions for both RFF and PFF that prevent the UAV swarm to escape from the vicinity of prioritized UDs. The simulation results first characterize the ability of the PFF and RFF to approach the prioritized UDs and then demonstrate the potential gain to improve the coverage probability using a layered FF structure.

In this paper, we consider a hybrid user association (HUA) problem for load balancing of multitier cellular networks. The proposed hierarchical HUA approach builds on a combination of decentralized user association (DUA) and auxiliary intervention of a central control unit (CCU). A major challenge with the CCU intervention is the time interval determined by a selected CCU control cycle during which the DUA must accept all users that satisfy the prevailing association criterion while proactively mitigating potential resource depletions. Consequently, the primary focus of this work is on relating the control cycle of the CCU intervention with the incipient resource depletions, according to a maximum allowed resource depletion probability. By uniquely combining a set of mathematical tools from stochastic geometry and queueing theory, we present a novel HUA method which evaluates the association bias values of the DUA according to a CCU-optimized load vector and enables tier-based resource depletion probability provisioning over finite control cycles. The trade-offs between the proposed HUA method and the standard DUA approach are demonstrated via network simulations with flow-level spatiotemporal dynamics.

The paper elaborates on the technological and architectural innovations researched and developed by 5G-PPP Phase 1 projects and covering innovation areas such as 5G system design and evaluation, novel air interfaces, network management and security as well as virtualization and service deployment aspects.

In this paper, we propose a novel cell splitting approach for massive multiple-input multiple-output (MIMO) base stations to improve energy efficiency. The user equipments (UEs) in the cell are divided into two groups based on their distances to the base station. These two UE groups are scheduled at different time slots, which effectively splits a cell into inner and outer cells. The number of transmitting and receiving antennas together with the downlink and uplink transmission powers are adapted according to the number of cell edge and center UEs to maximize energy efficiency. We propose two algorithms to optimize the number of antennas and transmission powers. Cell splitting is able to reach energy efficiency (EE) gain of 11-41 % depending on the UE density when compared to a conventional load-adaptive massive MIMO system. The inevitable loss of cell edge UE rates can be controlled by setting a target UE rate, which also reduces the search space of the optimization algorithm.

In this paper, we propose a novel power amplifier (PA) dimensioning method for massive multiple-input multiple-output (MIMO) systems whose number of transmitting antennas is adapted according to the number of user equipments (UEs) in the cell. The dimensioning method sets the maximum output powers of PAs unequally according to the pre-calculated average per-antenna transmission powers for different number of UEs. This allows PAs to operate at higher efficiency when the average per-antenna transmission powers vary due to the adaptive number of transmitting antennas. The performance of the method is evaluated in the symmetric multi-cellular scenario using a comprehensive power consumption model that considers both base station and UEs. When simple class-B PAs are used at the base station, unequal PA dimensioning reduces the PA power consumption up to 42 % when compared to the conventional equal PA dimensioning. This improves the total system energy efficiency. The benefits of the proposed unequal PA dimensioning are that no prior knowledge of the UE distribution is needed and good performance is achieved for all UE densities.

In this paper, we consider cooperative video transmission approaches to avoid video interruptions in a wireless real-time video streaming system. The target heterogeneous cooperative system consists of a direct link between a source and destination along with a selected number of parallel relay links. The relay link is a combination of a wide-area link and short-range link which operate in different frequency ranges. Previous contributions focus either on noncooperative video streaming systems using buffer preloading or cooperative systems which do not consider network delay jitter and its effect on interrupting video transmission. In our work, the potential gain in decreasing the interruption probability via different cooperative packet allocation protocols is evaluated analytically and with simulations, using appropriate methods from the queueing theory. We provide new insights on how the user heterogeneity in terms of time-varying packet delays influences the possibility to cooperatively solve the user problem arising from frequent video interruptions.

