We consider the optimization of coded continuous phase modulation (CPM) systems operating at the spectral efficiencies 0.5bps/Hz, 1.0bps/Hz, 1.5bps/Hz and 2.0bps/Hz. Due to the difficulty of defining an analytic fitness function and the discreteness of the CPM parameters, we opt for an evolutionary optimization, which easily deals with such limitations. We apply a bi-objective instance of the non-dominated sorting genetic algorithm II (NSGA-II) where the mutual information between the transmit bits and soft bits at the output of the CPM detector as well as the complexity are taken as objective functions. This enables us to quantify the trade-off between complexity and performance. The results show that for all considered spectral efficiencies, the best schemes are usually quaternary or octal with a frequency pulse length not exceeding 2 symbol durations and a code rate ranging between 0.7−0.8.

The application of short burst transmission, e.g. in frequency hopping systems requires a repeating acquisition of channel impairment parameters. In this work, a blind joint timing and carrier phase estimation of continuous phase modulation bursts is realized by the expectation maximization algorithm. The main contribution is the formulation of the expectation and maximization steps to enable an efficient computation and a simple joint maximization of the parameters, respectively. The joint estimator's performance in terms of the mean square error is shown to achieve the theoretical limits, i.e. the modified Cramér-Rao-Vector-Bound and is compared to the perfectly synchronized receiver in terms of bit and frame error rates. Its computational complexity is discussed qualitatively and some approaches are mentioned to decrease it further.

In this work, the continuous phase modulation (CPM) with short block lengths (up to 128 symbols) is considered as a waveform, which is used e.g. in tactical networks. In order to deploy an optimal coherent detector, among other parameters as e.g. carrier phase or symbol timing, the carrier frequency has to be estimated. It is proposed to use the expectation maximization algorithm (EM) for a maximum likelihood estimation. It is pointed out why finding a suitable starting value, so that the EM does not converge to a local maximum of the likelihood function, is non-trivial in this case. Based on the insights given on the likelihood function in this case, an algorithm to tackle that issue and to ensure convergence to the global maximum is formulated. The algorithm's performance is evaluated in terms of estimation error variance, including a comparison to the theoretical limit, and in terms of bit error rate, where it is compared to the perfectly synchronized receiver. The algorithm's robustness against unknown carrier phase is investigated and its computational complexity is reflected.

The benefits of continuous phase modulation (CPM), namely high power and spectral efficiencies, are often overshadowed by the high complexity that comes along with the nonlinearity of the modulation format. We tackle the problem of detection of a quaternary CPM signal in a frequency-selective fast fading channel. In particular, we derive a joint detector-equalizer using the Laurent principal pulse approximation. To handle time-selectivity, we adopt the well-known turbo-estimation approach. However, it turns out that classical turbo-estimation cannot be directly applied, but has to be modified beforehand. With the help of Monte Carlo bit error rate (BER) simulations, we show that using the modified turbo-estimation approach, the receiver is able to track channel variations within a transmit burst under fast fading conditions. This allows for a larger payload-to-overhead ratio. Since joint detection-equalization is practically feasible only for channels with short memory, we also consider a suboptimal approach which decouples detection from equalization.

We consider the detection of short continuous phase modulation (CPM) bursts in a frequency-selective fading channel. The conventional solution comprises training-aided channel estimation followed by coherent detection. However, the performance of the coherent detector is optimal only when the channel is perfectly known, which is practically never the case. In practice, the performance is limited by the quality of the channel estimate. This poses a problem for short bursts, where the number of training symbols must be kept low. When the channel is unknown, the optimal receiver uses available a priori stochastic information to marginalize the channel out of the likelihood function and determine the transmit sequence that maximizes it. Due to the lack of a priori information and the high complexity associated with marginalizing out a multi-tap channel, we derive a suboptimal detector, which replaces the unknown channel by the conditional maximum likelihood (ML) estimate for each hypothesis transmit sequence. From that, we derive a noncoherent soft-input soft-output (SISO) symbol-by-symbol detector. Using Monte-Carlo simulations to estimate the bit error rate (BER), we show the superiority of the proposed approach over the conventional one, especially for extremely short bursts in a time-variant environment.

In this work, the continuous phase modulation (CPM) is considered as a waveform, which fulfills the constant envelope constraint and is already used e.g. in tactical networks. In order to deploy the optimal coherent CPM receiver, among other parameters the carrier phase has to be estimated, which is done in this work by means of the expectation maximization algorithm (EM). It is pointed out that CPM inherently avoids the phase ambiguity problem and a technique to ensure finding the global maximum of the phase likelihood function instead of a local one is proposed. The estimation performance is evaluated in terms of estimated phase variance with and without the proposed enhancement and compared to a feedforward estimator and a theoretical lower bound. The performance in terms of bit error rate is compared both to an incoherent and a perfectly synchronized coherent detector as well as to the feedworward estimator. This work focuses on burst-type transmission where rather short blocks (tens of symbols) are transmitted independently.

