The utilization of pure space-division multiple access (SDMA) in mobile communications systems relies on the assumption that the array propagation vectors of different user equipments (UEs) differ by a minimum angle to obtain reasonable propagation conditions. However, when serving several UEs, this hypothesis does not hold with probability one, especially for channels with a strong line-of-sight (LOS) component, and it is beneficial w.r.t. maximizing the sum rate to switch to a different, truly orthogonal, multiple access scheme like time-division multiple access (TDMA) or frequency-division multiple access (FDMA). In this work, we use the array propagation vector correlation of two UEs to decide whether the utilization of pure SDMA is advantageous. For this reason, we derive an optimal analytical decision threshold based on this correlation for a two UE scenario. In addition, we extend this criterion numerically to find a practical decision criterion for the assignment of transmission groups in multi UE scenarios for a hybrid SDMA/TDMA approach and apply a linear-model based estimation approach.

With the rise of the sixth generation (6G) and the use of frequency range 3 (7.125-24.25 GHz) (FR3) centimeter wave (cmWave) bands, interference-limited environments due to the coexistence of multiple incumbents are becoming increasingly common. This emphasizes the need for effective interference management without sacrificing time and frequency resources. In multi-cell, multi-user scenarios, beam selection is crucial in reducing interference, particularly in non-orthogonal space division multiple access (SDMA) systems. This paper explores interference mitigation for multi-panel user equipment (MPUE) in coexisting FR3 networks with the help of beam selection mechanism. Numerical simulations showcase the gains in spectral efficiency and fairness achieved through this approach.

Millimeter-wave (mmWave) hybrid analog-digital beamforming is a promising approach to satisfy the low-latency constraint in multiple unmanned aerial vehicles (UAVs) systems, which serve as network infrastructure for flexible deployment. However, in highly dynamic multi-UAV environments, analog beam tracking becomes a critical challenge. The overhead of additional pilot transmission at the price of spectral efficiency is shown necessary to achieve high resilience in operation. An efficient method to deal with high dynamics of UAVs applies machine learning, particularly Q-learning, to analog beam tracking. The proposed Q-learning-based beam tracking scheme uses current/past observations to design rewards from environments to facilitate prediction, which significantly increases the efficiency of data transmission and beam switching. Given the selected analog beams, the goal of digital beamforming is to maximize the SINR. The received pilot signals are utilized to approximate the desired signal and interference power values, which yield the SINR measurements as well as the optimal digital weights. Since the selected analog beams based on the received power do not guarantee the hybrid beamforming achieving the maximization SINR, we therefore reserve additional analog beams as candidates during the beam tracking. When the candidates include the ideal beams, the combination of analog beams with their digital weights achieving the maximum SINR consequently provides the optimal solution to the hybrid beamforming.

A robust and adaptive variable length beam selection strategy based on M-ary sequential competition was proposed. It was enhanced by the elimination of inauspicious beams during the ongoing competition to improve the efficiency and speed of the training. In this paper, we refine the elimination process by introducing a new elimination mechanism based on estimated winning probability i.e. probability of being the strongest candidate for each beam at each time step. These probabilities are calculated using sequentially estimated a posterirori PDFs of the unknown signal amplitudes after beamforming. This way least promising beams that fail to promise a minimum predefined winning probability can be eliminated from the remaining candidates as early as possible.

This work focuses on the initial beam acquisition/alignment of millimeter wave (mmWave) communication systems. To detect the angle of arrival (AoA) and/or angle of departure (AoD), we propose a training protocol which probes all beamformers from a given codebook simultaneously by exploiting the sparse nature of mmWave channels. By applying a frequency-selective beam probing network, we can map each beamformer from the codebook to different frequencies and a spectral analysis at the receiver allows us to deduce favorable beamformers or AoDs. For practical reasons, we elaborate this idea of steering direction to frequency mapping for an orthogonal frequency division multiplexing (OFDM) communication system, i.e., we map each beamformer to specific pilot subcarriers. Under two different hardware designs, we investigate the feasibility of building such beamformer to frequency mappings for one additional radio frequency (RF) chain next to an existing OFDM communication system. We show that parallel beam training is able to achieve better effective transmission rates than exhaustive search in fast-time varying environments due to high temporal efficiency. This is crucial for mmWave communication systems which have access to large beamforming codebooks but suffer from short coherence times due to mobility and high spatial resolution.

