Abstract-We investigate link quality metrics (LQMs) based on raw bit-error-rate, effective signal-to-interference-and-noiseratio, and mutual-information (MI) for the purpose of fast link adaptation in communication systems employing orthogonal frequency division multiplexing and multiple-input multipleoutput (MIMO) antenna technology. From these LQMs the packet-error-rate (PER) can be estimated and exploited to select the modulation and coding scheme (MCS) among a class of candidate MCSs that achieves the maximum throughput for the current channel state under a specified target PER objective. We propose a novel MI-based LQM and compare the PERestimation accuracy obtained with this LQM with that resulting from using other LQMs by means of comprehensive Monte Carlo simulations. Search methods for the MCS in the class most suitable for a given channel state are presented. An algorithm for obtaining a practical upper bound on the throughput of any link adaptation scheme is proposed. The investigated LQMs are applied to the IEEE 802.11n standard with a 2x2 MIMO configuration and practical channel estimation. The proposed MI-based LQM yields the highest PER estimation accuracy and its throughput shows only 1.7 dB signal-to-noise-ratio (SNR) loss with respect to the upper bound, but up to 9.5 dB SNR gain compared to the MCS maximizing the throughput for the current noise variance.

Joint time-variant channel estimation and multiuser detection are key building-blocks for wireless broadband communication for mobile users at vehicular speed. We propose an iterative receiver for a multi-carrier (MC) code division multiple access (CDMA) system in the uplink. Multi-user detection is implemented through iterative parallel interference cancelation and conditional linear minimum mean square error (MMSE) filtering. MC-CDMA is based on orthogonal frequency division multiplexing (OFDM), thus time-variant channel estimation can be performed for every subcarrier individually. The variation of a subcarrier over the duration of a data block is upper bounded by the maximum Doppler bandwidth which is determined by the maximum velocity of the users. We exploit results from the theory of time-concentrated and bandlimited sequences and apply a Slepian basis expansion for time-variant subcarrier estimation. This approach enables time-variant channel estimation without complete knowledge of the second-order statistics of the fading process. The square bias of the Slepian basis expansion is one order of magnitude smaller compared to the Fourier basis expansion. The square bias of the basis expansion is the determining factor for the performance of the iterative joint channel estimation and data detection. We present an iterative linear MMSE estimation algorithm for the basis expansion coefficients in a multi-user system. The consistent performance of the iterative receiver using the Slepian basis expansion is validated by simulations for a wide range of velocities. Index Terms-Discrete prolate spheroidal sequence, MC-CDMA, multi-user detection, OFDM, parallel interference cancelation, Slepian basis expansion, time-variant channel estimation.

SUMMARYSignals transmitted through multiple-input multiple-output (MIMO) wireless channels suffer from multiple-access interference (MAI), multipath propagation and additive noise. Iterative multiuser receiver algorithms mitigate these signal impairments, while offering a good tradeoff between performance and complexity. The receiver presented in this paper performs channel estimation, multiuser detection and decoding in an iterative manner. The estimation of the frequency selective, block-fading channel is initiated with the pilot symbols. In subsequent iterations, soft decisions of all the data symbols are used in an appropriate way to improve the channel estimates. This approach leads to significant improvement of the overall receiver performance, compared to other schemes. The bit-error-rate (BER) performance of the receiver is evaluated by simulations for different parameter setups.

The HSDPA extension of UMTS promises an improved cell capacity and throughput. This enhancement is mainly achieved by three newly introduced techniques, namely adaptive modulation and coding, hybrid automatic repeat request, and fast scheduling. The used coding and modulation scheme depends on the transmitted Transport Block Size, which in turn is signalled via the Channel Quality Indicator (CQI). The CQI values are calculated with the help of SINRs at each User Equipments and fed back to the base station. An appropriate CQI estimation is necessary to transmit data packets with Transport Block Sizes that maximize the throughput. Therefore, in this work we propose a novel SINR-to-CQI mapping which achieves optimum throughput for selected ITU propagation channel models.

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