The use of non-orthogonal signals has several benefits over orthogonal signals in multi-coded communications. We provide a novel, theoretical study of non-orthogonal signaling to expand the applicability of these schemes. Motivated by a class of multi-carrier spread spectrum systems, this paper presents a thorough symbol error rate analysis of the broad class of multi-code signaling methods when they make use of codes which are not necessarily orthogonal. Our analysis is also extended to the case where the code set includes the negative of each code vector, i.e., an extension to biorthogonal signaling. Moreover, it is shown that the symbol error rate results derived in this paper reduce to those available in the literature when the multi-codes are orthogonal or have equal correlation between vectors. Additionally, we show how Monte Carlo integration can be used to evaluate the integrals in the error probability calculation and derive low complexity upper bounds on the error probabilities. We show that by combining these techniques, the error probability can be efficiently computed across the full SNR regime. Finally, we use the upper bound of the error probability to develop some analytical insights about the impacts of non-orthogonality among the code vectors on the symbol error probability.

In this paper, a practical precoding method for the downlink of filter bank multicarrier-based (FBMC-based) massive multiple-input multiple-output (MIMO) is developed. The proposed method includes a two-stage precoder consisting of a fractionally spaced prefilter (FSP) per subcarrier for flattening/equalizing the channel across the subcarrier band, followed by a conventional precoder whose goal is to concentrate the signals of different users at their spatial locations. This way, each user receives only the intended information. In this paper, we take note that channel reciprocity may not hold perfectly in practical scenarios due to the mismatch of radio chains in uplink and downlink. Additionally, channel state information (CSI) at the base station may not be perfectly known. This, together with imperfect channel reciprocity can lead to detrimental effects on the downlink precoder performance. We theoretically analyze the performance of the proposed precoder in the presence of imperfect CSI and channel reciprocity calibration errors. This leads to an effective method for compensating these effects. Finally, we numerically evaluate the performance of the proposed precoder. Our results show that the proposed precoder leads to an excellent performance when benchmarked against OFDM.

Resource allocation in orthogonal frequency division multiplexing (OFDM) systems is performed through allocating blocks of subcarriers to each user. Even though OFDM is the primary waveform for 5G NR systems, research reports have noted that single carrier modulation (SCM) offers several advantages over OFDM in massive multiple input multiple output (MIMO) systems, making it a preferred candidate for some future applications such as massive machine type communications (mMTC). This paper presents a method for SCM resource allocation and the relevant information recovery algorithms at the receiver. Our emphasis is on cyclic prefixed SCM, where highly flexible and efficient frequency domain detection algorithms enable the operation of many simultaneous users in a massive MIMO uplink scenario. The proposed resource allocation method allows the number of users to exceed the number of antennas at the base station (BS). Each single carrier transmission is partitioned into L interleaved streams, and each user is allocated a number of such streams. One major benefit of SCM is that each data symbol is spread over the entire bandwidth. As such, the receiver performance is dictated by the average channel gain across the transmission band rather than the channel gain at a given frequency bin or a small group of frequencies. In the proposed setup, each stream may be thought of as a resource block in SCM, analogous to resource blocks in OFDM. Hence, in the context of this paper, the terms resource blocks and streams may be used interchangeably.

Single carrier modulation (SCM) schemes are attractive for uplink (UL) transmissions due to improved power efficiency at the user equipment (UE) transmitter compared with multi-carrier modulation schemes. In a massive MIMO scenario with SCM, the UL detection must mitigate the effects of inter-symbol interference and multi-user interference. This processing is effectively performed in the frequency domain (FD) using a minimum mean squared error (MMSE) detector when the transmission is framed with a cyclic prefix. This paper analyzes an MMSE-based detector compatible with distributed processing in a time-division duplex (TDD) system. The matrix inverses computed for the UL detection are then reused to perform multi-user precoding for the downlink (DL). We find that this scheme yields tremendous savings in computational complexity compared to commonly used zero-forcing (ZF) precoding without sacrificing any performance. Since MMSE processing introduces a bias to the estimates, we derive the scalar coefficients necessary to cancel the MMSE bias. The impact of channel estimation errors is analyzed for both the UL and DL cases in conjunction with a power-efficient approach to SCM channel estimation. Moreover, extensive simulations are performed to confirm our theoretical findings.

By processing in the frequency domain (FD), massive MIMO systems can approach the theoretical per-user capacity using a single carrier modulation (SCM) waveform with a cyclic prefix. Minimum mean squared error (MMSE) detection and zero forcing (ZF) precoding have been shown to effectively cancel multi-user interference while compensating for inter-symbol interference. In this paper, we present a modified downlink precoding approach in the FD based on regularized zero forcing (RZF), which reuses the matrix inverses calculated as part of the FD MMSE uplink detection. By reusing these calculations, the computational complexity of the RZF precoder is drastically lowered, compared to the ZF precoder. Introduction of the regularization in RZF leads to a bias in the detected data symbols at the user terminals. We show this bias can be removed by incorporating a scaling factor at the receiver. Furthermore, it is noted that user powers have to be optimized to strike a balance between noise and interference seen at each user terminal. The resulting performance of the RZF precoder exceeds that of the ZF precoder for low and moderate input signal-to-noise ratio (SNR) conditions, and performance is equal for high input SNR. These results are established and confirmed by analysis and simulation.

Femtocells can dramatically increase the number of users serviced within a traditional 5G NR cell radius. This paper presents a method for adding femtocells as a secondary network operating in the same spectrum as the primary 5G NR network. The secondary network tailors its transmissions to keep the interference to the primary network to a minimal predefined threshold. Multi-antenna femtocell gateways (FGWs) are introduced, which operate simultaneously as standard user equipments on the primary network and as hubs for the femtocells in the secondary network. Since the downlink of the secondary network must operate through interference from the primary network user equipment (UE) transmissions, a spread spectrum waveform is used along with spectral masking at the femtocell terminals (FTs). Simulation results show that the interference at the base station receiver caused by the secondary FGW transmissions can be kept within a manageable level, allowing hundreds of FGWs to operate harmoniously with the primary network through opportunistic use of the spectrum.

Frequency domain (FD) multi-user detection (MUD) has been shown to be an effective means of approaching the theoretical per-user capacity for single carrier modulation (SCM) schemes in massive MIMO scenarios with highly dispersive channels. When a cyclic prefix is added to the SCM waveform, the circulant structures of the resulting convolutional channel matrix allows for relatively simple expressions for the FD detection. In this paper, we develop a computationally efficient minimum mean squared error (MMSE) FD-MUD technique in a time-division duplexing (TDD) massive MIMO setup and show how processing steps can be shared between uplink and downlink.

In this paper, we consider channel estimation problem in the uplink of filter bank multicarrier (FBMC) systems. We propose a pilot structure and a joint multiuser channel estimation method for FBMC. Opposed to the available solutions in the literature, our proposed technique does not rely on the flat-channel condition over each subcarrier band or any requirement for placing guard symbols between different users' pilots. Our proposed pilot structure reduces the training overhead by interleaving the users' pilots in time and frequency. Thus, we can accommodate a larger number of training signals within the same bandwidth and improve the spectral efficiency. Furthermore, this pilot structure inherently leads to a reduced peak-to-average power ratio (PAPR) compared with the solutions that use all the subcarriers for training. We analytically derive the Cramér-Rao lower bound (CRLB) and mean square error (MSE) expressions for our proposed method. We show that these expressions are the same. This confirms the optimality of our proposed method, which is numerically evaluated through simulations. Relying on its improved spectral efficiency, our proposed method can serve a large number of users and relax pilot contamination problem in FBMC-based massive MIMO systems. This is corroborated through simulations in terms of sum-rate performance for both single cell and multicell scenarios.

