A two step spatio-temporal filtering scheme for smart antennas compared to a multi-user maximum likelihood algorithm

Future wireless communication systems require an increased spectral efficiency to accommodate the growing number of users and permit connections with higher data rates. To this end, smart antenna arrays utilizing adaptive beamforming techniques on the uplink as well as the downlink enable space division multiple access (SDMA). Furthermore, the range is increased significantly which is of great advantage in rural areas. We present an algorithm in which a two-dimensional (2-D) spatial filtering scheme based on 2-D unitary ESPRIT is used to separate the dominant wavefronts. Then the separated wavefronts are assigned to the users by correlating them with known training sequences. To obtain temporal equalization, all wavefronts assigned to a particular user are passed on to the different diversity branches of a (single-user) Viterbi equalizer. The performance of this two step spatio-temporal filter is compared to a computationally more expensive algorithm in which a joint multi user maximum likelihood equalizer is applied to the impulse responses of all co-channel users. The impulse responses are estimated by exploiting the training sequences. Monte Carlo simulations for synthetic and realistic scenarios allow a performance evaluation of both schemes based on the uplink bit error ratio. Note that (both) data detection schemes require spatially well separated users to obtain good performance. Therefore, an intelligent channel assignment strategy is examined in connection with both schemes.