Adaptive transmission techniques including transmit beamforming, preceding, and opportunistic scheduling offer high spectral efficiency when channel state information at the transmitter (CSIT) is accurate, but suffer performance loss when the CSIT quality is poor. Diversity transmission techniques such as space-time coding and frequency interleaving, in contrast, are capable of capturing spatial and spectral diversity without CSIT, hence can provide good performance when CSIT degradation is severe. Between a pair of adaptive and diversity techniques, there exists a switching point in terms of the CSIT-quality; a CSIT- quality higher than this point favors the adaptive technique, but a lower CSIT-quality prefers the diversity one. This paper analyzes several adaptive and diversity schemes for a multiuser multiple-input single-output (MISO) system. Comparative performance in terms of the outage capacity is studied and the CSIT-quality switching points between adaptive and diversity schemes are analyzed. Results are supportive of adaptive transmissions for mobile applications, such as in the downlink of an orthogonal frequency division multiple access (OFDMA) system.

In this paper we study the downlink spectral efficiency of a wireless network using orthogonal frequency division multiple access (OFDMA), multiple input multiple output (MIMO) antenna systems and opportunistic scheduling (OS) techniques. The main purpose of the study is to understand how these techniques interact and influence the spectral efficiency of the network for different antenna configurations and scheduling policies given the coherence bandwidth of the channel and mobile speed. We will use the point-to-point link Shannon outage capacity as the underlying metric for evaluating the overall throughput of the network. The results illustrate the relationships between the different techniques.

This paper describes a low-complexity turbo equalizer for coded sparse multipath channels whose length can span hundreds of symbol intervals. First, for single-input-single-output (SISO) systems, an existing parallel-trellis framework, which consists of a bank of identical regular trellises, is exploited to construct the maximum a posteriori (MAP) equalizer in the turbo equalizer. This MAP equalizer, when combined with prefiltering, can equalize a broad selection of sparse multipath channels, including those with nonminimum phase, by using only M-state trellises, where M is the constellation size. For multiple-input-multiple-output (MIMO) systems, a MIMO prefilter and a bank of M-state parallel-trellis MAP equalizers are deployed according to a layering structure. The total number of states needed is only NTM, where NTis the number of transmit antennae. For both SISO and MIMO systems, a class of binary convolutional and turbo codes having sparse generator polynomials are chosen as the coding schemes. These codes partially integrate channel interleaving with encoding, which allows a simple channel interleaver with low latency and memory storage requirement to be employed. The MAP decoders for these codes can also be implemented with the same parallel-trellis framework as the MAP equalizers. Overall, parallel processing is supported throughout the turbo equalizers. The amount of computational time reduction when compared to a turbo equalizer using a single-trellis MAP equalizer and decoder is proportional to the number of trellises in the parallel-trellis MAP equalizer and decoder. The performance of the parallel-trellis turbo equalizers is evaluated on static and Rayleigh fading sparse multipath channels via Monte Carlo simulations

Analytical expressions that explicitly indicate the tap values and tap positions of infinite-length, T-spaced tapped-delay-line (TDL) equalizers for sparse multipath channels are derived. Simple design rules for allocating taps to finite-length, minimum mean-square error, nonuniformly spaced TDL equalizers (NU-Es) are formulated based on the derived results. The design-rule-based methodology demonstrates a better tradeoff between accuracy and efficiency than existing tap-allocation schemes. The resultant NU-Es also achieve a lower overall computational complexity than conventional, uniformly spaced TDL equalizers (U-Es) of the same span for both directly adaptive and channel-estimate-based implementations. Moreover, a square-root raised cosine (SRRC) receive filter matched to a SRRC transmit filter is better than a matched filter when used to precede a NU-E.

A novel coding and turbo equalization scheme for sparse multipath channels is presented in this paper. A burst-error-correcting convolutional code, which coding and interleaving via a sparse encoder and a convolutional interleaver, is selected as the channel code. A previously-proposed parallel-trellis framework is adopted for implementing the maximum a posteriori (MAP) equalizer and decoder in the turbo equalizer. Such a system exhibits a similar level of performance to a conventional system using a random-error-correcting convolutional code together with a row /column (R/C) or random block interleaver. Yet, the proposed system has the advantages of low latency and low memory requirements when compared to those conventional systems. This is due to (i) the elimination of the block-type interleavers and deinterleavers and (ii) the parallelism achieved in the turbo equalizer. One disadvantage of the proposed system is to decrease in throughput, as more tail symbols are required for proper termination of all sub-trellises in the decoder. Extension of the proposed system to turbo codes is considered. Also, the effect of prefiltering on a nonminimum-phase, high definition television (HDTV) channel is examined. Results indicate that using the feedforward filter (FFF) of a nonuniformly-spaced decision feedback equalizer (NU-DFE) performs almost as good as using one with a large number of uniformly-spaced taps. However, far fewer computations are needed to find the optimum tap values of the sparse prefilter.

Performance comparisons between the conventional decision feedback equalizer (DFE) and an alternative design, known as the decision directed feedback equalizer (DDFE), are conducted with nonuniform spacings on sparse multipath channels. The optimum feedforward filters (FFF) of the DDFE and its variant under the minimum mean square error (MMSE) criterion are derived with the constraint of a nonuniformly spaced feedback filter (NU-FBF), and relationships regarding the optimum tap values and the resultant MMSE between FFF with uniform and nonuniform spacings are established. While the bit error rate (BER) results obtained confirm previous claims that the T-spaced NU-DDFE exhibit prominent improvement over the T-spaced NU-DFE in equalizing long sparse channels such as those encountered in high definition television (HDTV) systems, the gain is only minimal, if any, when applied on simpler sparse channels with fewer multipath terms. Moreover, using a T/2-spaced FFF in the NU-DDFE demands a T/2-spaced FBF to mitigate additional intersymbol interference (ISI) caused by the T/2-spaced channel samples, and a better method than the commonly-used thresholding scheme may be required to accurately determine the tap positions of the T/2-spaced NU-FBF.

The problem of designing nonuniformly-spaced tapped-delay-tine equalizers (NU-E) for sparse multipath channels is addressed. First, analytical expressions that explicitly indicate the tap positions and tap values of the infinite-length, T-spaced linear equalizers (LE) and decision feedback equalizers (DFE) under the zero-forcing (ZF) and minimum mean square error (MMSE) criteria are derived using the conventional matched receive filter (MF) and a square root raised cosine (SRRC) receive filter that is matched to a SRRC transmit filter. For both receive filter systems, the ZF-LE and the MMSE-LE for sparse multipath channels are nonuniformly-spaced with identical tap positions, but the ZF-DFE and MMSE-DFE are uniformly-spaced. Next, two suboptimum tap allocation algorithms based on the positions of large magnitude taps in the infinite-length, T-spaced equalizers are proposed for designing finite-length, T- and T/2-spaced MMSE NU-LE and NU-DFE. Results have shown that the proposed NU-E exhibit superior performance over uniformly-spaced tapped-delay-line equalizers (U-E) for the same number of taps, and only a small loss in SNR when compared to U-E with a large number of taps. Moreover, the SRRC receive filter is found to be a better front-end receive filter than the MF when used together with an appropriately-designed NU-E. A simple method that assigns extra T/2-spaced taps to improve the timing insensitivity of the proposed NU-E is also included.