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It is well known, that the Alamouti scheme is the only space-time code from orthogonal design achieving the capacity of multiple-input multiple-output (MIMO) wireless communication system with n(T) = 2 transmit antennas and n(R) = 1 receive antenna. In this work, we propose the n-times stacked Alamouti scheme for n(T) = 2n transmit antennas and show that this scheme achieves the capacity in the case of n(R) = 1 receive antenna. For the more general case of more than one receive antenna, we show that if the number of transmit antennas is higher than the number of receive antennas we achieve a high portion of the capacity with this scheme.

Energy, especially Electricity has become a critical concern of society. The generation and distribution are, to a large extent, not matched with each other. There are many initiatives to balance the load on the Grid vis-à-vis production and consumption. Recently, technology has made it possible to generate small amounts of energy in each household with solar, thermal, wind and other sources. With storage devices, it is possible to use the generated energy at the sources i.e., localized generation and consumption of energy. The system can be made efficient and possibly design a zero or positive-energy home with the use ICT infrastructure, wireless sensor networks, in particular. This paper proposes a three-layered architecture for this system and also lists several associated issues and challenges.

By means of DFT-precoding, the PAPR of OFDM waveforms can be reduced. DFT-precoding has been proposed for uplink transmission in various future wireless communication systems. In this work, we consider DFT-precoding combined with spatial precoding for the uplink of multiuser MIMO OFDM systems. An efficient algorithm is developed to optimize the spatial precoder aiming at maximization of the system sum rate subject to individual power constraints of the users and maintenance of the low PAPR property for one user. Potential gains are shown compared to other popular precoding methods in 3GPP-LTE uplink scenarios.

Recently, the statistical properties of the equivalent channel representation of a multiple-input-multiple output (MIMO) system employing code rate one quasi-orthogonal space-time block codes (QSTBC), which are constructed by using orthogonal space-time block codes (OSTBC) as building elements, was characterized. Based on these characterizations we analyze the average rate (or mean mutual information), the bit-error-rate performance, and the coding gain achieved with QSTBC for any number of receive and n(T) = 2(n), n >= 2 transmit antennas. First, we study constellation rotation using a systematic approach in order to maximize the coding gain and to achieve full diversity QSTBC. Moreover, we present an upper bound on the coding gain. We derive a lower and upper bound on the BER-performance for QSTBC. Furthermore, we analyze the average rate achievable with QSTBC in case of an uninformed transmitter and also the case, in which the transmitter knows the mean channel matrix whereas the receiver has perfect CSI. Along with the analysis, we compare all the results of these performance measures with the results achieved with OSTBC, revealing important connections between OSTBC and QSTBC. For example, the coding gain of a QSTBC is upper bounded by the coding gain of the underlying OSTBC. Also, the BER of a QSTBC for n(T),T transmit and n(R) receive antennas is tightly lower bounded by the BER of a full-diversity providing intersymbol-interference free system. In addition to that, we show that gains in terms of average rate by using a QSTBC (and, thus, with higher n(T)) instead of the underlying OSTBC are only attainable, if the available channel state information at the transmitter (CSIT) is utilized. Finally, we illustrate our theoretical results using numerical simulations.

We maximize the performance of multiple-input multiple-output (MIMO) multiple access channels (MAC) and broadcast channels (BC) under individual and sum power constraints. We observe that the performance metrics sum capacity and sum mean-square error (MSE) belong to a general class of functions which are the trace of a matrix-monotone function. The sum capacity if successive interference cancellation (SIC) is applied in the uplink or if Costa Precoding is applied in the downlink, or the normalised sum MSE if a multiuser minimum mean-square error (MMSE) receiver is applied at the base, belong to that class of performance functions. We use Lowner's representation of matrix monotone functions in order to characterise the optimum transmission strategies. Using the Karush-Kuhn-Tucker optimality conditions, we show that the mutual covariance matrix optimisation can be decomposed into power allocation and covariance matrix optimisation under individual power constraints. The covariance matrix optimisation under individual power constraints in turn can be decomposed into a kind of modified single-user covariance matrix optimisation treating the other users as noise. The concrete structure of the single-user program depends on the performance metric used. The proposed algorithms efficiently solve the multi-user MIMO performance optimisation problem. These results generalise the results regarding the performance capacity optimisation recently reported for sum capacity optimisation and the results regarding the sum MSE optimisation. The optimal transmit strategy deconstructs into two independent parts: the coding and the signal processing part. The second part is adapted to the channel and performs multi-user power control and transmit covariance matrix optimisation.

