Multiple-Input Multiple-Output (MIMO) systems are characterised by increased capacity and improved performance compared to the single-input single-output (SISO) systems. One of the main challenge in the design of MIMO systems is the detection of the transmitted signals due to the interference caused by the multiple simultaneously transmitted symbols from the multiple transmit antennas. Several detection techniques have been proposed in the literature in order to reduce the detection complexity, while maintaining the required quality of service. Among these low-complexity techniques is the Lattice Reduction (LR), which can provide good performance and significantly lower complexity compared to Maximum Likelihood (ML) detector. In this paper we propose to use the so-called Element-based Lattice Reduction (ELR) combined with K-Best detector for the sake of attaining a better Bit Error Ratio (BER) performance and lower complexity than the conventional Lenstra, Lanstra, and Lovasz (LLL) LR-aided detection. Additionally, we propose a hardware implementation for the ELR-aided K-Best detector for a MIMO system equipped with four transmit and four receive antennas. The ELR-aided K-Best detector requires an extra 18% increase in power consumption and an extra 20% in area overhead compared to a regular K-Best detector dispensing with ELR, where this increase in the hardware requirements is needed in order to achieve a 2 dB performance improvement at a bit error rate of 10 −5 .

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sequence of three letters, called a triliteral root. A proposed "Matrix" method for the representation of the inflectional paradigms of Arabic words is presented. This representation results in a classification of Arabic words into a tree structure (Fig(l)) whose leaves represent unique conjugational or derivational paradigms, each represented in the proposed "Matrix" form. A study of about 2,500 stems from a high frequency Arabic wordlist due to Landau <1> has revealed a systematic set of co-occurrence patterns for the enclitic pronouns of Arabic verbs and for the possessive pronouns attached to Arabic nouns. Each co-occurrence pattern represents a subcategorization frame that reflects the underlying semantic relationship. The key feature that distinguishes these semantic patterns has been observed to be whether the attached suffixes relate to the animate or inanimate. In some cases for verbs, the number of the subject is also a significant feature. These semantic features also extend to non-attached subjects and objects (for verbs) and to possessive noun complements (for nouns). Therefore the semantic classes presented in this paper also assist in syntactic/semantic analysis. The first application that was developed, based upon the proposed representaion is a stem-based Arabic morphological analyser, from which a spell checker (on a PS/2 microcomputer) emerged as a by-product. Currently, the system is being used to interact with an Arabic syntactic parser and there are plans to use it in a machine assisted translation system.

sequence of three letters, called a triliteral root. A proposed "Matrix" method for the representation of the inflectional paradigms of Arabic words is presented. This representation results in a classification of Arabic words into a tree structure (Fig(l)) whose leaves represent unique conjugational or derivational paradigms, each represented in the proposed "Matrix" form. A study of about 2,500 stems from a high frequency Arabic wordList due to Landau has revealed a systematic set of co-occurrence patterns for the encLitic pronouns of Arabic verbs and for the possessive pronouns attached to Arabic nouns. Each co-occurrence pattern represents a subcategorization frame that reflects the underlying semantic relationship.