The beam selection problem is one of the crucial problems for achieving high spectral efficiency in millimeter wave (mmW) systems. Most of the previous works use heuristic algorithms with fixed training length to solve this problem, without considering the optimal length of the training sequence. Thus the training length is often over-designed. In this paper, we show that beam selection by exhaustive search can be interpreted as an M-ary hypothesis test, where the optimal training length can be found using the formula of the selection probability. Using this relation, we design two algorithms based on composite hypothesis test theory to determine the optimal training length. Simulations show the applicability of this approach.

We present a novel M-ary sequential test for beam selection when knowledge about the SNR operating point is not available. The proposed sequential test adaptively changes the test length (the number of observations) according to the SNR operating point to achieve the desired performance. Moreover, to achieve the same performance in terms of captured signal power, the sequential competition test requires on average less observations (particularly in the lower SNR regime) in comparison to a perfectly tuned fixed length test assuming genie knowledge.

In this paper, we show a novel algorithm for strong line-of-sight (LoS) multiple-input-multiple-output (MIMO) channel equalization. With optimally spaced antennas under specific arrangements, the LoS channels can be made spatially orthogonal. In practice, antenna displacements are expected. Conventional algorithms like zero-forcing (ZF) do not consider the special properties of the LoS MIMO channel and result in high complexity. We show that the LoS MIMO channel can be factorized into a product of three matrices. Thereby, the two diagonal matrices at the outer product positions are the most varying terms and should be compensated dynamically. Being a good tradeoff between complexity and robustness, the proposed sequential channel equalization is applied in a reverse order of the factorization. The algorithm can be applied to LoS MIMO systems with uniform linear or rectangular arrays, which are making use of digital or analog equalization. By considering the usage of the Winograd butterfly and Butler matrices, the number of multiplications in both digital and analog implementations of the proposed solution is increasing approximately linearly with respect to the number of antennas, while the complexity of the state-of-the-art designs grows quadratically. As found numerically and verified experimentally, the proposed method performs nearly as well as the ZF-based algorithms with near-optimal arrangements, while having significantly lower complexity.

Multi-beam selection is one of the crucial technologies in hybrid beamforming systems for frequency-selective fading channels. Addressing the problem in the frequency domain facilitates the procedure of acquiring observations for analog beam selection. However, it is difficult to improve the quality of the contaminated observations at low SNR. To this end, this paper uses an idea that the significant observations are sparse in the time domain to further enhance the quality of signals as well as the beam selection performance. By exploiting properties of channel impulse responses and circular convolutions in the time domain, we can reduce the size of a Toeplitz matrix in deconvolution to generate periodic true values of coupling coefficients plus random noise signals. An arithmetic mean of these signals yields refined observations with minor noise effects and provides more accurate sparse multipath delay information. As a result, only the refined observations associated with the estimated multipath delay indices have to be taken into account for the analog beam selection problem.

Hybrid beamforming is a promising concept to achieve high data rate transmission at millimeter waves. To implement it in a transceiver, many references optimally adapt to a high-dimensional multi-antenna channel but more or less ignore the complexity of the channel estimation or the effort for the subsequent step of computing the singular value decomposition of the channel matrix. Realizing that received coupling coefficients of the channel and pairs of possible analog beamforming vectors on both sides can be used for analog beam selection, we further propose a low-complexity scheme that exploits these implicit channel knowledge to implement hybrid beamforming. The estimates of these coupling coefficients yield alternatives of effective channel matrices of much lower dimension. After calculating the Frobenius norm of these effective channel matrices, it turns out that the effective channel having the largest value of the Frobenius norm provides the solution to hybrid beamforming problem.

