Mikko Vehkaperä

Blind Pilot Decontamination

A subspace projection to improve channel estimation in massive multi-antenna systems is proposed and analyzed. Together with power-controlled hand-off, it can mitigate the pilot contamination problem without the need for coordination among cells. The proposed method is blind in the sense that it does not require pilot data to find the appropriate subspace. It is based on the theory of large random matrices that predicts that the eigenvalue spectra of large sample covariance matrices can asymptotically decompose into disjoint bulks as the matrix size grows large. Random matrix and free probability theory are utilized to predict under which system parameters such a bulk decomposition takes place. Simulation results are provided to confirm that the proposed method outperforms conventional linear channel estimation if bulk separation occurs.

MIMO MC-CDMA communications for future cellular systems

We propose an efficient multiple-input multiple-output concept based on space-time turbo coded modulation and layered spatial multiplexing architectures for cellular multicarrier code-division multiple access systems. We design appropriate receiver algorithms, and compare their performance to competing schemes in a single-cell system. We then evaluate the performance of the scheme in a seven-cell system with universal frequency reuse. The proposed MIMO scheme improves throughput significantly compared to the corresponding single-antenna communications even in the presence of spatial correlation

Projection-Based and Look-Ahead Strategies for Atom Selection

In this paper, we improve iterative greedy search algorithms in which atoms are selected serially over iterations, i.e., one-by-one over iterations. For serial atom selection, we devise two new schemes to select an atom from a set of potential atoms in each iteration. The two new schemes lead to two new algorithms. For both the algorithms, in each iteration, the set of potential atoms is found using a standard matched filter. In case of the first scheme, we propose an orthogonal projection strategy that selects an atom from the set of potential atoms. Then, for the second scheme, we propose a look-ahead strategy such that the selection of an atom in the current iteration has an effect on the future iterations. The use of look-ahead strategy requires a higher computational resource. To achieve a tradeoff between performance and complexity, we use the two new schemes in cascade and develop a third new algorithm. Through experimental evaluations, we compare the pro posed algorithms with existing greedy search and convex relaxation algorithms.

Analysis of Pilot Decontamination Based on Power Control

A subspace method for channel estimation is proposed for asymmetric antenna array systems. The so-called pilot contamination problem reported in [1] is found to be due to the linearity of channel estimation in [2]. We show that it does not occur in cellular systems with power control and power-controlled handoff when the nonlinear channel estimation method proposed in this paper is used. Power-control hand-off is needed to guarantee separability between signal and interference subspaces. We derive the transmission conditions for subspace separability based on free probability and perturbation theory.

On an Achievable Rate of Large Rayleigh Block-Fading MIMO Channels With No CSI

Training-based transmission over Rayleigh block-fading multiple-input multiple-output (MIMO) channels is investigated. As a training method a combination of a pilot-assisted scheme and a biased signaling scheme is considered. The achievable rates of successive decoding (SD) receivers based on the linear minimum mean-squared error (LMMSE) channel estimation are analyzed in the large-system limit, by using the replica method under the assumption of replica symmetry. It is shown that negligible pilot information is best in terms of the achievable rates of the SD receivers in the large-system limit. The obtained analytical formulas of the achievable rates can improve the existing lower bound on the capacity of the MIMO channel with no channel state information (CSI), derived by Hassibi and Hochwald, for all SNRs. The comparison between the obtained bound and a high-SNR approximation of the channel capacity, derived by Zheng and Tse, implies that the high-SNR approximation is unreliable unless quite high SNR is considered. Energy efficiency in the low-SNR regime is also investigated in terms of the power per information bit required for reliable communication. The required minimum power is shown to be achieved at a positive rate for the SD receiver with no CSI, whereas it is achieved in the zero-rate limit for the case of perfect CSI available at the receiver. Moreover, numerical simulations imply that the presented large-system analysis can provide a good approximation for not so large systems. The results in this paper imply that SD schemes can provide a significant performance gain in the low-to-moderate SNR regimes, compared to conventional receivers based on one-shot channel estimation.