In this paper, we consider a simple queueing theoretic method to predict the video interruption probability for a given video length. Specifically, a mobile user is streaming a video with a limited length and variable bit rate video encoding. The playback interruptions are caused by random packet delays occurring in the wireless link between the source and destination nodes. The dynamics of the playback buffer in the user terminal is modeled as a G/G/1 queue. To evaluate the video interruption probability, a simple asymptotic method has been presented for the case in which the video length approaches infinity. However, in many practical cases, the video length is limited, hindering the usage of the asymptotic method. We obtain a simple and closed-form upper bound for the analysis of the interruption probability that incorporates the effect of finite video lengths with known statistical delay parameters. Furthermore, a useful method is presented to select between the proposed method and the asymptotic method whose relative accuracy changes with the video length and statistical properties of the buffer load size. The accuracy of the proposed analytical method is compared with the existing methods. Finally, we address some practical challenges in buffer dimensioning when the statistical delay parameters are unknown and estimated with a finite number of received packets.

Opportunistic use of the 2.4 GHz industrial, scientific, and medical (ISM) band has recently received a growing interest. Numerous measurement campaigns have been conducted to analyze the spectrum use in the ISM band in several locations. However, the parameter setting in measurements regarding the bandwidth and time resolution has not been analyzed in detail to support opportunistic use in the band. In this paper, measurement analysis with several bandwidths in two different locations is conducted. The study shows that the bandwidth strongly affects the results. However, there is clearly room for opportunistic operation in all the cases. The results also show that the idle times in the ISM band are geometrically distributed when the time resolution of the analysis is 1 second.

In this paper, we propose a modified unitary multiple signal classification (MUSIC) algorithm for a two-port composite right/left handed (CRLH) leaky-wave antenna (LWA). The algorithm requires only real-valued operations to estimate direction of arrival (DoA) of the received signals, which will simplify future hardware implementation. The CRLH LWA consists of a cascade of metamaterial unit cells, periodically modulated using varactor diodes. By changing the voltages across series and shunt varactors, the antenna is able to uniformly steer its radiation pattern. The proposed modified unitary MUSIC algorithm uses both antennas' input ports to estimate the DoA. Existing MUSIC implementations requires eigenvalue decomposition in the complex-valued signal subspace, which results in highly complex hardware implementation. The computational complexity can be reduced using our proposed modified unitary MUSIC algorithm since it transforms the complex-valued covariance matrix of the received signals to a real-valued matrix using unitary transformations. The performance of the algorithm is experimentally demonstrated by using a CRLH LWA within an anechoic chamber facility and the estimated DoA results are in good agreement with the predicted angles.

The probability density function (pdf) of the distance between randomly located user equipment (UE) and its nth closest base station (BS) is studied in this paper. The knowledge of these pdfs is essential in the analysis of cellular distributed multiple-input multiple-output (MIMO) systems where N BSs cooperate in transmission or reception. We show that earlier results on ordered distance distributions in regular point patterns can be applied to the analysis of distributed MIMO systems when the UE distribution is uniform and the BS locations form a regular lattice. We present previously unpublished pdfs of the distance between a cell edge UE, whose distance to the closest BS is at least r, and four closest BSs in the hexagonal cell topology. The pdfs are verified by simulated histograms. As an example on the application of the results, we show how the signal-to-noise ratio (SNR) gain from uplink cooperative reception increases as the transmitting UE moves further from the cell center. The results from this paper can be applied to the analysis of received and transmitted (in case of power adaptive transmission) power in distributed MIMO systems.

The energy efficiency of power-adaptive multipleinput multiple-output (MIMO) diversity methods is studied in this paper. The considered diversity methods are antenna selection (AS), maximum ratio transmission (MRT), and equal gain transmission (EGT) at the transmitter and maximum ratio combining (MRC) at the receiver. The transmitter energy efficiency is evaluated using the average power amplifier (PA) efficiency and the transceiver energy efficiency is evaluated using the bit error rate (BER) as a function of average PA input signal-to-noise ratio (SNR), which is a new metric. With the new metric, the effect of the PA efficiency is taken into account in the performance evaluation. The analytical results are verified by Monte Carlo simulations. It is shown that larger diversity in the spatial or frequency domain improves the average PA efficiency in a system with channel inversion. The BER results show that the performance improvement from channel inversion diminishes due to the nonideal PA efficiency. Even though MRT is the received SNR maximizing transmitter diversity method, EGT requires less PA input energy per bit when a PA with nonideal efficiency is used. These conclusions could not have been reached using the traditional SNR metrics that do not measure the PA input energy.