The steadily increasing demand for higher data rate in mobile communications has recently attracted attention to frequencies above some 10 GHz also known as millimeter wave (mmW) communications. However, to compensate the higher path loss antenna arrays are mandatory so that efficient beam alignment algorithms are important to make mmW communication feasible in practice. Furthermore, to keep cost and complexity within acceptable limits, imperfections of analog beam forming have to be handled with appropriate signal processing in digital baseband. To address this scenario we describe a robust beam alignment algorithm and illustrate its performance both by simulation and experiments using a real-time prototype system operating at 60 GHz.

With large bandwidths, millimeter wave (mmWave) line-of-sight (LoS) multi-input multi-output (MIMO) technology employing parallel stream transmission is well suited for future wireless backhaul systems. However, hardware imperfections of mmWave transceivers cause additional signal processing challenges. Considering the channel and hardware properties, this paper proposes a novel frame structure with high temporal efficiency. The required MIMO processing can be decomposed into two steps. The first one removes the interantenna interference including the carrier frequency offsets. In the second step, the intersymbol interference brought by the frequency-selective components is canceled with a parallel structure. As a comparison, a more general decision-directed least-mean-square approach (DD-LMS) for joint processing of all effects is introduced. With a 60 GHz 2 × 2 LoS MIMO demonstrator, only the widely linear version of DD-LMS achieves performance of about 0.2-0.6 dB better than the proposed method but requires approximately four times more complexity. The proposed method with parallel processing chains is well suited especially for larger LoS MIMO systems, e.g., for a system with 16 streams, its required complexity is less than 7% of the widely linear DD-LMS.

Spatial multiplexing is an important factor usable for improving the throughput of future millimeter-wave (mm-wave) backhaul links. One conventional strategy in mm-wave multiple-input multiple-output (MIMO) systems uses densely packed antennas and exploits the spatial signature of multiple paths. Meanwhile, spatial multiplexing over a single line-of-sight (LoS) path, known as LoS MIMO communication, offers an alternative option with widely spaced antennas exploiting the phases of spherical waves. In this paper, we first show that those two conventional approaches exploit two different degrees in the channel matrices, which we denote as inter- and intra-path multiplexing, respectively. Then, we show that the two kinds of spatial multiplexing can be jointly exploited and identify their different requirements on system design. Fulfilling all requirements simultaneously, we propose a system with multiple widely spaced subarrays. With the help of analog beamforming, the intra-path multiplexing of conventional LoS MIMO systems can be introduced to other non-LoS paths owing to its robustness. Merging the two kinds of spatial multiplexing in a combined channel model and connecting it with a hybrid beamforming architecture, the proposed system achieves spatial multiplexing of a higher order than conventional ones. Simulation results for a backhaul scenario illustrate that the channel of the proposed method has higher ranks than that of conventional approaches.

Combining analog with digital beamforming in the sense of hybrid beamforming is one of the promising solutions to maximize throughput for millimeter wave links. Due to a concern of complexity, codebooks used in the analog beamforming are limited to their size. This paper shows that if the limited codebooks are made up of orthogonal steering vectors, the analog beamforming can be implemented with low complexity by exploiting implicit knowledge of the channel and then the resulting effective channel should be estimated explicitly to determine the optimal weighting coefficients in the digital beamforming. The simulation results show that the proposed low-complexity beamforming method can achieve nearly the same data rates as the one with perfectly known channel state information.

In this work we show that the analog equalizing networks are suitable for low resolution quantization with limited mutual information loss in strong line-of-sight MIMO communication. More specifically, a simplified analog equalizing network design in comparison with state-of-the-art works is proposed in this work. Additionally, the new network design works equally good for larger displacement ranges. Furthermore, by using analog equalizing networks in line-of-sight MIMO systems, it is shown that the drawbacks of low resolution quantization can be minimized. This increases the energy efficiency of the analog-to-digital converters via minimizing the required magnitude resolution. Generally, low resolution quantization causes low entropy on the receive vectors which will effectively reduce the mutual information of the desired transmission. The analog equalizing network reshapes the distribution and reduces the dynamics of the received signals in the complex constellation plane before quantization. Therefore, the entropy loss after low resolution quantization is reduced and the system performs essentially as good as a system with higher resolutions. Finally, an algorithm is proposed to remove ambiguities which arise after analog-to-digital conversion with a given low resolution.