A hybrid analog/digital signal processor has been proposed to implement energy-efficient multi-input-multi-output (MIMO) detectors. A sub-optimum MIMO detector based on Markov Chain Monte Carlo (MCMC) algorithm for a 4×4 MIMO system is presented. The main part of the required signal processing occurs in analog domain to reduce power consumption. The outputs of the proposed analog processor are converted to digital using a low-resolution analog-to-digital converter (ADC) in order to close the loop in digital domain. The proposed 4×4 MCMC MIMO detector is designed in a conventional 45 nm CMOS technology, that consumes 29.3 mW from 1.0 V supply. A throughput of 235.3 Mbps is achieved while operating at 1.0 GHz clock frequency. The design occupies 0.11 mm2silicon area.

Cyclic Prefix Direct Sequence Spread Spectrum (CP-DSSS) is a novel waveform that is proposed as a solution to massive machine type communications (mMTC) for 5G and beyond. This paper analyzes the capacity of CP-DSSS in comparison with Orthogonal Frequency-Division Multiplexing (OFDM). We show that CP-DSSS achieves the same capacity as OFDM and can be optimized with similar precoding methods (e.g., water-filling). Because of its spread spectrum nature, CP-DSSS can operate as a secondary network using the same spectrum as the primary 4G or 5G network, but transmitting at much lower power. Accordingly, the combination of primary and secondary signals in the envisioned setup may be viewed as a power NOMA (non-orthogonal multiple access) technique where primary signals are detected and subtracted from the received signal first before detecting the secondary signals. In order to operate at a sufficiently low interference level to the primary network, details of CP-DSSS capacity for symbol rate reduction and multi-antenna operation are developed. The capacity limits established in this paper can be used as a baseline to evaluate the performance of future CP-DSSS receiver architectures for single- and multi-user scenarios.

Cyclic Prefix Direct Sequence Spread Spectrum (CP-DSSS) is a promising solution to increase user density for massive machine type communication (mMTC) applications. We propose that in such applications, the CP-DSSS waveform would operate as a secondary network, using the same spectrum as the primary network but at much lower signal to noise ratio (SNR). In this paper, we evaluate per-user capacity of CP-DSSS when simple matched filtering (MF) is performed on the uplink and time-reversal (TR) precoding is used on the downlink. In this setting and when operating in the low SNR regime, CP-DSSS achieves a per-user capacity that is near the optimum single-user capacity. TR precoding converges to the optimal capacity as the number of antennas at the hub/gateway increases. Using the estimated channel impulse response for MF and TR introduces little to no capacity loss. Given the near-optimal performance of MF detection and TR precoding for each of the users, CP-DSSS can be implemented with simple device transceiver structures, reducing per-unit cost for massively deployed 5G and beyond networks.

Orthogonal Time Frequency Space (OTFS) is a novel modulation scheme designed in the Doppler-delay domain to fully exploit time and frequency diversity of general time-varying channels. In this paper, we present a novel discrete-time analysis of OFDM-based OTFS transceiver with a concise and vectorized input-output relationship that clearly characterizes the contribution of each underlying signal processing block in such systems. When adopting cyclic prefix in the time domain, our analysis reveals that the proposed MIMO OTFS and OFDM systems have the same ergodic capacity despite the well-known fact that the former has great advantages in low-complexity receiver design for high Doppler channels. The proposed discrete-time vectorized formulation is applicable to general fast fading channels with arbitrary window functions. It also enables practical low-complexity receiver design for which such a concise formulation of the input-output relationship is of great benefits.

We perform an asymptotic study on the performance of filter bank multicarrier (FBMC) in the context of massive multi-input multi-output (MIMO). We show that the signal-to-interference-plus-noise ratio (SINR) cannot grow unboundedly by increasing the number of base station (BS) antennas, and is upper bounded by a certain deterministic value. This is a result of the correlation between the multi-antenna combining tap values and the channel impulse responses between the terminals and the BS antennas. To solve this problem, we introduce a simple FBMC prototype filter design method that removes this correlation, enabling us to achieve arbitrarily large SINR values by increasing the number of BS antennas.

Channel estimation techniques are crucial for reliable communications. This paper is concerned with channel estimation in a filter bank multicarrier spread spectrum (FBMC-SS) system. We explore two channel estimator options: (i) a method that makes use of a periodic preamble and mimics the channel estimation techniques that are widely used in OFDM-based systems; and (ii) a method that stays within the traditional realm of filter bank signal processing. For the case where the channel noise is white, both methods are analyzed in detail and their performance is compared against their respective Cramer-Rao Lower Bounds (CRLB). Advantages and disadvantages of the two methods under different channel conditions are also discussed to provide insight to the reader as to when one will outperform the other.

The development of low complexity, high performance spatial-multiplexing MIMO detectors continues to be an important area of research capable of increasing the spectral efficiency and capacity of wireless networks. The Markov Chain Monte Carlo (MCMC) detector has shown promise as a high performance method with low complexity growth. We present a solution to the high SNR stalling problems of previous MCMC detectors. Near-MAP performance is verified in simulation and in real-world measurements on an 8-antenna MIMO testbed using the 802.11ac WiFi protocol. This demonstration shows that the channel models predominantly used in the MCMC literature are too well-conditioned to provide an understanding of performance and complexity for indoor channels. Additional information is provided on the methods and techniques to match simulation to measurement and to construct a low cost and effective 8-antenna MIMO testbed.

In this paper, we study soft decision directed channel estimation algorithms for joint data detection and channel estimation over time-varying multiple-input multiple-output (MIMO) channels. The optimal Wiener filter (OWF) channel estimator is data dependent, and requires high complexity due to the computation of matrix inversion at each time instance. We develop a low-complexity, dual-layer channel estimation algorithm aiming to achieve the performance of OWF with a significantly reduced complexity. Excellent performance of the proposed design is achieved for both the soft minimum mean square error (soft-MMSE) MIMO detector and the Markov Chain Monte Carlo (MCMC) MIMO detector. The MCMC detector is shown to be significantly more robust to channel estimation error than the soft- MMSE detector.

Circular filter bank multicarrier with offset quadrature amplitude modulation (C-FBMC-OQAM) is one the recently introduced waveforms, which has shown promising characteristics to accommodate the requirements of future communication systems. In this letter, we analytically delve into some interesting properties of C-FBMC-OQAM waveform and, in particular, prove that the real and imaginary parts of the demodulated subcarrier signals carry exactly the same information. Hence, ignoring the imaginary part of the demodulated subcarrier signals does not incur any loss of information.