A new coded modulation with a phase shift is proposed. The parity bits decide how to shift the signal constellation point of information bits in the transmitter. In the receiver, the phase shift detector estimates how much the constellation points are shifted and then recovers the parity bit. Based on the recovered parity bit, soft input soft output decoding is carried out. The asymptotic coding gains of the proposed scheme using the (9,8) single parity check code are 3 dB and 0.7 dB when compared with the uncoded BPSK and QPSK, respectively. It is shown with simulations that the proposed scheme using the (9,8) single parity check code has at bit error rate 10−5about 2 dB gain compared with uncoded transmission and 0.5 dB gain compared with the (9,8) conventional single parity check code. In addition, concatenated codes are designed using the proposed coded modulation as the inner code. The concatenated code using the (255,247) Reed-Solomon code as the outer code and the proposed coded modulation as the inner code is designed as an example. It is shown that it has about 2 dB gain at bit error rate 10−5when compared with the conventional (255,247) Reed-Solomon code.

In this paper, we consider multiantenna energy detection (ED) of nonnegative pulse-amplitude-modulated (PAM) symbols suitable for low-power and low-complexity short-range communication radios using a very wide bandwidth or high centre frequency. We present a general condition which leads to the cancellation of the spatial cross products between the distinct PAM space-time coded signals at the output of an ED-based multiantenna diversity decoder. Moreover, it is shown that our existing analysis approach for single antenna ED-PAM systems in very wideband lognormal multipath fading channels can be conveniently extended for fast evaluation of spatial diversity gain and correlation effects between antenna elements in multiantenna ED-PAM systems. The error probability performance is illustrated for the selected system parameters by using the proposed analysis tool. The accuracy of the analysis approach is demonstrated with appropriate simulations.

In this paper, a novel blind decision-directed estimation approach is presented for systems using energy detection of pulse-amplitude-modulated (PAM) signals. The method provides an accurate blind solution for the estimates of the received signal energy and noise power spectral density which are required for the calculation of the symbol decision thresholds. Numerical results demonstrate that the proposed approach is able to outperform an existing nondata-aided solution. Furthermore, already for relatively short observation intervals, the error rate performance of the proposed method is comparable with the performance of a corresponding data-aided threshold estimator which, unlike the proposed blind approach, needs a redundant training signal.

This paper proposes a novel adaptive power control scheme to be used in nonergodic fading channels. We use the decision-theoretic criterion known as Telser's safety-first criterion and variational calculus to construct the adaptive power control scheme that maximizes the average transmission rate subject to the average transmission power constraint and outage probability constraint for a given target transmission rate. We recognize that for a given power budget only some combinations of outage probability and target transmission rate are feasible and derive the boundary of the feasible set of those parameters. Numerical results suggest that some feasible combinations of the constraints are inferior to the other ones. We present a practical way to properly select the superior set of constraints. The proposed scheme is the extension of the traditional scheme which aims only at minimizing the outage probability for a given target transmission rate and average transmission power.

In this paper we study the performance of adaptive transmission methods using the rational decision theory based concept. We introduce a channel model and a diversity model for simulations and develop a method for performance evaluation using the rational decision theory and the developed channel and diversity models. Optimal scheme based on this metric differs from the traditional capacity maximization scheme because the proposed metric takes transmission related risks into account. Several theoretical and practical power control methods are investigated through analysis and simulations. Both single-input single-output (SISO) and diversity channels are considered. The proposed filtered-x least mean square (FxLMS) algorithm outperforms other practical approaches and it can be actually seen as a generalization of practical algorithms.

This paper proposes a autocorrelation-based method to classify traffic patterns of primary channels in cognitive radio systems to allow a more accurate prediction of the future idle times. The classification algorithm uses binary information collected by spectrum sensing. It searches periodicity from the sensed binary pattern using a discrete autocorrelation function. Errors that are caused by noise and possible false sensing reports are filtered away from the autocorrelation function. We tested the method with Pare to, Weibull, and exponentially distributed stochastic traffic, and with deterministic traffic. The proposed method finds the type of traffic with a high probability when the channels of interest include both stochastic and deterministic traffic. Stochastic traffic is always classified right and regarding the deterministic traffic the probability of correct classification is over 95% when the probability of missed detection or probability of false alarms is below 10%.