In this work, we show a new design of analog equalizing network for N-stream strong Line-of-Sight MIMO communication, aiming at improved robustness. The design includes a core fixed equalizing network that equalizes ideal spatially orthogonal channels. Existing works show that the fixed equalizing network can equalize a spatially orthogonal MIMO system with parallel arrays. However, it is observed that such a fixed equalizing network is very sensitive to displacement errors. To make the system robust, state-of-the-art approaches use N2 fully controlled analog elements to perfectly equalize the channel via aligning the structured interferences. In this work, the terms causing the sensitiveness of fixed analog equalizing networks are identified. By compensating the tackled sensitive terms, the proposed design uses only 2N fully controlled analog elements and the robustness of the system is improved significantly. Meanwhile, by exploring the channel property, this work shows that if the spatially orthogonality is achieved by uniform rectangular arrays, the equalization can be applied with a new two-stage scheme. The scheme can be applied to spatially orthogonal MIMO systems with digital and/or analog equalization. Meanwhile, the computational complexity, required components number, as well as the complexity of the hardware design are significantly reduced.

Efficiently estimating spatial channel properties, such as angles of arrival and departure, for a hybrid beamforming (HBF) architecture is one of the crucial challenges to overcome at millimeter wave (mmW) systems. To this end, we propose an algorithm variant to a recently proposed approach [8] based on ideas borrowed from the compressed sensing literature and /0-norm minimization, which exploit the fact that the number of significant channel echoes is rather small for limited beamwidth. Our modified algorithm eliminates high dimensional singular value decomposition (SVD) of the estimated channel matrix in the original method by employing the orthogonality between the selected array propagation vectors. It is demonstrated that HBF design without SVD of the estimated channel matrix can achieve essentially the same capacity as the one with SVD. Moreover, the feedback overhead required for the beamforming systems can be significantly reduced by the proposed method.

For next-generation wireless networks, massive multiple-input multiple-output (MIMO) promises significant performance gains compared to today's wireless communication standards. In this paper, we address the challenge of how to synchronize the carrier signals of all antenna units in a large network. We show that mutually coupled digital phase-locked loops (DPLLs) can enable in-phase synchronous clocking in largescale systems with transmission delay. Using a phase model of coupled DPLLs including signal filtering and signal transmission delays, we show how the collective frequency and the time scales of synchronization depend on system specifications. To test our theoretical predictions, we designed and carried out experiments, thereby providing a proof-of-principle that mutually delay-coupled DPLLs can provide self-organized synchronous clocking.

We present a simple but efficientalgorithm that iteratively refines the channel estimate in a turbo equalizer exploiting soft feedback (a-posteriori likelihoods) from the decoder. This algorithm, denoted as 'Soft Interference Cancelation and Correlation' (SICC), repeatedly performs an interference cancelation step followed by correlation with symbol estimates derived from the output of the decoder. The novelty lies in two facts: first, the moments of the likelihood ratio density at the decoder output are used to remove the bias of the estimate. Second, an iterative version (I-SICC) is proposed where a data block is evaluated repeatedly without activation of the channel decoder. It is shown that this variant significantly outperforms its non iterative version.

We propose a quantization scheme for log-likelihood ratios which optimizes the trade-off between rate and accuracy in the sense of rate distortion theory: as distortion measure we use mutual information to determine quantization and decision levels maximizing mutual information for a given rate over a Gaussian channel. This approach is slightly superior to the previously proposed idea of applying theLloyd-Maxalgorithm to the dasiasoft bitpsila density associated to theL-values. A further data rate reduction can be achieved withentropycoding, because the optimum quantization levels based on mutual information are used with pronounced unequal probabilities.

We present a blind turbo equalizer for QAM signals that exploits the statistics that a channel code imposes on the transmitted signal. The receiver is an adaptation of previous work presented in [1], where a BPSK signal is encoded by a binary code and blindly recovered in a turbo way. The main concept is to exploit the constraints imposed by the parity check equations of the code on the transmitted sequence for estimating the channel. Two algorithms are presented: the first one blindly estimates the channel without feedback of the channel decoder and the second one iteratively refines the channel estimation using the soft feedback of the channel decoder. The performance of the proposed system is encouraging. It shows that our blind channel estimator can reach the same BER as a Turbo equalizer with perfect channel knowledge of the channel impulse response.

