This paper proposes an adaptive modulation system with a punctured convolutional code for land mobile communications to achieve high quality, high bit rate, and high spectral efficient data transmission in multipath fading environments. The proposed system adaptively controls the coding rate of the punctured convolutional code, symbol rate, and modulation level according to the instantaneous fading channel conditions. During good channel conditions, the modulation parameters are selected to increase the transmission rate as much as possible with satisfying a certain transmission quality. As channel conditions become worse, lower rate modulation parameters are applied or transmission is stopped. The performances in fading environments are evaluated theoretically and by computer simulations. The results show that the proposed system can realize higher quality transmission without the degradation in average bit rate compared to conventional adaptive modulation systems.

This paper proposes a Group Detection (GD) algorithm with Max-Log-MAP Sphere Decoder (MLM-SD) in order to reduce the complexity of signal detection in a Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system. The proposed algorithm divides spatial streams into multiple partial spatial streams by using Minimum Mean Square Error (MMSE) detector, followed by multiple MLM-SDs with reduced number of spatial streams. Although the spatial diversity gain in the MLM-SD degrades because of the lack of the degrees of freedom exploited by the MMSE detector, its diversity gain is recovered by combining the metrics obtained by the multiple MLM-SDs. In a MIMO wireless LAN multipath fading environment, the complexity of the proposed algorithm is 10% of that of the original MLM-SD and the performance degradation in terms of SNR is slightly less than that of the original MLM-SD in 4-by-4 MIMO architecture with 64 QAM achieving 216 Mbps. It is also found that the proposed algorithm is robust against the limitation of the number of searches in sphere decoder.

For future high-speed wireless communications using orthogonal frequency division multiplexing (OFDM), two major system requirements will emerge: throughput improvement and rich interference elimination. Because of its broadband nature and limited frequency allocations worldwide, interference from co-located wireless LAN's operating in the same frequency band will become a serious deployment issue. Adaptive array antenna can enhance the performance by suppressing the co-channel interference even when interference may have a large amount of multipath and also have similar received power to the desired signal. There are typically two types of adaptive array architecture for OFDM systems, whose signal processing is carried out before or after FFT (Fast Fourier Transform). In general, the pre-FFT array processing has low complexity, but in rich multipath and interference environments, the performance will deteriorate drastically. In contrast, the post-FFT array processing can provide the optimum performance even in such severe environments at the cost of complexity. Therefore, complexity-reduction techniques combined with the achievement of high system performance will be a key issue for adaptive array antenna applications. This paper proposes novel adaptive array architecture, which is a complexity-reduction technique using subcarrier clustering for post-FFT adaptive array. In the proposed scheme, plural subcarriers can be clustered into a group with the same spatial weight. Simulation results show that the proposed architecture is a promising candidate for real implementation, since it can achieve high performance with much lower complexity even in a rich multipath environment with low signal to noise plus interference ratio (SNIR).