A throughput-delay trade-off in packetized systems with erasures

In this paper we propose an information theoretic framework for studying coding and throughput optimization for multi-layered packet transmission systems. Our approach assumes that the system is divided into two separate layers: One code word forms a packet at the physical layer and the code at the network layer spans over these packets. At the receiver, the network layer assumes that the decoded packets arriving from the physical layer either have no errors or are marked as deleted. Thus, albeit the packet loss may be caused, for example, by decoding error, congestion or channel conditions, the network layer treats all decoding errors as erasures regardless of the cause. This allows us to view the system at the network layer as transmission over memoryless erasure channel. We study the throughput optimization and code design across the layers under a total code length constraint while taking also into account the network layer imperfections in the transmission. We use random coding error exponents to achieve results that do not depend on specific coding scheme used. The proposed scheme provides also means for investigating important physical layer phenomena, such as, channel model and lower layer error correction coding in the packet erasure models. Our approach extends to fading channels and networks of multiple nodes and by viewing the two layers of coding as a concatenated coding scheme, a comparison between layer-by-layer and joint cross-layer rate optimization can be made, as outlined in this paper

Large-System Analysis of Joint Channel and Data Estimation for MIMO DS-CDMA Systems

This paper presents a large-system analysis of the performance of joint channel estimation, multiuser detection, and per-user decoding (CE-MUDD) for randomly spread multiple-input multiple-output (MIMO) direct-sequence code-division multiple-access (DS-CDMA) systems. A suboptimal receiver based on successive decoding in conjunction with linear minimum mean-squared error (LMMSE) channel estimation is investigated. The replica method, developed in statistical mechanics, is used to evaluate the performance in the large-system limit, where the number of users and the spreading factor tend to infinity while their ratio and the number of transmit and receive antennas are kept constant. Joint CE-MUDD based on LMMSE channel estimation is compared to several methods of one-shot channel estimation, i.e., methods that do not utilize decoded data symbols to refine the initial channel estimates, in terms of spectral efficiency. Joint CE-MUDD is found to significantly reduce the rate loss caused by transmission of pilot signals when compared to the receivers based on one-shot channel estimation. This holds particularly for multiple-antenna systems. As a result, joint CE-MUDD can provide significant performance gains compared to the receivers based on one-shot channel estimation.

Large-System Analysis of Correlated MIMO Multiple Access Channels with Arbitrary Signaling in the Presence of Interference

Presence of multiple antennas on both sides of a communication channel promises significant improvements in system throughput and power efficiency. In effect, a new class of large multiple-input multiple-output (MIMO) communication systems has recently emerged and attracted both scientific and industrial attention. To analyze these systems in realistic scenarios one has to include such aspects as co-channel interference, multiple access and spatial correlation. In this paper, we study the properties of correlated MIMO multiple-access channels in the presence of external interference. Using the replica method from statistical physics, we derive the ergodic sum-rate of the communication for arbitrary signal constellations when the numbers of antennas at both ends of the channel grow large. Based on these asymptotic expressions, we also address the problem of sum-rate maximization using statistical channel state information and linear precoding. The numerical results demonstrate that when the interfering terminals use discrete constellations, the resulting interference becomes easier to handle compared to Gaussian signals. Thus, it may be possible to accommodate more interfering transmitter-receiver pairs within the same area as compared to the case of Gaussian signals. In addition, we demonstrate numerically for the Gaussian and QPSK signaling schemes that it is possible to design precoder matrices that significantly improve the achievable rates at low-to-mid range of signal-to-noise ratios when compared to isotropic precoding.

Receiver design for spatially layered downlink MC-CDMA system

One of the most promising candidates for the air interface of the upcoming multiuser broadband communication systems is multicarrier code-division multiple-access (MC-CDMA). In the pursuit for higher data rates and reliability of communication in fading environments, a vast amount of spatial multiplexing and transmit diversity techniques have been recently proposed for the multi-antenna systems. In this paper, we study the receiver design for downlink (base station to mobile) multi-antenna MC-CDMA when layered space-time (LST) architectures and space-time coding techniques are utilized. Due to the inevitable complexity restrictions, sub-optimal chip and symbol-level minimum mean squared error (MMSE) based receiver front-ends are derived. For further improvements in performance, an iterative MMSE based detector with soft co-antenna interference cancellation is designed. Performance of the different algorithms is evaluated in spatially correlated and uncorrelated fading channels. The results demonstrated that the proposed multi-antenna schemes combining recently discovered space-time turbo coded modulation and group-wise LST architectures are able to provide significant improvements both in error rate performance and spectral efficiency over the conventional single-antenna system also in spatially correlated environments. By utilizing iterative processing at the receiver, the considered 4/spl times/4 system was found to perform within 1.5 dB from the channel outage capacity in a spatially uncorrelated frequency-selective fading channel.

Analysis of Regularized LS Reconstruction and Random Matrix Ensembles in Compressed Sensing

Performance of regularized least-squares estimation in noisy compressed sensing is studied in the limit when the problem dimensions grow large. The sensing matrix is sampled from the rotationally invariant ensemble that encloses as special cases the standard IID and row-orthogonal constructions. The analysis is carried out using the replica method in conjunction with some novel matrix integration results. The numerical experiments show that for noisy compressed sensing, the standard IID ensemble is a suboptimal choice for the measurement matrix. Orthogonal constructions provide a superior performance in all considered scenarios and are easier to implement in practice.