We present a blind turbo equalizer for pulse amplitude modulation (PAM) signals that exploits the statistics that a multilevel code imposes on the transmitted signal. The receiver here is an adaptation of previous work presented in A.F. Santos, et al, (2008), where a BPSK signal is encoded by a binary code and blindly recovered in a turbo way. The main concept is to exploit the constraints imposed by the parity check equations of the code at the transmitted sequence for estimating the channel. Here multilevel codes are used for imposing the necessary constraints on a PAM signal for blind channel estimation. The performance of the proposed system is encouraging. It shows that our blind channel estimator gets close to the same BER of the turbo equalizer with perfect channel knowledge.

In this paper we discuss the effect of phase noise at both, transmitter and receiver in an OFDM system. We study an iterative equalization system at the receiver. The system is based on a joint linear MMSE estimation of the transmitter and receiver phase noise. We propose a receiver module which can be considered as a serial concatenation of an outer decoder with an inner phase noise correction/metric computation block. For intercarrier interference (ICI) suppression we introduce a method to only use the most reliable decoded symbols, which results in a significant performance improvement. The performance is shown by simulation results for different oscillator qualities and an ETSI HiperLan A channel.

The peak to mean envelope power ratio (PMEPR) problem in multicarrier communications can be significantly reduced, if one of several alternative transmit sequences can be selected. We propose to combine this so-called 'SelectedMapping' approach with the design of low density parity check (LPDC) codes which contain particular sequences within their code space and construct the respective parity check matrices with a variant of the 'ProgressiveEdgeGrowth' algorithm. This allows not only to exploit the power of LDPC codes, but also the simple generation of the transmit alternatives due to the linearity of the code and incorporation of explicit side information due to an invariant segment common to all used sequences.

Clipping and filtering is an attractive method for the reduction of the PAPR of OFDM signals before transmission. However, the resulting in-band distortion noise impacts the error rate performance. Since the optimum soft iterative equalization scheme has a prohibitively high computational complexity, we present two equalization algorithms for clipped and filtered COFDM signals with reduced complexity. The coded frame error rate (FER) performance over both AWGN and frequency-selective fading channels is evaluated for typical OFDM system parameters.

A very promising way to achieve high spectral efficiency in wireless communication is the use of multiple transmit and receive antennas. However, in combination with multicarrier modulation, e.g. MIMO-OFDM, the performance of such a system can be drastically limited due to the existence of RF imperfections such as oscillator phase noise. Many methods for phase noise compensations in a single antenna environment have been developed, whereas only a few deal with the problem in a MIMO case. Those contributions mainly discuss the common phase error (CPE) correction. In this work we extend the CPE correction and perform a linear minimum mean square error (LMMSE) estimation of higher order phase noise harmonics in order to compensate intercarrier interference (ICI) in a multi antenna system. In a coded multi antenna environment it is common to perform detector-decoder iterations which lead to an improved performance behavior. During the iterations we use the a-priori knowledge provided by the decoder to improve the phase noise estimation. This is done by using only the most reliable symbols for performing the LMMSE estimate. As for the detection we use a simple MMSE equalizer where we use the general expression and adapt the noise covariance matrix according to the remaining ICI. Finally the performance is shown by simulation results for an IEEE 802.11n E channel.

A preamble technique for synchronization and channel estimation introduces transmission delay and wastes capacity unavoidably due to the time loss before data transmission. In this paper, we optimize a complete iterative receiver algorithm for different preamble lengths and study the feasibility to reduce the preamble length in OFDM-WLAN. The results show that - as expected - the preamble technique with reduced length offers worse synchronization and channel estimation versus SNR. However they also show that the preamble can be reduced compared to current standards to a minimum of three short repeated preamble sequences providing higher throughput regardless of modulation schemes. This is of particular interest, if an OFDM-WLAN system has non-negligible amount of bursty traffic and operates at high SNR.