We study the possibility of removing the cyclic prefix (CP) overhead from orthogonal frequency division multiplexing (OFDM) in massive multiple-input multiple-output (MIMO) systems. We consider the uplink transmission, while our results are applicable to the downlink as well. The absence of CP increases the spectral efficiency in expense of intersymbol interference and intercarrier interference. It is known that in massive MIMO, the effects of uncorrelated noise and multiuser interference vanish as the number of base station antennas tends to infinity. To investigate if the channel distortions in the absence of CP fade away, we study the performance of the standard maximum ratio combining receiver. Our analysis reveals that in this receiver, there always remains some residual interference leading to saturation of signal-to-interference-plus-noise ratio. To resolve this problem, we propose using the time reversal (TR) technique. Moreover, in order to further reduce the multiuser interference, we propose a zero-forcing equalization to be deployed after the TR combining. We compare the achievable rate of the proposed system with that of the conventional CP-OFDM. We show that in realistic channels, a higher spectral efficiency is achieved by removing the CP from OFDM, while reducing the computational complexity.

A fundamental characteristic of wireless communications is in its broadcast nature, which allows accessibility of information without placing restrictions on a user's location. However, accessibility also makes wireless communications vulnerable to eavesdropping. In this context, this paper presents a two-part secure information transmission system. The first part makes use of reciprocity in wireless channels to allow for two asynchronous transceivers to obtain a pair of similar keys. Moreover, a unique augmentation, called strongest path cancellation (SPC), is applied to the keys. In the second part, the concept of artificial noise is introduced to the spread spectrum systems. Keys generated in the first part are used in the spread spectrum system and artificial noise is added to enhance the security of the communications. Two attacks on the proposed security solution are evaluated. First, an adversary following the same steps as the legitimate users is considered. Here, simulation and experimentation results show that SPC provides a boost to security against this type of adversary. The second attack studies an adversary with significant blind detection capabilities. Our observations on this attack indicate that when an ample amount of artificial noise can be used, two legitimate parties can communicate multiple information symbols per key.

Filter bank multicarrier (FBMC) systems based on offset quadrature amplitude modulation (OQAM), namely FBMC-OQAM, have been criticized for their inefficiency in the use of spectral resources, because of the long ramp-up and ramp-down tails at the beginning and the end of each data packet, respectively. We propose a novel method for shortening these tails. By appending a set of virtual (i.e., none data carrying) symbols to the beginning and the end of each packet, and clever selection of these symbols, we show that the ramp-up and ramp-down tails in the FBMC-OQAM can be suppressed to the extent that they are deemed negligible and thus may be ignored. This shortens the length of signal burst in each FBMC-OQAM packet and improves its spectral efficiency, viz., the same data is transmitted over a shorter period of time. We develop an optimization method that allows computation of virtual symbols for each data packet. Simulation results show that, compared with the existing methods, the proposed tail-shortening approach leads to superior out-of-band emissions performance and a much lower error vector magnitude for the demodulated symbols.

The fifth generation of wireless networks (5G) necessitates the use of waveforms with loose constraints on synchronization in multiuser scenarios. Also, carrier aggregation, as a way to better utilize the spectrum in 5G, needs a waveform with low out-of-band (OOB) emissions. Generalized frequency division multiplexing (GFDM) and circular filter bank multicarrier (C-FBMC) are two candidate waveforms that fulfill these requirements. Both GFDM and C-FBMC operate based on circular convolution, and use cyclic prefix to combat channel response. Because of obvious reasons, we refer to these waveform as circularly pulse-shaped. In this paper, we develop an analytical technique for examining the OOB emissions and multiuser interference (MUI) in circularly pulse-shaped waveforms. To stay focused, the study in this paper is limited to C-FBMC modulation. However, the approach we take is trivially extendable to other waveforms (including GFDM) as well. We derive equations that quantify OOB emissions and MUI. Our analysis allows us to identify the source of OOB emissions and MUI. This leads us to quantify the methods proposed by other researchers to decrease OOB emissions and MUI. Moreover, we quantify the impact of signal windowing at the transmitter and receiver in reducing OOB emissions and MUI, respectively.

In a recent paper, we have proposed a filter bank multicarrier spread spectrum (FB-MC-SS) waveform as a new method for wideband spread spectrum communications in HF bands. We have noted that FB-MC-SS is well suited for this application because of its robustness against narrow and partial band interference and because it has good performance over a wide range of delay and Doppler spreads. In this paper, we further our study and analyze the bit error rate (BER) of FB-MC-SS when applied to HF channels. Our study is a comprehensive one and includes time-varying characteristics of HF channels, channel estimation error, and correlation among subcarriers in the proposed FB-MC-SS system.

Generalized frequency division multiplexing (GFDM) and circular filter bank multicarrier (C-FBMC) are two contender waveforms with circular pulse-shaping that are recently proposed for the physical layer of the fifth generation of wireless communication networks (5G). This paper puts these waveforms under the microscope and conducts an analysis on their practical feasibility and performance. In addition, we present a transmitter structure for both GFDM and C-FBMC and show that this structure has the same complexity for both systems. In this paper, GFDM receiver with successive interference cancellation (SIC) is considered as it can get a performance close to that of OFDM (orthogonal frequency division multiplexing). Our bit error rate (BER) performance analysis reveals that GFDM has limitations in terms of the total number of symbols per data packet. When the number of symbols in a packet has an even value, GFDM suffers from a high error floor in BER. For the small constellation sizes, GFDM and C-FBMC reach the same BER performance as that of OFDM. As the constellation size increases, a gap between the BER curve of GFDM and OFDM starts to appear while C-FBMC keeps the same performance as OFDM. Finally, our computational complexity analysis reveals that C-FBMC receiver is simpler than GFDM.

In underwater acoustic (UWA) communications, the mobility of communicating vehicles results in a change of the time scale in the received signal. This is called Doppler scaling. Doppler scaling, although small (usually 1%, or smaller), impacts the receiver performance significantly, if uncompensated. This paper suggests a novel method for compensating Doppler scaling in filter bank multicarrier (FBMC) systems. We show that the method of frequency spreading that have already been applied to the design of digital filters can be applied to each subcarrier in FBMC systems to compensate the impact of Doppler scaling. This novel approach compensates for Doppler scaling with a very small addition in the complexity.

This paper starts with presenting a fundamental principle based on which the celebrated orthogonal frequency division multiplexing (OFDM) waveform is constructed. It then extends the same principle to construct the newly introduced generalized frequency division multiplexing (GFDM) signals. This novel derivation sheds light on some interesting properties of GFDM. In particular, our derivation seamlessly leads to an implementation of GFDM transmitter which has significantly lower complexity than what has been reported so far. Our derivation also facilitates a trivial understanding of how GFDM (similar to OFDM) can be applied in MIMO channels.

There is a strong need in wireless communication systems for better, low-complexity detectors. Here we demonstrate the implementation, simulation, and real-world measurements of such a near-optimal approximate ML method called Markov Chain Monte Carlo (MCMC) within an 802.11ac WiFi framework. Detail is provided on the relationship between SNR, channel matrix condition number (CN), and bit error rate (BER). The importance of considering condition number in real-world measurements is demonstrated.

An analog adaptive notch filter implementation at 54.1 MHz is presented in this paper. The analog circuit is implemented using discrete components. Implementation issues such as components phase shift and DC offset are discussed and solution for them are proposed. In addition, effect of frequency offset between reference and input signal is discussed. The implemented circuit has -3 dB bandwidth of 300 Hz and a null depth of 45 dB or better.

This paper presents a theoretical analysis of the performance of a filter bank-based multicarrier spread spectrum (FB-MC-SS) system. In FB-MC-SS, each data symbol is spread across multiple subcarriers, but - contrary to some other systems - there is no spreading in time. The results of this system are then compared with those of the well-known direct sequence spread spectrum (DS-SS) system with a rake receiver for its best performance. We compare the two systems when the channel noise is white. We prove that as the processing gains of the two systems tend to infinity both systems approach the same performance. However, numerical simulations show that in practice, where processing gain is limited, FB-MC-SS outperforms DS-SS.