The application of various probabilistic inequalities in link budget analysis of adaptive transmission systems is considered. In particular, we complement conventional link budget analysis with a new correction term that we call adaptation gain. The adaptation gain describes how the area mean of the received power changes when transmission power control is used. The upper and lower bounds of the adaptation gain are derived using the Holder inequality. Furthermore, using the one-sided Chebyshev inequality, we determine general upper and lower bounds of the fade margin using only the first and second order moments of the received power. Numerical results suggest that the adaptation gain, when expressed in decibels, can be either positive or negative with an absolute value of several decibels. A similar effect is observed also for the required fade margin. These observations bring new insights into the link budget analysis of adaptive links.

The proposed method classifies traffic patterns of primary channels in cognitive radio systems and applies different prediction rules to different types of traffic. This allows a more accurate prediction of the idle times of primary channels. An intelligent channel selection scheme then uses the prediction results to find the channels with the longest idle times for secondary use. We tested the method with Pareto and exponentially distributed stochastic traffic and with deterministic traffic. The predictive method using past information improves the throughput of the system compared to a system based on instantaneous idle time information. The classification-based predictive method improves the performance compared to pure prediction when the channels of interest include both stochastic and deterministic traffic. The amount of collisions with a primary user can drop 60% within a given interval compared to a predictive system operating without classification.

We present a study on the effect of power control algorithms on the average efficiency of a power amplifier (PA). The efficiencies are analytically calculated. Several efficiency curves of PAs are considered. The power control algorithms are the water-filling algorithm and the full and truncated channel inversion algorithms. The algorithms have an ideal knowledge of the power gain of the channel. Constant amplitude and also Gaussian distributed data signals simulating orthogonal frequency division multiplexing (OFDM) are used. Several channel models are considered. The analysis is verified via Monte Carlo simulations. We obtain realistic average power amplifier efficiency performance that takes into account the power control algorithm as well as the input signal power distribution, for various types of channels and signals. The study shows that the power control should be reckoned with when investigating the average power amplifier efficiency. Using power control improves the PA average efficiency. The higher the cut-off value, the higher the PA average efficiency, at the expense of the throughput.

In this paper we present an adaptive transmission scheme that leads to a surprising situation in analysis of a mathematical model of wireless communications. Namely, the average received energy tends to infinity despite the fact that the average transmitted energy and the representative energy gain of the channel are finite. Yet, it is reasonable to postulate that such a scheme should not be used in any practical wireless system. This anomaly is commonly referred to as St. Petersburg paradox. We discuss possible reasons for the St. Petersburg paradox to occur in analysis of wireless systems and how it can be resolved using suitable performance metrics and fading models. For example, the paradox is resolved by optimizing some performance metric which is either bounded or concave function of the received signal-to-noise ratio. The analysis of St. Petersburg paradox brings new intuition to the normalization of fading channels and optimization of wireless systems.

Noncoherent multilevel systems have been typically analyzed with spectrally inefficient orthogonal modulation methods. In this paper, we present a novel error probability analysis of energy detected (ED) signals with spectrally efficient multilevel pulse amplitude modulation (PAM). One of the main challenges in the analysis of ED systems with the multilevel PAM is to find analytical methods to evaluate and optimize the performance of ED systems with respect to arbitrary system parameters, e.g., decision thresholds for chi-squared-distributed decision variables, integration time, bandwidth, and number of modulation levels. We propose analytically tractable methods that can be efficiently used to design spectrally efficient ED systems for short-range, wideband, and high data rate wireless communications in lognormal multipath fading channels with uncorrelated diversity paths.

Antenna array beamforming reduces multipath fading components, and decreases the complexity of equalizer in a single carrier receiver. Nonlinear analog parts cause, however, impairments in the beamforming. In this paper we show that when the separate antenna elements include nonlinear amplifiers with different amplitude modulation to amplitude modulation (AM-AM) and amplitude modulation to phase modulation (AM- PM) conversions, there are errors in the level of main beam and in the direction of the main beam, respectively. There are no impairments in the beamforming if there is phase noise at the input of the antenna array. Anyhow, the phase noise may dramatically distort the signal constellation. A common method to avoid nonlinear distortions is to use modulation which has constant envelope. This is not enough if the nonlinear amplifier has memory.