A novel scheduling for turbo equalization with turbo decoding is proposed. The use of turbo codes associated to turbo equalizers has been frequently investigated in the literature. The conventional turbo equalizer with turbo decoding consists of a soft input soft output equalizer cooperating with a turbo decoder. In this way, the turbo decoder performs several iterations at each turbo equalizer iteration. The proposal here is a new scheduling procedure for the association of an equalizer and a turbo decoder. At each turbo equalizer iteration, only the decoding of a single component code of the turbo code is performed. The component decoders are connected through the turbo equalizer iterations, in such a way that when two turbo equalizer iterations are executed, a complete turbo decoding iteration is performed. The advantage of this system lies in the complexity reduction, since its complexity is given by the sum of the complexity of the equalizer with only a single component decoder.

Clipping and filtering is an attractive method for the reduction of the PAPR of OFDM signals before transmission. However, the resulting distortion noise impacts the error rate performance. An iterative receive algorithm employing soft modulation and soft input-soft output (SISO) decoding is presented, and its coded frame error rate (FER) performance over both AWGN and frequency-selective fading channels is evaluated. The performance of an approach with reduced complexity is also shown.

Space-time block codes (STBC) from orthogonal designs have been proposed by Alamouti and Tarokh-Jafarkhani-Calderbank, achieving full diversity in the order of the number of transmit antennas. However, orthogonal STBC always result in a symbol rate less than one, if complex symbols are transmitted from more than 2 antennas. Jafarkhani, Tirkkonen-Boariu-Hottinen and Papadias-Foschini have suggested to use quasi-orthogonal STBC (QO-STBC), and it has been shown by various authors that these schemes achieve transmission rate 1 and full diversity, if selected symbols are chosen from suitably rotated constellations. The schemes can, however, lead to a high detection complexity, which has been recently addressed through co-ordinate interleaved orthogonal designs (CIOD) and minimum detection complexity (MDC) QO-STBC, though leading to a slight degradation in performance. In this paper, we present a novel QO-STBC scheme that uses stretched, i.e. non-linearly preprocessed symbol constellations, achieving full diversity and a performance comparable to that of CIOD and MDC, while further reducing detection complexity.

In this paper, we propose an algorithm for suppressing intercarrier interference due to phase noise in coded orthogonal frequency division multiplexing (OFDM) systems. The algorithm approximates the phase-noise waveform by using a Fourier series approximation for the current phase-noise realization. Thereby, it cancels the effects of the phase noise beyond the standard common phase error correction used in contemporary OFDM standards. The algorithm requires that the correlation properties of the intercarrier interference are known. We calculate these properties in terms of the phase-noise spectral correlation matrix for bothWienerandOrnstein-Uhlenbeckphase-noise models, respectively. This modeling corresponds to a free-running oscillator, as well as a phase-locked loop realization of the local oscillator in orthogonal frequency division multiplexing transceivers. For both transceiver configurations, we investigate the performance of the proposed algorithm. It is demonstrated that the new algorithm achieves as much as one order of magnitude better performance in terms of packet/bit error rate when compared to a receiver with only the common phase error suppression.

Near-capacity performance can be achieved in multiple-antenna systems by using a list sequential (LISS) detector for iterative equalization. Path augmentation is known to increase the performance of this detector, while a so-called bias term has been used to reduce its computational complexity, in applications other than MIMO detection. In this work, we extend the LISS MIMO detector [1] to incorporate different implementations of the bias term. We show that following the traditional approach of using an auxiliary stack for this purpose leads to a strong narrowing of the search tree, but also to a significant performance degradation, due to a reduced quality of the detector soft output. We therefore propose to use a so-called noise bias term instead, which can be implemented with negligible effort, significantly reduces the size of the search tree, but allows for almost retaining detector performance. Finally, we demonstrate that the extension of only a small fraction of the incomplete stack entries is sufficient to leverage the full gains of path augmentation, thus enabling further substantial savings in computational complexity.