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.

This paper presents a low-complexity front-end for the demodulation of continuous phase modulation (CPM). We show that in the presence of strong adjacent channel interference (ACI), using more than one basis function for signal demodulation is not necessary, if not detrimental, at least for a wide range of CPM schemes. For additive white Gaussian noise (AWGN), it is known that the principal component analysis (PCA) yields the optimal truncated front-end. In the presence of strong ACI and a severe low-pass filter at the receiver input, we show that an elementary frequency domain approach (FDA) suffices to design a one-dimensional front-end which outperforms the one based on the first principal component in most practical cases.

In this paper we present measurement results for pure line-of-sight MIMO links operating in the millimeter wave range. We show that the estimated condition numbers and capacities of the measured channels are in good agreement with the theory for various transmission distances and antenna setups. Furthermore, the results show that orthogonal channel vectors can be observed if the spacing criterion is fulfilled, thus facilitating spatial multiplexing and achieving high spectral efficiencies even over fairly long distances. Spacings generating ill-conditioned channel matrices show on the other hand significantly reduced performance.

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.

A multiple-input multiple-output (MIMO) satellite communications system for fixed-satellite services (FSS) is considered. The MIMO Line-of-Sight (LOS) satellite channel is optimized to achieve maximum spectral efficiency. This requires an orthogonal MIMO channel matrix, ending up with large antenna spacing of the ground terminal antennas. As the main drawback, considerable propagation delays between the MIMO paths are observed, and the MIMO signal sub-streams interfere asynchronously in the order of several tens or hundreds of a symbol duration at the receiver. To cope with these delays, we propose a system architecture that uses a sufficiently large guard-interval or cyclic prefix between successive data blocks. The delay equalization at the receiver is then performed by a zero-forcing frequency domain equalizer for single-carrier transmission (SC-FDE). Thanks to the orthogonality of the considered MIMO channel, the SC-FDE architecture achieves even perfect spatial equalization of the multiplexed signal streams at considerably low implementation effort. The capacity reduction caused by the guard-interval is, moreover, mitigated by long data blocks, which can be used because of the long channel coherence times in FSS applications. The system concept reveals superior BER and transinformation performance, which is verified through fair comparison with current single-input single-output (SISO) systems. If the channel orthogonality is violated through narrow antenna spacing, the system performance degrades dramatically.

The bandwidth efficiency of Multiple Input - Multiple Output (MIMO) channels with different antenna arrays is analyzed. MIMO channels with a strong and unobstructed line-of-sight (LOS) signal component are considered, as it is the case in indoor in-room scenarios. The bandwidth efficiency of such channels is strongly dependent upon the applied antenna array and its orientation. Simulations of the pure LOS channel without multipath components are carried out to demonstrate this effect. So called polyhedron antenna arrays with antenna elements mounted on the faces of a regular polyhedron as well as the MIMO Cube deliver a bandwidth efficiency that is almost invariant from rotations of the antenna arrays. The measurement results verify this result. Polyhedron arrays appear to be a good alternative for MIMO systems, as the measured bandwidth efficiency of a polyhedron array is comparable to this of an uniform linear array (ULA), while the standard deviation is reduced to a large extend.

We present a channel-matched coding method for the compensation of dispersion in coarsely quantized coherent optical communication systems. The approach consists in optimizing a subset of equiprobable input symbols for each channel state, which is robust against dispersion and coarse quantization. This codebook optimization is solved efficiently using an iterative algorithm. The performance of the channel-matched codes is simulated for a 42.8Gbit/s dual-polarization coherent optical fiber system with QPSK modulation and single-bit analog-to-digital (A/D) conversion. Apart from the optimization, the proposed coding method does not increase the encoding/decoding complexity, but yields a considerable coding gain.