This paper introduces filter bank multicarrier (FBMC) as a potential candidate in the application of massive MIMO communication. It also points out the advantages of FBMC over OFDM (orthogonal frequency division multiplexing) in the application of massive MIMO. The absence of cyclic prefix in FBMC increases the bandwidth efficiency. In addition, FBMC allows carrier aggregation straightforwardly. Self-equalization, a property of FBMC in massive MIMO that is introduced in this paper, has the impact of reducing (i) complexity; (ii) sensitivity to carrier frequency offset (CFO); (iii) peak-to-average power ratio (PAPR); (iv) system latency; and (v) increasing bandwidth efficiency. The numerical results that corroborate these claims are presented.

Multiple carrier frequency offsets (CFOs) present in the uplink of orthogonal frequency division multiple access (OFDMA) systems adversely affect subcarrier orthogonality and impose a serious performance loss. In this paper, we propose the application of time domain receiver windowing to concentrate the leakage caused by CFOs to a few adjacent subcarriers with almost no additional computational complexity. This allows us to approximate the interference matrix with a quasi-banded matrix by neglecting small elements outside a certain band which enables robust and computationally efficient signal detection. The proposed CFO compensation technique is applicable to all types of subcarrier assignment techniques. Simulation results show that the quasi-banded approximation of the interference matrix is accurate enough to provide almost the same bit error rate performance as that of the optimal solution. The excellent performance of our proposed method is also proven through running an experiment using our FPGA-based system setup.

This paper introduces the use of non-uniform fast Fourier transform (NUFFT) in detection of orthogonal frequency division multiplexing (OFDM) in a situation when the received signal samples are unevenly spaced. The application of interest to us is underwater acoustic communications, where the relatively low speed of (acoustic) signal propagation in water combined with movement of communicating vehicles introduces a time-varying time-scale to the received signal. This is called Doppler scaling. In the presence of Doppler scaling, when the received signal is sampled at the nominal rate, the samples will be seen as unevenly spaced within the domain of transmit signal. This leads to an undetectable OFDM signal, if not corrected. We develop the necessary equations that show how NUFFT should be applied to this application. We also discuss a method of Doppler scaling estimation by using of null subcarriers that we assume are inserted in the OFDM signal. Moreover, we examine our development on real signals obtained from an at-sea experiment (ACOMM10) and confirm its correct operation.

Orthogonal frequency division multiplexing (OFDM), widely recommended for sharing the spectrum among different nodes in a dynamic spectrum access network, imposes tight timing and frequency synchronization requirements. We examine the use of filterbank multicarrier (FBMC), a somewhat lesser known and understood alternative, for dynamic spectrum access. FBMC promises very low out-of-band energy of each subcarrier signal when compared to OFDM. In order to fully understand and evaluate the promise of FBMC, we first examine the use of special pulse-shaping filters of the FBMC PHY layer in reliably transmitting data packets at a very high rate. Next, to understand the impact of FBMC beyond the PHY layer, we devise a distributed and adaptive medium access control (MAC) protocol that coordinates data packet traffic among the different nodes in the network in a best-effort manner. Using extensive simulations, we show that FBMC consistently achieves at least an order of magnitude performance improvement over OFDM in several aspects including packet transmission delays, channel access delays, and effective data transmission rate available to each node in static, indoor settings. Using measurements of power spectral density and high data rate transmissions from a transceiver that we build using our National Instruments hardware platform, we show that while FBMC can decode/distinguish all the received symbols without any errors, OFDM cannot. Finally, we also examine the use of FBMC in a vehicular network setup. We find that FBMC achieves an order of magnitude performance improvement over large distances in this setup as well. Furthermore, in the case of multihop vehicular networks, FBMC can achieve about 20 × smaller end-to-end data packet delivery delays and relatively low packet drop probabilities. In summary, FBMC offers a much higher performing alternative to OFDM for networks that dynamically share the spectrum among multiple nodes.

In this paper, we study carrier frequency offset (CFO) estimation in the uplink of multiuser offset QAM filter bank multicarrier (FBMC) communication systems. A low-complexity frequency-domain CFO estimator using periodical training sequences is proposed. We derive the theoretical mean square error (MSE) for the proposed estimator and computer simulations show that the derived MSE matches the simulated MSE closely. Compared with state-of-the- art time-domain estimators, the proposed estimator achieves better performance with a much lower computational complexity.

Implementation of any cognitive radio network requires an effective control channel that can operate under various modes of activity from the primary users. This paper reports the design and implementation of a filter bank multicarrier spread spectrum (FBMC-SS) system for use as the control channel in cognitive radio networks. The proposed design is based on a filtered multitone (FMT) implementation. Carrier and timing acquisition and tracking methods as well as a blind channel estimation method are developed for the proposed control channel. We also report an implementation of the proposed FBMC-SS system on a hardware platform; a FlexRIO FPGA module from National Instruments.

The third generation partnership project (3GPP) long term evolution (LTE) radio standard has adopted a special form of orthogonal frequency division multiplexing (OFDM) method for the uplink of multiple access networks. This method which is called single carrier frequency division multiple access (SC-FDMA) applies a precoding to each user data set in each OFDM symbol to control its peak-to-average power ratio (PAPR). Some recent works have proposed minimization of the variance of the instantaneous power of the output signal of the transmitter as a means of reducing PAPR to near its minimum value. However, the studies so far have been based on intuitions and observation of some numerical results. The goal of this paper is to develop a mathematical procedure to further establish the significance of this method. We formulate the problem in the form of a method of Lagrange multipliers and analyze its second-order conditions to confirm analytically that the optimal window is indeed a strict local minimizer. We also analyze and compensate the noise enhancement penalty of the optimal window. Our analysis also leads us to find new window functions that further reduce the PAPR and improve the BER performance.

Orthogonal frequency division multiplexing (OFDM) is the most popular scheme for broadband communications. However, it has been shown that OFDM has disadvantages in time-varying channels. Filter bank multicarrier (FBMC) is an alternative multicarrier modulation method that can be designed for robust performance in doubly (time and frequency) dispersive channels. The emphasis of this paper is on a class of FBMC systems that are called filtered multitone (FMT). We note that although unlike the more popular FBMC systems that use offset quadrature amplitude modulation (OQAM) or cosine modulated techniques to achieve full bandwidth efficiency, FMT does not have full bandwidth efficiency, its possible use in multiple-input multiple-output (MIMO) channels still makes it an attractive method. In a recent work, we have noted that the FBMC systems that are based on OQAM/cosine modulated techniques are very restrictive in MIMO channels and introduced a class of FMT systems with robust performance in doubly dispersive channels. This paper extends our previous results and shows that further improvement can be obtained by organizing the data symbols in a hexagonal lattice structure, as compared to the more popular rectangular structure. In addition, results that compare our proposed FMT systems with the conventional FMT and OFDM are presented and we show that a substantial gain in performance is achieved.

