Analyse Eines Mehrbenutzer-Mehrfachzugriffskanals Mit Mimo

The increasing number of connected users as well as the availability of new services and mobile applications drive the need for higher data rates. In order to fulfill such expectations different strategies such as spatial multiplexing have been introduced. This thesis is centered on the Multi-User Uplink Channel where different users transmit to a single base station with multiple antennas. The purpose of this thesis is to design the transmitter and the receiver architectures so that the maximum sum rate of a Multi-User Uplink Channel reaches the capacity for single and multi-antenna users. In the literature there is a lack of practical implementations and not many studies exploit the multi-antenna user scenario. It is important to properly characterize the capacity region and define practical implementation schemes on the uplink direction to design the architecture for the Multi-User Downlink Channel also referred as the Broadcast Channel, which is a more complex problem based on the uplink solution. The design of the optimal transmitter is motivated by the analysis of capacity first for the single user scenario with Multi Input Multi Output Peer-to-Peer (MIMO P2P) communica- tions followed by the Multi-User scenario for single and multi-antenna users. At the receiver three types of beamformers are analyzed and compared: Zero Forcing, QR and Minimum Mean Squared Error beamformer. Results for the Bit Error Rate performance and maximum sum rate for the different receivers are provided. The thesis results show that the optimal architecture for the Multi-User Uplink with multi- antenna users that achieves capacity is the combination of the optimal MIMO P2P design, based on the Singular Value Decomposition of the channel matrix and the Water Filling power allocation. For the receiver part the Minimum Mean Squared Error beamformer is proven to achieve capacity. Channel State Information is needed at the transmitter and receiver, therefore a channel estimation algorithm is provided based on orthogonal sequences and is proven to deliver good Bit Error Rate results

Hardware Impairments in Large-scale MISO Systems: Energy Efficiency, Estimation, and Capacity Limits

The use of large-scale antenna arrays has the potential to bring substantial improvements in energy efficiency and/or spectral efficiency to future wireless systems, due to the greatly improved spatial beamforming resolution. Recent asymptotic results show that by increasing the number of antennas one can achieve a large array gain and at the same time naturally decorrelate the user channels; thus, the available energy can be focused very accurately at the intended destinations without causing much inter-user interference. Since these results rely on asymptotics, it is important to investigate whether the conventional system models are still reasonable in the asymptotic regimes. This paper analyzes the fundamental limits of large-scale multiple-input single-output (MISO) communication systems using a generalized system model that accounts for transceiver hardware impairments. As opposed to the case of ideal hardware, we show that these practical impairments create finite ceilings on the estimation accuracy and capacity of large-scale MISO systems. Surprisingly, the performance is only limited by the hardware at the single-antenna user terminal, while the impact of impairments at the large-scale array vanishes asymptotically. Furthermore, we show that an arbitrarily high energy efficiency can be achieved by reducing the power while increasing the number of antennas.Comment: Published at International Conference on Digital Signal Processing (DSP 2013), 6 pages, 5 figure

Power Scaling of Uplink Massive MIMO Systems with Arbitrary-Rank Channel Means

This paper investigates the uplink achievable rates of massive multiple-input multiple-output (MIMO) antenna systems in Ricean fading channels, using maximal-ratio combining (MRC) and zero-forcing (ZF) receivers, assuming perfect and imperfect channel state information (CSI). In contrast to previous relevant works, the fast fading MIMO channel matrix is assumed to have an arbitrary-rank deterministic component as well as a Rayleigh-distributed random component. We derive tractable expressions for the achievable uplink rate in the large-antenna limit, along with approximating results that hold for any finite number of antennas. Based on these analytical results, we obtain the scaling law that the users' transmit power should satisfy, while maintaining a desirable quality of service. In particular, it is found that regardless of the Ricean $K$-factor, in the case of perfect CSI, the approximations converge to the same constant value as the exact results, as the number of base station antennas, $M$, grows large, while the transmit power of each user can be scaled down proportionally to $1/M$. If CSI is estimated with uncertainty, the same result holds true but only when the Ricean $K$-factor is non-zero. Otherwise, if the channel experiences Rayleigh fading, we can only cut the transmit power of each user proportionally to $1/\sqrt M$. In addition, we show that with an increasing Ricean $K$-factor, the uplink rates will converge to fixed values for both MRC and ZF receivers

Uplink Performance of Time-Reversal MRC in Massive MIMO Systems Subject to Phase Noise

Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI). In particular, we consider two distinct operation modes, namely when the phase noise processes at the $M$ BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare their performance. Based on the derived achievable sum-rates, we show that with the proposed receive processing an $O(\sqrt{M})$ array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users.Comment: 13 pages, 6 figures, 2 tables, IEEE Transactions on Wireless Communications (accepted

Energy-Efficient Resource Allocation in Multiuser MIMO Systems: A Game-Theoretic Framework

This paper focuses on the cross-layer issue of resource allocation for energy efficiency in the uplink of a multiuser MIMO wireless communication system. Assuming that all of the transmitters and the uplink receiver are equipped with multiple antennas, the situation considered is that in which each terminal is allowed to vary its transmit power, beamforming vector, and uplink receiver in order to maximize its own utility, which is defined as the ratio of data throughput to transmit power; the case in which non-linear interference cancellation is used at the receiver is also investigated. Applying a game-theoretic formulation, several non-cooperative games for utility maximization are thus formulated, and their performance is compared in terms of achieved average utility, achieved average SINR and average transmit power at the Nash equilibrium. Numerical results show that the use of the proposed cross-layer resource allocation policies brings remarkable advantages to the network performance.Comment: Proceedings of the 16th European Signal Processing Conference, Lausanne, Switzerland, August 25-29, 200