We investigate the impact of atmospheric impairments on the theoretical bandwidth efficiency of Multiple-Input Multiple-Output (MIMO) geostationary satellite links which are shaped to optimize the channel bandwidth efficiency. We analyze the impairments caused by precipitation, since this is the most severe atmospheric effect causing capacity degradations. By theory, the MIMO channel capacity is strongly affected by signal attenuation as well as signal phase shifts that might reduce the number and strength of spatial subchannels (eigenmodes). We will show, however, that the characteristics of the phase disturbances prevent a loss of capacity. Regarding the additional attenuation, which the signals may encounter passing through the troposphere, we will quantify outage values for several levels of link capacity degradation. Although a loss of capacity cannot be avoided in total, it still turns out that MIMO systems outperform conventional Single-Input Single-Output (SISO) designs in terms of reliability. Even in the presence of atmospheric perturbations, MIMO systems still provide enormous capacity gains and vast reliability improvements. Thus, the MIMO satellite systems presented are perfectly suited to establish the backbone network of future broadband wireless standards (e.g. DVB-SH), supporting high data rates for a variety of worldwide services.

The bandwidth efficiency of Multiple Input - Multiple Output (MIMO) channels is analyzed for point-to-point (P2P) and relay channels. The focus lies on channels with a strong and unobstructed line-of-sight (LOS) signal component between transmitter (Tx) and receiver (Rx), as it is the case in indoor in-room scenarios. The bandwidth efficiency of the resulting correlated P2P MIMO channel is strongly dependent upon the geometrical antenna setup. Especially the angle of arrival (AOA) and the inter-array antenna spacing of uniform linear arrays (ULAs) influence the bandwidth efficiency. Both influences are minimized by the use of distributed simple amplify-and-forward relay stations, while the resulting relay MIMO channel is correlated. In the relay case, the total transmit power spent at the Tx and the relay is limited to the transmit power of the Tx in the P2P case for a fair comparison. Relay stations are capable to enhance the bandwidth efficiency of the pure LOS MIMO channels, while the high bandwidth efficiency of channels with LOS and non line-of-sight (NLOS) signal components is not further increased in the considered scenario.

MIMO satellite links have recently attracted a high interest with respect to possible link capacity enhancements. In it has been shown that especially in Line-of-Sight (LOS) satellite channels maximum multiplexing gain can be achieved via the construction of orthogonal channels by means of the geometrical arrangement of the ground terminal antennae in relation to the antennae in orbit. Based on these theoretical results, we present practically relevant design and configuration examples for satellite communication systems, involving transparent pay loads for the first time. Thus, we significantly extend the results, that have been limited to regenerative payloads. The examples cover multiple-satellite and single-satellite MIMO scenarios. The assets and drawbacks of the applications are investigated, especially highlighting system-inherent design uncertainties.

We propose a fixed-effort MIMO decoder for frequency selective indoor channels that are characterized by strong line-of-sight (LOS) components. Contrarily to the maximum likelihood (ML) approach, where all possible hypotheses are investigated by the metrics calculation, the proposed MIMO detector performs the search over a reduced set of candidates. This search set contains a reduced but representative set of hypotheses around the linear solution obtained at the first detection stage. The candidates are selected according to pre-computed search probabilities. A decision feedback equalizer (DFE) is applied in order to remove the effect of the inter symbol interferences (ISI) caused by the channel dispersion. The method provides a near ML performance using a fixed computational effort determined by the hardware resources. The proposed detector also shows a significant complexity reduction compared to popular MIMO detectors such as the V-BLAST and the sphere decoder. Moreover, the proposed detector provides a soft output information for each transmitted bit, using the pre-selected candidates from the reduced search set which presents a promising aspect for the coded transmission.

Different multiple input - multiple output (MIMO) channel models are analyzed with regard to the indoor line-of-sight (LOS) MIMO channel. In the literature this channel is proven to achieve high capacities while being highly correlated. The modeling results from physical as well as analytical models are compared with measured channels, showing that none of the established models is exactly suitable for the considered indoor LOS MIMO channel. However, there is a promising approach that applies an extended Saleh model in conjunction with the physically correct spherical wave propagation. Although in its current state this basic approach cannot be regarded as a complete MIMO channel model, at least it provides an adequate origin for the correct prediction of MIMO capacities in different types of LOS channels. This is due to the fact, that the crucial prerequisites for an appropriate LOS MIMO channel model, which are by name the application of the physically correct spherical wave propagation, the correct modeling of the high correlation in LOS channels and the inclusion of the geometrical antenna setup, are regarded correctly. Contrarily, these prerequisites are included in none of the current models that are widely accepted in MIMO radio communications nowadays. The proof of this statement using measured data is a major objective of this paper.

A novel strategy of precalculating potential MIMO spectral efficiencies of correlated channels based on both, measured as well as appropriately modeled SISO channel impulse responses is presented. Besides capacity prediction, the model is capable of comprising the physical nature of the channel in form of its frequency response. The method is applied to indoor MIMO channels where the correlation is introduced mainly by a strong LOS signal component coinciding with low mobility. A spherical wave model is applied and the distributions of angle of arrival and angle of departure turn out to be important modeling parameters. The modeled MIMO capacities are compared to measured capacity records for verification, proving high accuracy.