In this paper, we develop a novel statistical detection algorithm following similar principles to that of expectation maximization (EM) algorithm. Our goal is to develop an iterative algorithm for joint channel estimation and data detection in channels that have a long memory and are fast varying in time. At each iteration, starting with an estimate of the channel, we combine a Markov Chain Monte Carlo (MCMC) algorithm for data detection, and an adaptive algorithm for channel tracking, to develop a statistical search procedure that finds joint important samples of possible transmitted data and channel impulse responses. The result of this step, which may be thought as E-step of the proposed algorithm, is used in an M-step that refines the channel estimate, for the next iteration. Excellent behavior of the proposed algorithm is presented by examining it on real data from underwater acoustic communication channels.

In this paper, we study joint iterative data detection and channel decoding under imperfect channel state information (CSI). We apply the Markov Chain Monte Carlo technique to generate a list of channel estimates (LCE) that maximizes the a posteriori probabilities of the transmitted data, given the received signal and the soft feedback from the channel decoder. The LCE is refined over each iteration of data detection and decoding to facilitate improved channel estimation and thus yields superior detection performance. It is shown that, even with a small list size, the proposed MCMC-LCE detector outperforms the coherent detector in which data detection is performed based on a single channel estimate (SCE). As opposed to the noncoherent detectors which impose stringent constraints on the fading distribution, the MCMC-LCE detector is applicable to general fading distributions. It also offers a low complexity that is linear in the coherent length of the channel and the list size.

This paper presents an analysis of the effect of carrier frequency offset (CFO) on offset QAM (OQAM) multicarrier filter bank (MCFB) systems, also known as staggered modulated multitone (SMT), over frequency-selective channels. This effect may be quantified by signal-to-interference ratio (SIR). We drive an accurate expression for the interference power and the desired signal power. Then SIR of SMT systems is calculated. Next, we drive an approximated SIR when the maximum delay of the channel is small in comparison with symbol spacing. The approximated SIR show that the SIR over frequency-selective channels converges to that over additive white Gaussian noise (AWGN) channels. Numerical results show that with increasing number of subcarriers, both of accurate and approximated forms of SIR as a function of CFO over frequency-selective channels converge to that over AWGN channels. Also, we compare SMT and orthogonal frequency division multiplexing (OFDM). It is shown that OFDM has better SIR in small CFO over frequency-selective channels. But with large number of subcarriers or high CFO, SMT outperforms OFDM.

This paper examines near capacity performance of Markov Chain Monte Carlo (MCMC) detectors for multiple-input and multiple-output (MIMO) channels. The proposed MCMC detector (Log-MAP-tb b-MCMC) operates in a strictly bit-wise fashion and adopts Log-MAP algorithm with table look-up. When concatenated with an optimized low-density parity-check (LDPC) code, Log-MAP-tb b-MCMC can operate within 1.2-1.8 dB of the capacity of MIMO systems with 8 transmit/receive antennas at spectral efficiencies up to ¿ = 24 bits/channel use (b/ch). This result improves upon best performance achieved by turbo coded systems using list sphere decoding (LSD) detector by 2.3-3.8 dB, leading to nearly 50% reduction in the capacity gap. Detailed comparisons of the Log-MAP-tb b-MCMC with LSD based detectors demonstrate that MCMC detector is indeed the detector of choice for achieving channel capacity both in terms of performance and complexity.

We address the problem of collaborative sensing in cognitive radios. In a cognitive radio network, all the nodes may sense the spectrum simultaneously. They should then exchange their sensing results in order to improve the reliability of the detection. This exchange of information has to be done efficiently to improve on the bandwidth efficiency of the network. We propose a medium access control (MAC) signaling protocol and study its performance behavior. For the case of a single-band channel, we present a thorough analysis of the proposed protocol and use the results to pick the protocol parameters that minimizes the signaling time for a given probability of detection. Analysis of the proposed protocol for multiband channels is solved by introducing a matrix formulation of the proposed protocol that allows its evaluation numerically.

Statistical detectors that are based on Markov chain Monte Carlo (MCMC) simulators have emerged as promising low-complexity solutions to both multiple-input multiple-output (MIMO) and code division multiple access (CDMA) communication systems. While these types of detectors achieve unprecedented near capacity performance, i.e., when operated in low signal-to-noise ratio (SNR) regime, they exhibit a serious problem at medium to high SNR regimes, referred to as the "stalling" problem. In this paper, we investigate the sources of this degradation and propose a new search strategy called constrained MCMC to remedy the issue of stalling.

Although orthogonal frequency division multiplexing (OFDM) communication systems that use inverse discrete Fourier (IDFT) for multicarrier modulation and discrete Fourier transform (DFT) for demodulation are dominantly adopted in the current broadband standards, there have been some reports in recent years that discuss the shortcomings of OFDM in highly mobile and/or multiple access environments. To resolve these problem, a number of authors have proposed a shift from OFDM to filterbank-based multicarrier techniques. This paper is also along the same line. We present a thorough study of filtered multitone (FMT)in time-varying frequency selective channels. We derive close-form equations for the optimum parameters of per tone fractionally spaced equalizers and also signal to interference plus noise ratio (SINR) and use these to evaluate FMT in typical wireless mobile environments.

In this paper, we propose a novel low complexity soft-in soft-out (SISO) equalizer using the Markov chain Monte Carlo (MCMC) technique. Direct application of MCMC to SISO equalization (reported in a previous work) results in a sequential processing algorithm that leads to a long processing delay in the communication link. Using the tool of factor graph, we propose a novel parallel processing algorithm that reduces the processing delay by orders of magnitude. Numerical results show that, both the sequential and parallel processing SISO equalizers perform similarly well and achieve a performance that is only slightly worse than the optimum SISO equalizer. The optimum SISO equalizer, on the other hand, has a complexity that grows exponentially with the size of the memory of the channel, while the complexity of the proposed SISO equalizers grows linearly.

A carrier offset in OFDM system simulation is generally considered to be slowly time-varying, so that, over short simulation periods, it may be considered to be a constant quantity. However, depending on system mobility, carrier frequency, and communication duration, time-varying carrier offsets caused by Doppler effects can be significant in a real physical environment. Few researchers have addressed this in their works. Of those who have addressed this, many present simplified, vague, or inaccurate time-varying carrier offset models. In this paper, we present a more realistic time-varying carrier offset model and present expressions for carrier offset correction that maximize the signal-to-interference ratio (SIR). We also provide guidelines for when the application of the time-varying carrier offset model is crucial for correct OFDM system evaluation.

This letter presents a new prospect of selection of taper windows (prolate filters) in the multitaper spectral estimators for applications where very wide spectral dynamic range are of interest. Previous works have emphasized on the use of an adaptive approach to deal with such cases. However, the adaptive approach is computationally very expensive. The novel approach proposed in this letter avoids the need for adaptation, by suggesting a modification to the design of the taper windows.

Markov Chain Monte Carlo methods have recently been applied as front-end detectors in multiple- input multiple-output (MIMO) communication systems. Moreover, the near capacity behavior of such detectors in low signal-to-noise ratio (SNR) regimes have been demonstrated through computer simulations. However, it has also been found that the MCMC MIMO detectors degrade in high SNR regimes. This paper investigates into the source of this degradation and proposes a number of ad hoc methods to resolve this undesirable behavior of the MCMC MIMO detectors. The effectiveness of the proposed methods is shown through empirical (simulation) results.

