The attractiveness of OFDM decreases with the rising of inter-carrier interference in quickly time-varying channels. Classical OFDM low-complex detection is impaired and more elaborated techniques are required to mitigate the need for full matrix equalization. We present here a fresh approach to this subject, introducing novel fast-converging iterative techniques based on preconditioning. Moreover, we interpret windowing under a new perspective in association with the Basis Expansion Modeling of the time-varying channel. We discuss the complexity of the proposed methods, showing that they are still linear to the OFDM block size. We conclude by illustrating their competitive performance by means of numerical simulations.

The performance of the classical low complexity OFDM detection is known to rapidly degrade with the raising of inter-carrier interference in the presence of fast time-varying channels. Advanced equalization techniques to mitigate the impact of the inter-carrier interference under those circumstances, generally involve significantly higher complexity. In this paper we address a class of reduced-complexity fast-converging iterative equalization algorithms yielding nearly-optimal performance with respect to other well-known methods. The complexity is optimized by suitable pre-conditioning in order to drastically reduce the number of required iterations necessary to achieve reliable signal detection. A detailed analysis supported by numerical results under realistic scenarios shows the nearly-optimal performance achievable by the proposed techniques with a very limited complexity, when comparing with classical zero-forcing and minimum-mean square error linear equalization.

We consider initial timing acquisition in discrete-sequence code-division multiple-access (DS-CDMA) when propagation is affected by multipath and fading, and where the base-station broadcasts a synchronization pilot signal in the form of bursts of modulated chips transmitted periodically and separated by long silent intervals. Subject to certain simplifying assumptions, we derive the maximum-likelihood (ML) estimator by solving a constrained maximization problem. Our ML timing estimator has constant complexity per observation sample. The relation to other estimation methods is addressed, and performance comparisons are provided by simulation. The proposed estimator yields good performance independently of the multipath-intensity profile of the channel, provided that the delay spread is not larger than a given maximum spread. Moreover, our estimator is fairly robust to the mismatch in the fading Doppler spectrum and provides good performance for both fast and slow fading.

We consider timing initial acquisition in DS-CDMA when propagation is affected by multipath and fading and where the base-station broadcasts a synchronization pilot signal in the form of bursts of modulated chips transmitted periodically and separated by long silent intervals. Subject to certain simplifying assumptions we derive the maximum likelihood (ML) estimator by solving a constrained maximization problem by applying the Karush-Kuhn-Tucker conditions. Our ML timing estimator has constant complexity per observation sample. The relation to other estimation methods is addressed, and performance comparisons both in terms of estimation mean-square error and cumulative density function of the channel energy falling in a certain window are provided by simulation. The resulting estimator offers good results over all fading channels with delay spread not larger than a given maximum spread.

This paper proposes a beamforming design method for interference cancellation using a special thinned array structure, termed minimum redundancy array (MRA). MRA is analyzed with partially adaptive beamforming design techniques and compared with corresponding uniform regular array (URA) over a set of likely interference scenarios. The partially adaptive beamformer design is subject to worst-case performance constraints. Extensive numerical simulations with several sets of interference scenarios show that MRA almost always outperforms URA, in both cases of fully adaptive beamformers and of partially adaptive beamformers. We also introduce a design criterion to take into account both the array geometry and partially adaptive beamforming methods.