This paper introduces a novel concept of efficient power control in nonergodic fading channels. We use the risk-reward approach to quantitatively describe the performance of power control schemes. A power control scheme is said to be efficient if it minimizes the risk for a given level of reward. The reward and risk are measured, respectively, as the expected value of the link spectral efficiency in excess of some predefined target value and the below-target semideviation of the link spectral efficiency distribution. Furthermore, we introduce a novel fundamental limit on the performance of adaptive power control schemes. The new fundamental limit, which we call the efficient frontier, is the set of all efficient power control schemes. We analytically derive the adaptive power control rule that achieves the fundamental limit. We show that no power control scheme can be constructed with the performance above the efficient frontier. The numerical results suggest that various state-of-the-art power control schemes are suboptimal, i.e., their risk-reward performance is below the efficient frontier.

This paper introduces a novel quantitative framework for measuring the risk and the reward provided by adaptive transmission schemes. In particular, the reward is measured as the expected value of the link spectral efficiency in excess of some predefined threshold. The risk, on the other hand, is the nth root of the nth order lower partial moment of the link spectral efficiency distribution. We apply mathematical tools of finance theory to analyze the risk-reward performance of various state-of-the-art adaptive transmission schemes in generic multi- antenna channels. We identify the maximum-return, minimum- risk, efficient, and optimal risk-reward schemes. The numerical results suggest that in a general case the optimal risk-reward scheme is neither the scheme that maximizes the expected link spectral efficiency nor the scheme that minimizes the risk by minimizing, e.g., the outage probability. The financial risk-reward theory brings a new intuition to the understanding of adaptive transmission in nonergodic channels.

A nonideal radio transmitter both distorts the desired signal and generates spectral regrowth causing interference to adjacent channels. Predistortion techniques can be used to minimize these effects. The joint effect of different types of nonidealities is not straightforward to analyze and has not yet been studied in detail in the literature. In this paper, we demonstrate how to adaptively predistort a nonlinear high power amplifier and an I/Q modulator, and to compensate the frequency response of a radio frequency filter. The study considers the spatial order of adaptive predistorters and the temporal sequence of adaptation steps. In this way, both the system capacity and the power efficiency are improved.

We propose a new training sequence and integer frequency offset estimation algorithm using the characteristics of chirp training signals. We also propose modifications of known fractional frequency offset estimation algorithm and timing synchronization algorithm. The training sequence is composed of one up and two down chirp symbols, also known as Newman phases. The integer frequency offset estimation algorithm uses the effect of timing and frequency offsets on the matched filter outputs of the chirp signals. Autocorrelation and reversed autocorrelation are used to acquire the timing instant and the fractional frequency offset. We present the whole timing and frequency synchronization procedure and its performance via Monte Carlo simulations in multipath channels. Our procedure shows better performances compared to previously published algorithms.

In this paper we study the normalization of mathematical models of linear vector channels. The ratio of the received energy to the transmitted energy is the energy gain of the channel. All physical systems follow an energy conservation law which implies that the energy gain of the channel is less than or equal to one. The major approaches for normalization include setting of either the average energy gain or the peak energy gain to unity. The peak energy gain of many mathematical fading models is infinite and those models cannot be normalized by the peak energy gain. We propose a new approach to normalization where the mathematical channel model is guaranteed to represent a physical system with a predefined probability. We show that the proper normalization of the mathematical model and the selection of the correct performance measure are of paramount importance in comparative performance analysis of adaptive transmission systems.

In this paper, a new aspect on the problem of carrier frequency offset (CFO) estimation is studied in a frequency-hopping (FH) orthogonal frequency division multiplexing (OFDM) system. Unlike in a traditional nonhopped OFDM system, in FH-OFDM system it is important to verify how accurately frequency-switching must be performed before the CFO estimation can take place with adequate performance. The accuracy of frequency-switching is evaluated through frequency-hopping timing offset (FHO) and frequency-hopping phase offset (PHO) between the received signal and the signal produced by the local frequency-hopping synthesizer of the receiver. The target system uses ultra-wideband (UWB) in order to achieve very high data rate of 1.6 Gbit/s. The performance of selected autocorrelation based algorithms is simulated in multipath fading channel under the FHO and PHO, and the results are compared to the performance of ideal frequency-switching and the corresponding analytical Cramer-Rao bound. It is found that the CFO estimators based on autocorrelation principle are quite robust to the FHO less than half the hopping period. Furthermore, simple methods are proposed to compensate the degradation caused by the FHO. The estimators are, however, sensitive to the PHO caused by the possible lack of phase memory in the frequency-hopping synthesizer resulting in a significant bias to the CFO estimate.

