Introduction

With the wide deployment of 3G wireless mobile systems, data access anytime, anywhere is now becoming reality. It is anticipated that the demand for higher rate data access in the wireless environments will grow significantly in coming years due to the use of Internet and media rich applications requiring several tens of Mbps. Spatial multiplexing (SM) schemes that use multiple antennas at the transmitter and receiver also called multiple input multiple output (MIMO) architecture and layered space-time decoding at the receiver, promise enormous spectral efficiency in a range of 4-40 bits/sec/Hz and much improved error performance over conventional single input single output (SISO) antenna systems in rich scattering multipath channels. MIMO is therefore regarded as the fundamental enabling technology that can fulfill the high spectral efficiency demand of fourth generation cellular wireless systems such as WiMAX and 3GPP Long Term Evolution (LTE) and potentially leading to Gigabits wireless systems. In the context of point-to-point based single user scenario, SM techniques such as Bell-Labs Layered Space-time (BLAST) detection have been investigated extensively. However, cellular wireless systems have to allow simultaneous access to the data for many users, which require a very different and more complex transmission and detection approach to optimise the system performance. This research aims to propose new system approaches and techniques to address the above-discussed challenges that are fundamental to efficient and cost effective deployment of SM based SDMA techniques in practical wireless environments. The research investigations in typical multicellular settings with aggressive frequency reuse pattern and sum rate optimisation under the effects of intra and intercell interference will be carried out. Furthermore, the project will encompass the work on cooperative and relay assisted spatial diversity and other expertise gained from previous research projects for possible applications in to advanced air interface technologies such as LTE, IEEE 802.16m and LTE-Advanced.

Figure 1: Proposed group collaborative SDMA system model

Past projects

High Capacity CDMA and Collaborative Techniques (2003-2008)

The project successfully demonstrated new approaches to increase the user capacity and improve the error performance of Code Division Multiple Access (CDMA) by employing adaptive interference cancellation and collaborative spreading and space diversity techniques. Collaborative Coding Multiple Access (CCMA) was also investigated as a separate technique and combined with CDMA. The advantages and shortcomings of CDMA and CCMA were analysed and new techniques for both the uplink and downlink were proposed and evaluated. The project has results in following major contributions:

• New blind adaptive receiver designs employing successive and parallel interference cancellation (IC) architectures were presented that have shown to offer near single user performance and approximately two fold user capacity compared with conventional IC receivers. Furthermore, higher capacity and low complexity blind adaptive subcarrier combining (BASC) technique was also proposed for Multicarrier-CDMA.
• User collaborative scheme with successive interference cancellation for uplink of CDMA referred to as collaborative SIC (C-SIC) was investigated to reduce multiple access interference (MAI) and achieve improved diversity.

Figure 2: User terminals collaboratively transmit and exchange their data to improve reliability of communication with the destination

• It is known that existing collaborative diversity schemes incur loss in throughput due to the need of orthogonal time/frequency slots for relaying source’s data. To address this problem, a novel near-unity-rate scheme also referred to as bandwidth effcient collaborative diversity (BECD) was proposed and evaluated.
• A novel approach of ‘User Collaboration’ was introduced to substaintially increase the user capacity of CDMA for both the downlink and uplink. Its was shown that when users’ channels are independent (uncorrelated), signi?cantly higher user capacity can be achieved by grouping multiple users to share the same spreading sequence and performing MUD on per group basis followed by a low complexity ML decoding at the receiver.