In this work we consider the front-end receivers for flat fading MIMO transmission, whose essential feature is the calculation of the log-likelihood ratios (LLRs) for the transmitted bits. When the number of transmit antennas and the modulation size grow, the exact calculation of the LLRs is most often unfeasible due to the necessity to enumerate the symbols affecting the output. In this work, to avoid the burden of explicit enumeration, instead of calculating the likelihoods exactly, we explore the possibilities offered by the saddlepoint approximation of the likelihood functions. The resulting fixed-complexity approach significantly outperforms the well known linear-filter based minimum mean square error detection.

In this work, we consider the front-end receivers for flat fading MIMO transmission, whose essential feature is the calculation of the log-likelihood ratios (LLRs) for the transmitted bits. When the number of transmit antennas and the modulation size grow, the exact calculation of the LLRs becomes unfeasible due to the necessity to enumerate the symbols affecting the output. In this work, to avoid the burden of explicit enumeration, instead of calculating the likelihoods exactly, we explore the possibilities offered by the saddlepoint approximation of the likelihood functions. The resulting fixed-complexity approach significantly outperforms the well known linear-filter based minimum mean square error detection. A complexity analysis identifies the main computational bottleneck of the proposed detection algorithm.

Equalization for uplink MIMO SC-FDMA LTE multi-stream transmission is considered utilizing linear filtering methods and redundancy in the form of channel coding. The equalizer jointly removes inter-symbol (ISI) as well as spatial (MIMO) interference. It is observed that in an unequal received power situation, gains over traditional MMSE frequency equalization can be obtained via group-based cancellation with turbo equalization. It is shown that signal co-existence is possible with this methodology and therefore QoS for cell-edge users can be maintained at considerably higher noise levels as compared to a baseline receiver.

Iterative processing for linear matrix channels, aka turbo equalization, turbo demodulation, or turbo code-division multiple access (CDMA), has traditionally been addressed as the concatenation of conventional error control codes with the linear (matrix) channel. However, in several situations, such as CDMA, multiple-input-multiple-output (MIMO) channels, orthogonal frequency-division multiplexing (OFDM), and intersymbol-interference (ISI) channels, the channel itself either contains inherent signal redundancy or such redundancy can readily be introduced at the transmitter. For such systems, iterative demodulation of the linear channel exploiting this redundancy using simple iterative cancellation demodulators, followed by conventional feedforward error control decoding, provides a low-complexity, but extremely efficient decoding alternative. This two-stage demodulator/decoder outperforms more complex turbo CDMA methods for equal power modes (users). Furthermore, it is shown that arbitrary numbers of modes can be supported if an unequal power distribution is adopted. These power distributions are nested, which means that additional modes can be added without disturbing an existing mode population. The main result shows that these nested power distributions enable the two-stage receiver to approach the Shannon capacity of the channel to within less than one bit for any signal-to-noise ratio (SNR).