In order to obtain full spatial diversity available in a multiple-input multiple-output (MIMO) system, orthogonal space-time block codes (OSTBC) are employed due to their low decoding complexity. However, the drawback of OSTBC is that the code rate decreases with increasing number of transmit antennas. Using a recent result on the properties of Gaussian quadratic forms, we show that an OSTBC for an odd number of transmit antennas is always outperformed in terms of different performance measures, namely, the outage probability, the outage mean-squared error (MSE), and the raw bit-error rate (BER), by an OSTBC for an even number of transmit antennas, which has a strong impact on the design and application of OSTBC.

Different performance measures are an important mean in order to analyze and design wireless communications systems. Examples of common performance measures are the ergodic capacity, the outage capacity, and the average mean-square error (MSE). In this work, we study the delay-limited capacity (DLC). The DLC depends on the properties of the fading channel, e.g. on the spatial correlation and on the line-of-sight (LOS) component. In this letter, we derive the DLC for the general class of parallel fading channels, including the multiple antenna channels under moment and long-term power constraint. We prove that the DLC is Schur-concave with respect to the spatial correlation in single-input multiple-output (SIMO), and multiple-input single-output (MISO). Bounds for the DLC of multiple-input multiple-output (MIMO) and parallel fading channels are derived and the impact of the the mean component and spatial correlation on these bounds is characterized.

Multiple transmit antennas improve the ergodic and outage capacity of wireless systems. Spatial properties of the channel including the transmit antenna array affect the Optimum transmission strategy as well as the achievable capacity and average throughput. First, we study the outage probability of a multiple input single output (MISO) system with perfect channel state information (CSI) at the receiver under different types of CSI at transmitter and with transmit antenna correlation. We prove the conjecture given in Telatar's seminal paper and complete the analysis of the optimum transmit strategy without CSI at the transmitter and uncorrelated antennas. Furthermore, we show how the impact of correlation on the outage probability depends on the transmission rate and SNR. We show that the behaviour of the outage probability differs from the behaviour of the ergodic capacity. In terms of ergodic capacity there are clear instructions what is the optimum transmission strategy and what is the impact of correlation. In contrast, the outage probability behaves chameleonic. If the transmitter is aware of the channel correlation matrices, the optimum transmit strategy is to transmit along the eigenvectors of the known correlation matrix. The remaining power allocation problem is difficult since it is a non-convex optimisation problem. However, necessary conditions characterise the optimal allocation. Finally, we analyse the outage probability for the general multiple input Multiple Output (MIMO) system with spatially correlated transmit and receive antennas in asymptotic high and low SNR regime. The theoretical results are illustrated by numerical simulations.

Recently, the statistical properties of the equivalent channel representation of a multiple-input-multiple output (MIMO) system employing rate one quasi-orthogonal space-time block codes (QSTBC) for n(T) = 2(n), n >= 2 transmit antennas was characterized. It was shown, that these QSTBC were capable of achieving a significant fraction of the outage mutual information of a MIMO system. In this letter, based on the Minkowski's determinant inequality and the Meijer's G-function we derive an upper bound for the fraction of outage probability achieved with QSTBC for the general case of n(T) = 2(n), n >= 2 transmit antennas. Simulations results show that this bound gets tight for all signal-to-noise-ratios (SNR) values by increasing the number of receive antennas.