A carrier offset in OFDM system simulation is generally considered to be slowly time-varying, so that, over short simulation periods, it may be considered to be a constant quantity. However, depending on system mobility, carrier frequency, and communication duration, time-varying carrier offsets can be significant in a real physical environment. Few researchers have addressed this in their works. Those few who have, present simplified, vague, or inaccurate time-varying carrier offset models. The main goal of this paper is to present an accurate time- varying carrier offset model, and to provide guidelines for when the application of this model is crucial for correct OFDM system evaluation.

Multiuser/MIMO detectors that use Markov chain Monte Carlo (MCMC) simulation techniques to obtain likelihood of information bits have been developed recently. In this paper, we explore the implementation details of one such detector and present an efficient hardware architecture of it. The first step in development of this architecture is to derive a log domain version of the Gibbs sampler, an efficient method of obtaining samples of MCMC simulator. This formulation is numerically stable and can operate with low precision. The log-domain formulation also lends itself to a hardware architecture that involves only addition, subtraction, and compare operations. Moreover, pipelining can be introduced in the proposed architecture straightforwardly. We also explore the word-length requirement of the developed architecture through computer simulations.

Satisfactory operation of orthogonal frequency-division multiplexing (OFDM) requires carrier frequency estimation with precision on the order of 1 to 2% of the subcarrier spacing. Numerous pilot-aided and blind algorithms that achieve this precision have been proposed. Blind algorithms are generally more complex than the pilot-aided algorithms. In this paper, we propose a novel low-complexity blind algorithm that takes advantage of a key property of the in-band OFDM power spectral density (PSD). To date, OFDM PSD research and modelling has mainly been directed towards reducing the out-of-band radiation. Here, we turn our attention to the in-band portion of the spectrum and show that it has an oscillatory variation. We show how this property can be used for carrier frequency tracking. Computer simulations show that the proposed algorithm works well in high-noise, frequency-selective channels.

In this paper, the use of cosine modulated filter banks (CMFB) for multi-carrier modulation in the application of very high-speed digital subscriber lines (VDSL) is studied. We refer to this modulation technique as cosine modulated multitone (CMT). CMT is fundamentally the same as the discrete wavelet multitone (DWMT) except for the receiver structure. With the modified receiver structure, CMT uses only two taps per sub-carrier for equalization. This is an order of magnitude less complex than DWMT where each subcarrier requires more than 20 taps for equalization. We compare CMT with zipper discrete multitone (z-DMT) and filtered multitone (FMT), the two modulation techniques that have been included in the VDSL draft standard.

A recent development in the literature has proposed a cosine modulated filter bank-based multicarrier modulation technique with blind equalization capability. However, convergence studies of the proposed blind equalizer have been carried out through computer simulations only. We present a thorough study of the blind equalizer by analyzing its associated cost function and show that it has two global minima and two saddle points.

In this paper, we develop a new soft-in soft-out (SISO) multiple-input multiple-output (MIMO) detection algorithm using the Markov chain Monte Carlo (MCMC) simulation techniques and study its performance when applied to a MIMO communication system. Comparison with the best MIMO detection algorithm in the current literature, sphere decoding, shows that the proposed detection algorithm can improve the gap between the present results and the capacity by as much as 2 dB.

In a recent work, it has been found that the suboptimum detectors that are based on Markov chain Monte Carlo (MCMC) simulation techniques perform significantly better than their sphere decoding (SD) counterparts. In this letter, we explore the sources of this difference and show that a modification to existing sphere decoders can result in some improvement in their performance, even though they still fall short when compared with the MCMC detector. We also present a novel SD detector that is an exact realization of max-log-MAP detector. We call this exact max-log SD detector. Comparison of the results of this detector with those of the max-log version of the MCMC detector reveals that the latter is near optimal.

We consider the problem of channel estimation and tracking in OFDM systems and explore the idea of adding pilot symbols to the data symbols as a means of conserving bandwidth. The term pilot embedding (PE) is used to refer to this scheme. Compared to the pilot insertion (PI) scheme, i.e., the conventional pilot symbol assisted modulation (PSAM), PE is more bandwidth efficient since no separate subcarriers/timeslots are allocated to pilots. We formalize this by evaluating the capacity of the two schemes and showing that PE indeed has the potential to transmit at a higher rate. The problem of channel tracking using a decision directed approach is reviewed and found to be unreliable, in the sense that the channel estimator fails to track the channel variations after some iterations because of unavoidable decision errors. We propose an ad hoc channel estimation algorithm that uses the embedded pilots along with the past decisions of data for reliable tracking of the channel.

We present a novel soft-in soft-out (SISO) detection scheme based on Markov-chain Monte-Carlo (MCMC) simulations. The proposed detector is applicable to both synchronous multiuser and multiple-input multiple-output (MIMO) communication systems. Unlike previous publications on the subject, we use Monte Carlo integration technique to arrive at the receiver structure. The proposed multiuser/MIMO detector is found to follow the Rao-Blackwell formulation and found to result in much more reliable systems than those reported so far in the literature. In particular, through computer simulations, we demonstrate that the proposed receiver can easily handle the cases of overloaded systems, i.e. when in a multiuser set-up the number of users is larger than the spreading gain, or when in a MIMO set-up there are more transmit antennas than receive antennas.

In this paper a MIMO system with transmit and receive antenna and the channel model with two methods of pilot-aided (PA) schemes are considered. The first scheme is pilot insertion (PI) scheme, where pilots are time multiplexed with data and the second scheme pilot embedding (PE) scheme, where pilots are added and transmitted concurrently with data. The study shows that PI scheme is better than PE scheme. To obtain the capacity the maximum-likelihood channel estimation is used. Then the discrete and continuous capacity of a MIMO channel with imperfect channel estimates is evaluated.

Runlength limited (RLL) codes are essential in recording systems for minimizing distortions and maintaining bit synchronization. In this paper, we investigate the application of turbo codes on RLL (1,7) coded partial response equalized recording channels. We proposed a 'combined trellis' approach for doing 'soft-in soft-out' (SISO) channel detection and RLL decoding jointly. This approach makes the implementation of turbo equalization easier since it eliminates the need for a 'SISO RLL encoder' in the feedback path from turbo decoder to channel detector. Simulation studies on magnetic recording channels show that our approach provides a coding gain of about 4 dB compared to Viterbi detection at 10/sup -6/ bit error rate.

Space-time block codes based on orthogonal designs, known as space-time orthogonal block (STOB) codes, have recently been proposed. It has been noted that when the number of transmit antennas is more than two, full-rate STOB codes could only be designed for real-valued data symbols. Real-valued symbols form pulse amplitude modulated (PAM) sequences whose bandwidth efficient transmission is only possible through single side-band (SSB) modulation. We proposed cosine modulated filter bank (CMFB) multicarrier modulation (MCM) as a bandwidth efficient method of implementing full-rate STOB-coded systems. The impact of channel distortion on the received signal is studied, and a method of designing a zero-forcing equalizer that removes intersymbol interference (ISI) and interchannel interference (ICI) in the system is developed. Some relevant properties of the proposed system are also reported.

