The recent advances in multiple-input multiple-output (MIMO) processing [1] are making the application of multiantenna transmitters and receivers increasingly popular in modern wireless communications due to the enhanced capacity and space diversity they offer. MIMO schemes have recently been incorporated in communication standards such as WiMAX and 3GPP-LTE to satisfy the growing demand for higher data rates and quality of service for multimedia applications. Despite the increased information capacity offered by the MIMO channel, the spatial correlation of the multiple subchannels introduces an additional source of interference which corrupts the data symbols and in effect degrades the achievable error rate performance of such systems. In the MIMO uplink, space diversity detection techniques [2–5] can counteract this impediment to a satisfactory extent. In [2, 3], the sphere decoder is presented for an arbitrary lattice code and a lattice code resulting from applying algebraic space-time coding on a MIMO system, respectively. Regardless of the technique's near-optimal performance, the decoding complexity is quite significant, which makes it impractical for use in mobile units at downlink and point-to-point reception. Suboptimal solutions with reduced complexity are introduced in [4, 5] where diagonal- and vertical-layered architectures of the (Bell Laboratories Layered Space Time) BLAST receiver are presented, respectively. While complexity is drastically reduced the performance of these techniques is comparable to the sphere decoder in most practical scenarios. An alternative to MIMO detection is to shift the signal enhancement processing to the transmitter by use of precoding. This is particularly popular in MIMO downlink communications and point-to-point systems, which is the focus of this work. Channel inversion (CI) [6] entails the least complexity of the precoding techniques available. However, the disadvantages of the CI technique include a poor symbol error rate (SER) performance and the fact that the transmission rate and throughput delivered are limited and do not improve by increasing the number of antennas, as demonstrated in [7]. The solution proposed in [7], which is a minimum mean square error (MMSE) form of channel inversion, provides some performance and capacity gains with respect to the conventional CI, without a considerable complexity increase. Nevertheless, the transmission rates offered by both these schemes are far from reaching the theoretical channel capacity. Dirty paper coding (DPC) techniques as, for example, in [8–11] based on the initial information theoretical analysis in [12], can further increase transmission rates and achieve significant capacity benefits. However, the majority of the DPC methods developed so far are impractical in many scenarios as they require sophisticated signal processing at the transmitter with complexity similar to the one of sphere decoding. A promising alternative is the joint transmit-receive beamforming scheme as presented in [13] amongst others in the literature. Despite being less complex than DPC, the most robust beamforming schemes require iterative communication between the transmitter and receiver for the optimization of the joint processing and the system configuration. This needs to be done every time the channel characteristics change and hence, in fast fading environments introduces considerable latency to the MIMO downlink system. Owing to their favourable performance-to-complexity tradeoff amongst the techniques mentioned above, this paper focuses on the application of the proposed scheme to the more practical V-BLAST detection and MMSE precoding.

Complementary to the aforementioned signal enhancement processing MIMO schemes, a number of resource allocation schemes [14–19] have emerged for MIMO communications mainly involving antenna selection [14–16] and power allocation [17, 18] for multielement transceivers as well as frequency (subcarrier) allocation [19] for MIMO-orthogonal frequency division multiplexing (OFDM) communications. All the relevant resource allocation methods focus on the reduction of interference between the spatial streams of the MIMO channel. This clearly differentiates them to the proposed scheme where the aim is not strictly to minimise the correlation of the spatial streams but rather to optimise it and accommodate for constructive interchannel interference (ICI). Moreover, resource allocation schemes such as antenna selection can be used in addition to the proposed technique to further improve the performance. The focus of this paper, however, is on signal enhancement schemes and for reasons of coherence, antenna selection and power allocation are not considered here.

In more detail, the proposed scheme which parallels the ones in [20, 21] proposed for code division multiple access (CDMA) is based on the fact that ICI is separated into constructive and destructive as discussed in detail in [22]. The characterisation of the instantaneous ICI depends on the channel characteristics and the correlation between the spatial streams, and, equally importantly, on the instantaneous values of the transmitted symbols. By perturbing the data symbols to be transmitted by means of reordering or scrambling, the proposed scheme influences the ICI between the MIMO subchannels. It then chooses a symbol mapping such that the interference is optimised and the decision variables at the receiver are maximised. Subsequently, conventional precoding or detection can be applied with enhanced performance due to the optimisation of interference achieved by the proposed symbol mapping.

It is clear that the proposed symbol mapping scheme can be combined with various conventional MIMO detection (linear detection, V-BLAST, sphere decoding, etc.) and precoding schemes (linear precoding, dirty paper coding etc.) to improve the respective performance. For reasons of simplicity and to maintain the focus of the present paper, as mentioned above, only two of the most practical and popular MIMO techniques are considered here, MMSE precoding and V-BLAST detection.

It should be noted that the proposed data allocation method entails the transmission of control signalling (CS) to inform the receiver about the mapping process used so as to attain the correct initial order or appropriately descramble the received data after detection. It will be shown that the CS increases logarithmically with the number of candidate mapping patterns and for this reason the number of possible reordered or scrambled versions of the data to select from should be limited. In the simulations presented here this number is limited to values such that the overhead imposed by the CS transmission is restricted to less than 6% of the transmitted information.