Atul Arvind Salvekar

CQI algorithm design in MIMO systems with maximum likelihood detectors

Abstract In this paper, we investigate throughput optimization in 2 × 2 multi-input multi-output (MIMO) systems using channel quality indicator (CQI) based scheduling. Existing MIMO CQI algorithms are mostly designed for sub-optimal linear symbol detectors such as minimum mean square error (MMSE). We consider in this paper how to select CQIs for both streams in order to maximize the total throughput when the non-linear optimal symbol detection technique, maximum likelihood (ML) detector, is employed. Specifically, we formulate a simple yet accurate mathematical model for throughput maximization in a 2 × 2 MIMO channel using an ML detector. We make use of constellation constrained capacity to characterize the feasible rate region of such MIMO systems. Based on the information-theoretic analysis, a novel CQI algorithm for 2 × 2 MIMO transmission is proposed. Numerical results indicate that the proposed CQI algorithm yields up to 4% throughput improvement over the CQI algorithm optimized for MMSE detectors in High Speed Downlink Packet Access (HSDPA).

Special issue on Advances in MIMO–OFDM

The combination of Orthogonal Frequency Division Multiplexing (OFDM) and Multiple Input – Multiple Output (MIMO) techniques is instrumental to achieving the high spectral efficiency required for the evolution of mobile communication systems. The implementation of MIMO–OFDM systems will require, among others, advances in the design of channel estimation and synchroThe first paper ‘‘Joint Channel and Frequency Offset Estimation in MIMO–OFDM Systems with Insufficient Cyclic Prefix’’ [1] addresses joint channel and frequency offset estimation for MIMO–OFDM systems in the presence of Inter Symbol Interference and Inter Carrier Interference due to an insufficient CP. The second paper ‘‘CQI Algorithm Design in MIMO Sysnization techniques to work in fast fading conditions. These techniques in combination with strategies to manage or limit feedback information and overhead will allow for the adaptation of the transmitted signal to the changing channel conditions.MIMO–OFDMsystemswill use cooperative communication, through relays, to improve reliability and extend coverage. The challenges facedwhen implementingMIMO–OFDM in the presence of multiple users increase, but also the benefits. Multiuser and multi-cell interference arise and resource allocation becomes crucial. Several approaches have been developed recently to improve the performance ofMIMO–OFDM inmultiuser andmulti-cell environments, enhancing the data rates and/or the expanding the coverage. The special issue on Advances in MIMO–OFDM was organized to highlight and encourage recent advances in this topic. Each submitted paper was reviewed by experts in the area. Based on the critical reviews, we selected 7 papers to include in this special issue. They all contribute innovative ideas for the design and implementation of MIMO–OFDM based transceivers and networks that will meet the requirements of future generations of mobile communications. The first three papers cover the topics of channel quality estimation and performance prediction. With this information it is possible to perform adaptation at the transmitter, which is the topic of the fourth paper. The final two papers extend this possibility to multiuser and cooperative systems while the last paper proposes physical layer security techniques for MIMO–OFDM. MIMO–OFDM systems use a cyclic prefix (CP) longer than the expected channel impulse response to maintain orthogonality at the expense of a small capacity loss. An insufficient CP may appear in some wireless scenarios with a very long channel response or in some military applications that suppress the CP to avoid signal identification. tems with Maximum Likelihood Detectors’’ [2] investigates the problem of choosing a channel quality indicator (CQI) for individual streams in a 2×2 MIMO system, where the goal is to maximize the total throughput when data is scheduled based on the CQI chosen. Based on an information-theoretic analysis, a novel CQI algorithm is proposed and is shown to yield a throughput improvement in High Speed Downlink Packet Access (HSDPA), where MIMO–OFDM is used. Performance prediction in practicalMIMO–OFDMwireless links is challengingwhen forward error correction and interleaving are performed over subcarriers and spatial streams in frequency/spatial selective channels. Recent results show that the error-rate of coded and bit-interleaved MIMO–OFDM links may be characterized by the postprocessing signal-to-noise ratio (SNR), sorted over subcarriers, what is denoted as ordered SNR. The third paper ‘‘Modeling Ordered Subcarrier SNR in MIMO–OFDM Wireless Links’’ [3] establishes fundamental structure of this ordered SNR, obtaining interesting results that find several applications such as high-resolution limited channel feedback, simpler channel models for system simulation and algorithm design, and the reduction of dimension in link quality metrics for link adaptation. Multicast transmission is an attractive way to provide common information like video simultaneously to multiple users. In conventional approaches to multicast, information is sent either at the most reliable mode of operation supported by the system, or is adapted to the performance of the worst user. The fourth paper ‘‘Distributed Link Adaptation for Multicast Traffic in MIMO–OFDM Systems’’ [4] shows how link adaptation can be used in multicast transmission to further increase data rates exploiting channel feedback from the users. It uses a data driven machine learning approach to propose a joint link adaptation