The cosine modulated filter bank (CMFB) is introduced as a multicarrier modulation (MCM) technique for wideband data transmission over wireless channels. Under the name discrete wavelet multitone modulation, CMFB has been considered for data transmission over digital subscriber lines. We propose a new receiver structure that is different from those proposed previously. The new structure simplifies the task of channel equalization, by reducing the number of equalizer parameters significantly. We also propose a novel blind equalization algorithm that fits very nicely in the proposed structure. Moreover, we discuss the bandwidth efficiency of the proposed CMFB-MCM system and show that it is superior to the conventional (single carrier) quadrature amplitude modulation (QAM) and orthogonal frequency-division multiplexing (OFDM). The CMFB is found to be a signal processing block that stacks a number of vestigial sideband modulated signals in a number of overlapping subchannels in the most efficient way. The proposed CMFB-MCM is also compared to OFDM with respect to bit-error rate performance. Under the conditions that the channel impulse response duration remains less than the length of cyclic prefix, OFDM is found marginally superior to CMFB-MCM. However, OFDM degrades very fast when the channel impulse response duration exceeds the length of the cyclic prefix. CMFB-MCM, on the other hand, is found less sensitive to variations in channel impulse response duration.

A high peak-to-average power ratio is a major problem that is inherent in all multicarrier communication systems. Clipping the high-peak power samples introduces (extra) clipping noise, which degrades the system performance in terms of bit-error rate (BER). Measuring the BER usually requires a very long simulation time, as clipping occurs very rarely. We propose a method called clipping noise injection, which allows BER estimation (due to clipping) in discrete multitone-based systems in a fast and quite precise way. Savings of as great as 90% or more are observed in some simulations that are reported. Higher savings are expected when lower BER cases have to be studied.

A general method of constructing run-length limited (d, k) constrained codes from arbitrary sequences is introduced. This method is then combined with the method of guided scrambling for constructing a class of weakly constrained codes. The proposed codes are analyzed for the case of d=0 and are shown to give results which are better or comparable to those of the best available codes, however, at the cost of failure with some very low probability. For d>0, the code efficiency of the codes constructed according to the proposed method reduces significantly.

High peak to average power ratio (PAR) is a major problem that is inherent to all multi-carrier communication systems. Clipping the high peak power samples introduces (extra) clipping noise, which degrades the system performance in terms of bit error rate (BER). Measuring BER usually requires very long simulation time, as clipping occurs very rarely. In this paper, we propose a method called clipping noise injection, which allows us to estimate BER (due to clipping) in DMT-based systems in a fast and quite precise way. Savings of as great as 90% or more are observed in some simulations that are reported in this paper. Higher savings are expected when lower BER cases have to be studied.

We investigate the effects of performing channel estimation on an OFDM system in AWGN and Rayleigh channels using non-ideal interpolating and decimating filters. Pilots are used to estimate the combined response of the channel and the filters. By making use of the standard Gaussian approximation to the interference for the AWGN channel, we illustrate how to estimate the symbol error rate of an M-QAM system. By using an improved Gaussian approximation for the Rayleigh fading channel for error rate estimation, we show that this is equivalent to making the assumption that the interference is Gaussian noise experienced in a Rayleigh fading channel. It is shown that the predicted symbol error rate is close to that produced by simulations for a 64QAM modulated OFDM system based on the wireless LAN system described in IEEE 802.11a.

An added pilot semi-blind (APSB) scheme used for channel identification of OFDM systems, which have been adopted for DAB and DVB-T, is proposed. This scheme uses pilot symbols that are added directly to the data symbols and hence does not require any additional bandwidth for its implementation. To remove the pilots, a two dimensional Wiener filter is used for the purpose of channel interpolation by using successive iterations. Although its complexity increases with additional iterations, the APSB scheme is found to compare favorably to existing blind schemes proposed for the OFDM system in terms of bit error rate and convergence.

A general method of constructing (d, k) constrained codes from arbitrary sequences is introduced. This method is then used for constructing a class of weakly constrained codes. The proposed codes are analyzed for the case of d=0 and shown to give results which are better or comparable to those of the best available codes, however at the cost of failure with some very low probability.

Timing-recovery and gain-control play important role in communication systems. In this paper, we propose reliable acquisition, tracking and gain control algorithms for fixed delay tree search with decision feedback (FDTS/DF) detector on magnetic recording channel. First, we propose a modified Mueller and Muller algorithm for timing recovery during tracking period, which is based on selective transitions in the samples at the detector input. Next, we give the modified threshold detection scheme that quickly converges to the correct sampling phase without hang-up problems during acquisition period. Bit-by-bit simulations are included first to show the reliability in tracking performance of the timing-recovery and gain-control loops, and then to show the robustness and accuracy of the fast acquisition algorithm.

Adaptive least mean square (LMS) filters with or without training sequences, which are known as training-based and blind detectors respectively, have been formulated to counter interference in CDMA systems. The convergence characteristics of these two LMS detectors are analyzed and compared in this paper. We show that the blind detector is superior to the training-based detector with respect to convergence rate. On the other hand, the training-based detector performs better in the steady state, giving a lower excess mean-square error (MSE) for a given adaptation step size. A novel decision-directed LMS detector which achieves the low excess MSE of the training-based detector and the superior convergence performance of the blind detector is proposed.

A new adaptive beamformer which combines the idea of subband processing and the generalized sidelobe canceller structure is presented. The proposed subband beamformer has a blocking matrix that uses coefficient-constrained subband adaptive filters to limit target cancellation within an allowable range of direction of arrival. Simulations compare the fullband adaptive beamformer and the subband adaptive beamformer show that the subband beamformer has better performance than the fullband beamformer when the input signals to the microphone array are coloured. In reverberant environments, also, the proposed subband beamformer performs better than its fullband counterpart.

Clipping the peak power samples in the DMT signal introduces clipping noise which degrades the system performance. A previous report proposed the spectrum shaping method in which clipping noise is shifted to the high frequency subcarriers that can tolerate higher noise levels. We propose two new clipping noise reduction schemes, one of which is used in conjunction with the spectrum shaping method, to efficiently reduce the clipping noise in ADSL transceivers. The second scheme reduces the clipping noise through a signal randomization, transparent to the receiver. We also study the reduction in clipping noise by combining the two proposed schemes.

The application of iterative detection using turbo codes for signal detection in magnetic recording channels has become a topic of intense research. Interesting results have been reported for partial response equalized recording channels. This paper investigates the performance of turbo codes on decision feedback equalized (DFE) recording channels. The channel detector used is a soft-in soft-out parallel DFE (PDFE) detector. Simulation results shows a coding gain of more than 3 dB at a bit error rate of 10/sup -6/. Further, the error propagation in PDFE has been significantly minimized by the de-interleaver between PDFE and turbo decoder, and it does not influence the overall burst error performance.

The study of error-burst statistics is important for all detection systems, and more so for the decision feedback class. In data storage applications, many detection systems use decision feedback in one form or another. Fixed-delay tree search with decision feedback (FDTS/DF) and decision feedback equalization (DFE) are the direct forms, whereas the partial response detectors such as the reduced state sequence estimator (RSSE) and noise predictive maximum likelihood (NPML) detectors are the other forms. Although DF reduces the system complexity, it is inevitably linked with error propagation (EP), which can be quantified using error-burst statistics. Analytical evaluation of these statistics is difficult, if not impossible, because of the complexity of the problem. Hence, the usual practice is to use computer simulations. However, the computational time in traditional bit-by-bit simulations can be prohibitive at meaningful signal-to-noise ratios. In this paper, we propose a novel approach for fast estimation of error-burst statistics in FDTS/DF detectors, which is also applicable to other detection systems. In this approach, error events are initiated more frequently than natural by artificially injecting noise samples. These noise samples are generated using a transformation that results in significant reduction in computational complexity. Simulation studies show that the EP performance obtained by the proposed method matches closely with those obtained by bit-by-bit simulations, while saving as much as 99% of simulation time.