In this paper, a novel adaptive inverse power control method that is based on the filtered-x LMS (FxLMS) algorithm is introduced. Inverse power control minimizes the interference that a cognitive radio creates to licensed users and allows more users to share the spectrum. It is also needed in multi-access systems like code division multiple access (CDMA) to alleviate the near-far problem. The proposed variable step algorithm adjusts the step size in a nearly optimal way. Based on numerical analysis this new method clearly improves system performance compared to the algorithm where the well-known fixed or variable step adjustment power control is used. A normalized version of the FxLMS algorithm is needed in a fading channel. In a slowly fading channel (e.g., normalized Doppler frequency of 0.001) the FxLMS power control can keep the received signal-to-noise ratio (SNR) in the desired level with a good accuracy most of the time. The standard deviation of the received SNR is 1.92 dB when the received SNR is kept at 10 dB. The results with almost all different SNR values are better than the other methods can achieve.

Clock-gating has been employed in low-power FPGA designs based on an emulated and compromised method. So far in literature the actual efficiency of savings in power consumption is not thoroughly studied for this method. In this paper we evaluated the clock-gating technique in FPGAs, based on a novel and comparative process. For a set of design cases, both the FPGA and ASIC clock-gating methods were implemented. Figures of power consumption were obtained using the corresponding FPGA/ASIC power estimation tools and devices. The results show that in FPGAs, the efficiency of savings in dynamic power consumption is about 50% to 80% of its ASIC counterparts. However, we also found that compared to ASICs, clock-gating for FPGAs in terms of the efficiency of savings in total average power consumption was only about 6% to 30% of its ASIC counterparts due to FPGA’s large static power consumption.

In this paper we discuss the proper normalization of a fading channel model. Physically, radio channels correspond to passive circuits and follow the energy conservation law. The ratio of the received energy to the transmitted energy is the energy gain of the channel. The representative energy gain is defined as the average energy gain for a signal that is uniformly distributed in time, frequency and space. The major approaches for normalization include setting of either the average representative energy gain or the peak energy gain to unity. The peak energy gain of many fading models including Rayleigh fading is infinite, which is obviously impossible in a passive system where the peak energy gain should be less than or equal to unity. Our aim is to show that it is due to the normalization that in some cases the performance in a fading channel is better than in a nonfading channel.

Energy is a basic resource in digital transmission links. Physically, radio channels correspond to passive circuits and most of the transmitted energy is lost in the channel. Two alternative approaches are used for performance measurements in terms of energy. Either the average transmitted or received energy per bit is used, both usually normalized by the receiver noise spectral density. This leads to the average transmitted or received signal-to-noise ratio (SNR) per bit, respectively. However, the transmitted energy is the basic system resource. The average energy gain of a channel depends on the transmitted signal. For convenience, the transmitted SNR referred to the receiver is defined to be the product of the transmitted SNR and the representative energy gain, which is defined as the average energy gain of a signal that is uniformly distributed in all dimensions: time, frequency and space. An explicit relationship between the transmitted and received SNR's using the covariance concept is derived. Limitations of the use of different SNR definitions are summarized

We propose a new time-domain simultaneous fractional frequency and sampling offsets estimation algorithm using the characteristics of down-sampled chirp training signals. The training sequence is composed of one up and one down chirp symbols. We also propose a new estimation algorithm to estimate the integer timing and frequency offsets in the time domain. The algorithms use the outputs of matched filters and autocorrelators. We present Monte Carlo simulations results in AWGN channels and show the good performance of our algorithm, especially for the integer timing; and frequency estimates compared to known methods. Indeed, we obtain perfect results for SNR of 5 dB and higher and normalized frequency offset smaller than 10, when no fractional offsets are present. The fractional timing and frequency estimator does not perform as well as known methods, but is much simpler to implement.