This paper provides an approach to reach a near maximum likelihood performance, for MIMO systems, with a strongly reduced computational effort. This method is based on a two-step detection. The first detection step will be performed by using a MMSE equalizer and a subsequent decision unit The second step is a reduced search (RS) algorithm, that is applied only in a neighborhood of the detected symbols of the first step. For complexity reasons only the least reliable symbols are processed by the RS algorithm. The simulation results show that this MMSE RS detector outperforms the MMSE V-BLAST detector. It provides an improved performance using the same complexity.

A novel strategy for the modeling of indoor MIMO channels based on a spatial extension of appropriate SISO channel models is presented. The approach enables a precalculation of potential MIMO spectral efficiencies within a particular environment from the SISO channel information while taking into account the correlation of the MIMO channel. The objective measure is given by the spatial probability distribution of the MIMO capacity which is to be predicted correctly. The method is exemplified by Saleh's popular SISO indoor channel model. However, the approach is not limited to this SISO model. In order to practically verify the method, firstly, the key parameters for the SISO model are derived from measured data, before the extension to the MIMO channel model is performed. Finally, the spatial cumulative distribution function, which is predicted by the model is compared to its counterpart which was derived using a fast MIMO radio channel sounder. In the measurements a strong line-of-sight (LOS) signal component was always present resulting in correlated entries within the MIMO channel matrix. For the accurate capacity modeling in such correlated channels, the characterization of the LOS signal part by a spherical wave model is a crucial prerequisite.

The indoor MIMO line-of-sight (LOS) channel in theory strongly depends on the geometrical arrangement and spacing of the antennas at both, the transmitter as well as the receiver. Recently, theoretical directives have been presented [1] which enable the user to achieve high-rank LOS channels for linear antenna arrays which are oriented broadside to each other. The authors focus on proper phase angle relations within the entries of the channel transfer matrix, while neglecting the channel path loss in a first approach, and they consider the antenna spacings as the major degree of freedom for optimization. Contrarily, in practical indoor scenarios we consider the antenna array spacings to be fixed at the base station as well as the mobile unit and therefore they can be optimized for one particular transmitter-receiver distance at most. Furthermore, the free space path loss has to be taken into account as it causes huge SNR variations across an indoor environment. Thus, in this paper we try to apply the results in [1] to an exemplary real-world scenario observing the spatial capacity distribution as well as their variation. This way, we endorse the results in [1] by further design hints for practical MIMO systems using linear antenna arrays of arbitrary positioning.

We present broadband capacity snapshots as well as grid measurements derived with a fast 5times5 MIMO channelsounder in a typical, large-scale, non-mobile, in-room office scenario where we focus on line-of-sight (LOS) transmission channels. The accessible MIMO capacity is compared to its theoretic counterpart which would have been obtained if only the LOS signal without any reflections was considered. Our premise is to enable the user of quantifying the LOS signal's impact on the overall channel capacity for the particular scenario and coinciding to demonstrate the LOS's beneficial effect for the capacity. For a huge amount the beneficial effect of the LOS signal has to be ascribed to its receive signal power increase, an advantage which can hardly be balanced by any measures in the non-LOS case. The results generally indicate the overall capacity staying fairly high even for single channel matrix realizations and widely independent from the current geometric antenna assembly. Besides, strong variations over frequency are observed. These variations are shown to be slightly reducible by rising the number of antennas, but more efficient, larger bandwidths seem to be an appropriate measure for stabilizing the overall channel capacity per bandwidth unit

Digital radio systems employing multilevel QAM are at least optionally equipped with adaptive time- and/or frequency-domain equalizers. Their purpose is to reduce the vulnerability of these systems to linear distortion caused by multipath propagation. Linear transversal filters are prominent candidates for the realization of time-domain equalizers, especially for high-capacity applications. They are well known for their good performance and their relatively easy implementation at a high data rate. On the other hand, decision feedback equalizers are known to be very capable of eliminating linear distortion, especially of the so-called minimum-phase type. But realization problems are likely to occur in a high-speed application. A solution is proposed which merges the relative advantages of both the linear transversal and the decision feedback approaches. The goal of a frequency-domain equalizer, which is the restoration of the shape of the power density spectrum of the received signal without any recovered carrier and timing signals, can also be achieved with the aid of a transversal filter. The performance obtained with the joint utilization of the novel timeand frequency-domain equalizers is described.