Time-domain equalizers (TEQ) are used in the discrete multitone (DMT) transceivers in order to reduce the duration of the overall response of the transmission system, so that a shorter-length cyclic prefix could be used. The optimum TEQ is the one that results in maximum bit allocation to each block of the DMT. However, the optimum design of TEQs turns out to be a very difficult task. We give the general guidelines that one should follow in the design of TEQ to achieve a good performance. Based on the suggested guidelines, we first propose an eigenapproach design method which results in TEQs with comparable performance to those of a previously reported method, but at a much lower computational cost. Further study of the proposed guidelines reveals that the choice of target-impulse response in the design of TEQ only weakly depends on the channel response. Noting this, we propose a second design method that is even simpler than our first method, but still results in comparable designs to those of our first method and also those obtained from the much more complex methods of the present literature.

We present a new rigorous analysis of the FBLMS algorithm. We derive the equations which control the expected convergence of the FBLMS algorithm and then go on to analyze the eigenvalues of the matrix which control the convergence behaviour of the FBLMS algorithm. Using Gerschgorin's theorem, we then show that all the eigenvalues of the normalized constrained and unconstrained FBLMS algorithms tend asymptotically towards the same value.

Adaptive filters used in code division multiple access (CDMA) receivers to counter interference have been formulated both with and without the assumption of training symbols being transmitted. They are known as training-based and blind detectors respectively. We show that the convergence behaviour of the blind minimum-output-energy (MOE) detector can be quite easily derived, unlike what was implied by the procedure outlined in a previous paper. The simplification results from the observation that the correlation matrix determining convergence performance can be made symmetric, after which many standard results from the literature on least mean square (LMS) filters apply immediately.

The time domain equalizer (TEQ) is used in the discrete multitone (DMT) transceivers in order to reduce the duration of the overall response of the transmission system. The optimum TEQ is the one that results in maximum bit allocation to each block of the DMT. However, the optimum design of the TEQ turns out to be a very difficult task. In an earlier work, we noted that there are some general guidelines that one should follow in the design of the TEQ for achieving a near-optimum performance. There, we proposed an eigen-approach which could result in TEQs with comparable performance to those of a previously reported method, but at a much lower computational cost. We propose a second design method which is even simpler than our first method, but still results in designs comparable to the best available methods.

A time domain equalizer (TEQ) is used in discrete multitone (DMT) transceivers in order to reduce the duration of the overall response of the transmission system, so that a shorter length cyclic prefix could be used. The optimum TEQ is the one that results in maximum bit allocation to each block of DMT. Al-Dhahir and Cioffi (1996) have proposed an optimization scheme which can achieve this goal under certain conditions. This scheme is rather involved and thus its implementation in an on-line system is not feasible. In this paper, we present a novel approach which results in TEQ designs with comparable performance to those of Al-Dhahir and Cioffi, but at a very affordable computational cost.

In this paper, we propose a simple detection scheme for a d=2 optical recording channel. The detection method employs a partial response target that introduces destructive interference, but which is effectively removed by modifications to the threshold detector. Bit error rate performance simulations based on pulses obtained from both a channel model and a real DVD system show that the new detection technique achieves 1.5-2 dB improvement over direct threshold detection following equalization to symmetric target response of memory 4. The proposed scheme performs better than Viterbi detection with an optimal partial response target of memory 4, while having a complexity comparable to that of a threshold detector.

The convergence behaviour of the LMS CDMA multiuser detector is of great interest both in practice and in theory. The sampling rate for the tap-input of a LMS detector may be equal to or higher than the chip rate, and these correspond to chip-spaced (CS) and fractionally-spaced (FS) detection, respectively. It is shown in this paper that CS and FS detectors with the same time-span exhibit identical convergence behaviour, if the baseband received signal is strictly bandlimited to half the chip rate. Even in the practical case when this condition is not met, deviations from this observation are imperceptible unless the initial tap-weight vector gives an extremely large mean squared error (MSE). The inadequacy of the eigenvalue spread of the tap-input correlation matrix as an indicator of transient behaviour, and the influence of the initial tap weight vector on convergence speed, are highlighted. Specifically, initialization within the signal subspace or to the origin leads to very much faster convergence compared to initialization in the noise subspace.

The problem of channel equalization via channel identification (CEQCID) that has previously been considered by a handful of researchers is explored further. An efficient algorithm for mapping the channel parameters to the equalizers coefficients is proposed. The proposed scheme is compared with a lattice least squares (LS) based receivers. For the particular application of the high frequency (HF) radio channels, we find that the CEQCID has lower computational complexity. In terms of the tracking performance, also, the CEQCID has been found to be superior to the LS based receivers. We emphasize on the implementation of a fractionally tap-spaced decision feedback equalizer (DFE) and compare that with the T-spaced DFE. We show that the former is a better choice for the multipath HF channels.

Implementation of the transform domain adaptive filters is addressed. Recent results have shown that if the input data to a radix-2 fast Fourier transform (FFT) structure is sliding one sample at a time, only N-1 butterflies need to be calculated for updating the FFT structure, after the arrival of every new data sample. This is opposed to most of the previous reports that, assume order of N log N complexity, for such implementation. In this paper the sliding implementation of the other useful transforms, that can also be implemented with the order of N complexity, are worked out in detail.>

The variable step size least mean square (VSLMS) algorithm is explored further and adopted for tracking of time varying environments. Two implementations of the VSLMS algorithm are proposed. Our emphasis is on the implementations with different step sizes at various taps of the adaptive filter. For an application where the adaptive filter is used to track a time varying plant, it is shown that the step sizes of the VSLMS algorithm converge towards their optimum values. Simulation results that support the developed theories are also presented.>

A low complexity high selectivity fast filter bank (FFB) which does not involve down-sampling and up-sampling of signals has been developed. Since a single sampling rate is used throughout the filtering process, aliasing problem does not exist. The FFB was derived from the FFT. In this paper, we present an alternative derivation for the FFB. This alternative derivation renders detailed analysis of the performance of the FFB possible. This in turn leads to the optimum design of the FFB. In this paper, we also show by means of an example that the computational complexity of the FFB is significantly less than that of a single rate polyphase filter.>

The performance of the transform domain normalized least mean square (LMS) algorithm is studied. The discussion is limited to the systems that employ an orthogonal transform to convert the incoming samples to a set of partially uncorrelated components, to be used as input to an adaptive linear combiner. To obtain an effective mathematical tool for analysis of the LMS-type algorithms a new performance index is proposed. The proposed index is used to derive many useful results. It is shown that a thorough understanding of the filtering concept results in many rules of thumb that can be readily used for choosing near-optimum transformations in the cases when partial information of input statistics is available. It is shown that the KLT (Karhunen-Loeve transform) implements a set of parallel filters which is optimal in the sense that it fulfils the conditions imposed by the filtering concept.>

A timing recovery scheme based on the maximization of the spectrum of the sampled received signal at the frequency of f-=1/2T is proposed. The quadrature amplitude modulated data signals are considered. Algorithms for both initial adjustment of the timing phase and its tracking during transmission of actual data bits are developed. The algorithms are tested by computer simulations for a typical telephone line channel. It is shown that the proposed scheme is quite robust with respect to channel impairments such as noise and phase jitter and also with respect to the correlation to the transmitted data symbols.>