The phase ambiguity problem in detecting phase modulated signals transmitted over a time-variant frequency-nonselective Rayleigh fading channel is addressed. A unified way for signal detection in an unknown channel based on the noncoherent estimator-correlator receiver is presented. We explain how this receiver can be used in conjunction with linear modulations. We provide a method for estimating the required number of pilot symbols and the need for tracking.

Pilot-symbol-assisted modulation system using feedback minimum mean-square error (MMSE) power control in subject to an unavoidable feedback delay, and in conjunction with diversity, is considered over a slow Rayleigh fading channel. Feedback MMSE power control is defined as a power-control function, with feedback MMSE predictions of the current channel fading gains as input that minimizes the system-error probability. The use of feedback requires causality, and an MMSE predictor has to be employed for the purpose of power control. Previously, in the literature, the predictor was used also in detection. The pilot-symbol system with MMSE power control is shown to achieve a clear performance improvement by employing a smoother, instead of the predictor, in detection. Furthermore, the performance loss caused by a feedback delay of 10%-20% from the channel coherence time appeared to be minor with reasonable bit-error rate levels. Finally, additional performance improvement using low-order diversity was shown to be considerable.

Accurate channel estimates are needed in space-time coded OFDM systems for decoding purposes. In this paper, a novel channel tracking algorithm based on space-time coded training and information symbols is presented. The algorithm takes advantage of the orthogonality properties of the space-time block codes and it is therefore capable of providing channel estimates without performance degradation due to estimation errors from adjacent channels. The algorithm is tested via Monte Carlo computer simulations using both slowly Rayleigh fading channels and time-invariant frequency selective channels and Alamouti space-time block coding. Computer simulations also show that this simple algorithm outperforms LMS-based approach without additional complexity.

An adaptive reduced-state sequence estimation (RSSE) receiver based on per-survivor processing (PS) in conjunction with a local decision feedback equalizer (DFE) for the EDGE system with 8PSK modulation is proposed in this paper. A pre-filter prior to the RSSE-PSP is exploited to reshape the channel impulse response (CIR) to have approximately a minimum phase property. The pre-filter settings are computed indirectly by estimating the CIR from the midamble with the least squares algorithm and then applying the minimum-mean square error (MMSE) criterion to reshape the estimated CIR. The proposed scheme handles the first part of the sampled CIR by the RSSE-PSP and the rest by the local DFE, which utilizes the decision per survivor mechanism for reducing the error propagation and complexity reduction. A good trade-off between the performance and complexity could be achieved by retaining the RSSE-PSP for good performance and local DFE for intersymbol interference cancellation. Computer simulations indicate that the RSSE-PSP with a pre-filter works well in ISI channels with a lower computation burden.

We analyzed the effect of time and frequency domain windowing, or weighting, of the transmitted signal for least squares (LS) and minimum mean-square error (MMSE) estimators when the channel is time-variant. We considered the estimation error for different windows and we found that the windows can be selected independently. We explained the performance of the estimators with the help of the radar ambiguity function of the transmitted signal including the windowing.

A new adaptive reduced-complexity MLSE receiver based on per-survivor processing (PSP-MLSE) and a decision feedback equalizer (DFE) for GSM/EDGE system with 8PSK modulation is proposed. The initial channel impulse response (CIR) is estimated by the LS algorithm with a mid-amble and updated by the LMS algorithm during data transmission. The proposed scheme handles the first part of the sampled CIR by the PSP-MLSE and the rest by the DFE for complexity reduction. Instead of the conventional global DFE (decision per sample), the local DFE (decision per state/survivor) is suggested to reduce error propagation. A good tradeoff between performance and complexity, by retaining the PSP-MLSE for good performance and using the local DFE for intersymbol interference cancellation, is obtained. Computer simulations indicate that the PSP-MLSE with the local DFE is clearly superior to that with the global DFE, especially in severe ISI channels.