In this paper, we propose a "turbo" coding scheme consisting of the serially concatenation of a channel code and OSTBC with iterative processing at the receiver. We analyze the impact of different mapping strategies on the information transfer of the space-time detector with EXIT-charts and derive some criteria for the optimum mapping strategy.

We study the optimal transmission strategy of a multiple-input single-output (MISO) wireless communication link. The receiver has perfect channel state information (CSI), while the transmitter has different types of CSI, i.e., either perfect CSI, or no CSI, or long-term knowledge of the channel covariance matrix. For the case in which the transmitter knows the channel covariance matrix, it was recently shown that the optimal eigenvectors of the transmit covariance matrix correspond with the eigenvectors of the channel covariance matrix. However, the optimal eigenvalues are difficult to compute. We derive a characterization of the optimum power allocation. Furthermore, we apply this result to provide an efficient algorithm which computes the optimum power allocation. In addition to this, we analyze the impact of correlation on the ergodic capacity of the MISO system with different CSI schemes. At first, we justify the belief that equal power allocation is optimal if the transmitter is uninformed and the transmit antennas are correlated. Next, we show that the ergodic capacity with perfect CSI and without CSI at the transmitter is Schur-concave, i.e., the more correlated the transmit antennas are, the less capacity is achievable. In addition, we show that the ergodic capacity with covariance knowledge at the transmitter is Schur-convex with respect to the correlation properties. These results completely characterize the impact of correlation on the ergodic capacity in MISO systems. Furthermore, the capacity loss or gain due to correlation is quantified. For no CSI and perfect CSI at the transmitter, the capacity loss due to correlation is bounded by some small constant, whereas the capacity gain due to correlation grows unbounded with the number of transmit antennas in the case in which transmitter knows the channel covariance matrix. Finally, we illustrate all theoretical results by numerical simulations.

We study the optimal transmission strategy of a single-user multiple-input/multiple-output communication system with covariance feedback. We consider the situation with correlated receive and correlated transmit antennas in Rayleigh flat fading. Furthermore, we assume that the receiver has perfect channel state information, while the transmitter knows only the transmit correlation matrix and the receive correlation matrix. We show that transmitting in the direction of the eigenvectors of the transmit correlation matrix is the optimal transmission strategy. In addition to this, the optimal power allocation is studied and a necessary and sufficient condition for optimality of beamforming is derived. All theoretical results are illustrated by numerical simulations.

We analyze the impact of transmitter and receiver spatial correlation on the performance of a multiple-input multiple-output (MIMO) system which applies an orthogonal space-time block code with no channel state information at the transmitter and perfect channel state information at the receiver. We derive a general formula for the bit error rate of a MIMO system with arbitrary number of transmit and receive antennas as a function of the correlation at the transmitter and the receiver. We prove that the diversity advantage is given by M/spl middot/N if M is the rank of the transmit correlation matrix and N the rank of the receive correlation matrix, respectively.

In this work, we study the multiuser multiple-input multiple-output (MIMO) multiple access channel (MAC) under the assumption that the base station performs linear multiuser minimum mean-square error (MMSE) detection. We derive the average normalized MSE and the individual MSEs of users. At first, we optimize the average normalized MSE with respect to the transmit covariance matrices of the users. Next, adaptive power allocation is applied to further minimize the average normalized MSE. This leads to the general average normalized MSE optimization under a sum power constraint. We analyze the optimization problems and their connections by their Karush-Kuhn-Tucker conditions. The covariance matrix optimization is solved by iteratively single-user average MSE optimization in which the interference is treated as noise. We develop an iterative algorithm that performs power allocation and covariance matrix optimization. In addition to this, we study the achievable MSE region. We show that the MSE region is convex for the two-user MIMO case. Furthermore, we characterize the optimum power allocation among the users with regard to the single-user range. We show that the user with the maximum singular value of its channel matrix is the first supported user. For low SNR values, the optimal strategy is to have the best user transmitting only. In addition, we derive the individual MSE using single-user MMSE detectors and study the fulfillment of MSE requirements.