A preamble technique is used in present OFDM-based WLAN systems to accomplish synchronization and channel estimation. The preamble introduces transmission delay and wastes capacity, especially when a data packet is short. An alternative is a superimposed pilot technique which can provide similar BER vs. Eb/N0 performance by specially designed receiver and optimized system parameters. In this paper we study the conditions under which superimposed pilots can be successfully used for jointly estimating the channel and detecting data. It is shown that the transmission delay or throughput of wideband WLAN systems can be significantly improved when such a technique is employed at the price of higher complexity due to the iterative receive algorithm.

We present a unified analysis of intercarrier interference (ICI) which is caused by phase noise in OFDM. The "small" phase noise approximation known from the literature is dropped and analysis applies to a general phase noise model. The power of intercarrier interference is calculated in two ways, namely using an integral form and using an ICI correlation matrix which we also derive. As two special cases, the Wiener and Orastein-Uhlenbeck phase noise models, which are typical for free-running and PLL synthesizer realizations of the local oscillator, respectively, are presented. Closed form expressions of the respective powers are calculated. We show that these theoretical considerations fit well to numerical experiments. The calculated ICI distribution show that ICI cannot be approximated by a Gaussian random variable for a wide range of phase noise strengths contradicting the usual assumptions on the ICI.

The implementation challenge for new low-cost low-power wireless modem transceivers has continuously been growing with increased modem performance, bandwidth, and carrier frequency. Up to now we have been designing transceivers in a way that we are able to keep the analog (RF) problem domain widely separated from the digital signal processing design. However, with today's deep sub-micron technology, analog impairments-dirt effects-are reaching a new problem level which requires a paradigm shift in the design of transceivers. Examples of these impairments are phase noise, non-linearities, IQ imbalance, ADC impairments, etc. In the world of dirty RF we assume to design digital signal processing such that we can cope with a new level of impairments, allowing lee-way in the requirements set on future RF sub-systems. This paper gives an overview of the topic and presents analytical evaluations of the performance losses due to RF impairments as well as algorithms that allow to live with imperfect RF by compensating the resulting error effects using digital baseband processing

Orthogonal frequency division multiplexing (OFDM) has already become a very attractive modulation scheme for many applications. Unfortunately OFDM is very sensitive to synchronization errors, one of them being phase noise, which is of great importance in modern WLAN systems which target high data rates and tend to use higher frequency bands because of the spectrum availability. In this paper we propose a linear Kalman filter as a means for tracking phase noise and its suppression. The algorithm is pilot based. The performance of the proposed method is investigated and compared with the performance of other known algorithms.

A novel approach to multiuser transmission (MUT) for the CDMA downlink in frequency-selective channels is proposed. The key idea is to minimize the BER at the receivers directly by pre-distortion of the transmitted symbols. The BER can he predicted in the transmitter In calculating the signal at the receiver (including interference) exactly and treating only the additive noise at the receiver statistically. Using state-of-the-art nonlinear optimization methods like SQP (sequential quadratic programming), the BER minimizing pre-distortion coefficients can be found. Simulations compare the proposed scheme with the RAKE matched filter and linear transmitter preprocessing schemes, like joint transmission. The proposed MUT scheme can be applied for instance in the 3GPP-TDD and the TD-SCDMA standards, where the channel impulse response is known in the transmitter due to channel reciprocity.

The paper investigates the possibility of reusing frequencies of a terrestrial digital video broadcasting (DVB-T) network for a UMTS Terrestrial Radio Access Network (UTRAN) with negligible influence on the DVB-T performance. A frequency division duplex (FDD) UTRAN is deployed such that it can reuse all frequencies of the DVB-T network in each DVB-T frequency reuse cluster in the downlink, with a predefined level of (negligible) interference from the UTRAN to DVB-T. The downlinks of both networks can thus coexist in the same frequency spectrum, thereby increasing the spectral efficiency. The uplink of UTRAN-FDD is assumed to operate in traditional non coexistence and is therefore not considered. Close to 100% of the capacity of a non coexisting UTRAN are achievable for typical UTRAN cell sizes, with only marginal increase of outage in the DVB-T network.