In this paper, the problem of carrier phase recovery of linearly modulated signals in the presence of unknown data symbols is studied within the expectation-maximization (EM) framework using two different approaches. First, an iterative joint maximum likelihood (ML) phase estimator and data detector is derived using conditional maximization steps. Secondly, an iterative joint ML nondata-aided (NDA) phase and power spectral density estimator is derived for uncoded and coded transmitted signals. The main difference between the approaches is that the first estimator uses hard decisions whereas the second estimator uses soft decisions about the data symbols at each iteration. Furthermore, the mean-squared performance of the second estimator is approximated by the inverse of the empirical observed Fisher information. Finally, it is shown that the recursive approximations of both estimators lead to the Costas type of loops introduced earlier in the literature.

A pilot symbol assisted modulation system with feedback MMSE power control over a slowly Rayleigh fading channel was previously considered in the literature. The MMSE predictor was used in power control and the MMSE smoother in detection, respectively, to estimate the complex fading gains. In this paper the additional effect of diversity on the system performance is derived. Furthermore, the coded bit error performance for the pilot symbol system using MMSE power control and diversity is arrived at through analytical bounds.

The exact bit error probability of a matched filter receiver in a known discrete Rayleigh fading multipath channel is determined for a binary antipodal system. The matched filter receiver or the RAKE is one form of a diversity receiver. Traditionally, both the interpath interference (IPI) and the intersymbol interference (ISI) caused by the non-ideal autocorrelation function of the bit waveform are neglected in the analysis of the RAKE. Previously, the exact matched filter bounds; which include IPI, were derived. This bound gives the performance of the matched filter if only one symbol is transmitted. In our analysis, a symbol sequence is transmitted instead of only one symbol. Thus, our analysis includes both IPI and ISI as well as the correlation between the paths, The analysis permits direct comparisons between different kinds of bit waveforms.

An adaptive threshold control scheme for packet acquisition is described. The threshold control is done adaptively by setting the threshold proportional to the maximum likelihood estimate of the noise power.

The bit-error probability is determined for a binary antipodal diversity system with an adaptive receiver using decision-directed channel estimation. The diversity channels are assumed to be nonselective Rayleigh-fading channels with additive white Gaussian noise (AWGN). The analysis is valid for all linear estimators which use a finite-impulse-response (FIR)-type estimation filter. Numerical results are presented for a minimum mean-square error (MMSE) filter and a moving average (MA) filter.

The main purpose of this paper is to study the frequency synchronization problem in OFDM systems. A new frequency synchronization method is achieved by means of an all-digital synchronization loop including acquisition and tracking modes. The frequency offset is estimated only once per frame. The acquisition algorithm is based on periodically inserted reference symbols, and the tracking algorithm on the cyclic prefix of the OFDM symbols. The algorithm performance is assessed in an AWGN channel with a low SNR value and in the presence of a timing inaccuracy. The simulations show that the algorithm is accurate and the suggested frequency synchronization scheme works well.

It is already known that the performance of narrowband interference adaptive filtering in DS spread spectrum systems is additionally degraded in the presence of a frequency hopped jamming signal compared to the case with CW interference. Even so, the adaptive filter can be rather efficient because during the hopping interval, while the jamming signal parameters are constant, the filter adjusts its weights; and if the hopping rate is not too high, there are time periods when the interfering signal is suppressed. In order to have a better insight into the performance of these systems, we analyze the DS spread spectrum receiver behavior, when the jamming signal frequency is continuously changing (chirp signal). We find that this is a reasonable step for a jammer that is trying to be more efficient. In such a case, a two-sided filter structure shows worse overall performance than a prediction error structure. As the jamming frequency sweeping rate or bandwidth is increased, the system performance is degraded. The analysis provides an insight into how much the system performance will be degraded as a function of the interfering (frequency sweeping) signal parameters.>

The exact matched filter bound for an L-path Rayleigh fading channel is determined. The result is used to study the effect of interpath interference. The numerical analysis shows that the loss in the signal-to-noise ratio due to the interpath interference depends on the selected waveform.>

The effect of channel estimation errors upon the performance of an adaptive rake matched filter in a DS spread-spectrum system is studied in a two-path channel. A moving average filter with a memory of M bit intervals is used in the channel estimation. The estimation errors are mainly caused by channel noise and channel impulse response variations during the observation interval. The performance of the adaptive rake depends strongly on the selection of M. The optimal value of M depends on the signal-to-noise ratio and on the variation rate of the channel.>