Signal Constellation Size Research Articles

New rate-2 STBC design for 2 TX with reduced-complexity maximum likelihood decoding

We propose a new full-rate space-time block code (STBC) for two transmit antennas which can be designed to achieve maximum diversity or maximum capacity while enjoying optimized coding gain and reduced-complexity maximum-likelihood (ML) decoding. The maximum transmit diversity (MTD) construction provides a diversity order of 2Nr for any number of receive antennas Nr at the cost of channel capacity loss. The maximum channel capacity (MCC) construction preserves the mutual information between the transmit and the received vectors while sacrificing diversity. The system designer can switch between the two constructions through a simple parameter change based on the operating signal-to-noise ratio (SNR), signal constellation size and number of receive antennas. Thanks to their special algebraic structure, both constructions enjoy low-complexity ML decoding proportional to the square of the signal constellation size making them attractive alternatives to existing full-diversity full-rate STBCs in [6], [3] which have high ML decoding complexity proportional to the fourth order of the signal constellation size. Furthermore, we design a differential transmission scheme for our proposed STBC, derive the exact ML differential decoding rule, and compare its performance with competitive schemes. Finally, we investigate transceiver design and performance of our proposed STBC in spatial multiple-access scenarios and over frequency-selective channels.

Performance evaluation of spatially multiplexed MIMO systems with subset antenna transmission in interference limited environments

Transmit antenna selection in spatially multiplexed multiple-input multiple-output (MIMO) systems is a low complexity low-rate feedback technique, which involves transmission of a reduced number of streams from the maximum possible to improve the error rate performance of linear receivers. It has been shown to be effective in enhancing the performance of single-user interference-free point-to-point MIMO systems. However, performance of transmit antenna selection techniques in interference-limited environments and over frequency selective channels is less well understood. In this paper, we investigate the performance of transmit antenna selection in spatially multiplexed MIMO systems in the presence of co-channel interference. We propose a transmission technique for the downlink of a cellular MIMO system that employs transmit antenna selection to minimize the effect of co-channel interference from surrounding cells. Several transmit antenna selection algorithms are proposed and their performance is evaluated in both frequency flat and frequency selective channels. Various antenna selection algorithms proposed in the literature for single user MIMO links are extended to a cellular scenario, where each user experiences co-channel interference from the other cells (intercell interference) in the system. For frequency selective channels, we consider orthogonal frequency division multiplexing (OFDM) with MIMO. We propose a selection algorithm that maximizes the average output SINR over all subcarriers. A method to quantify selection gain in frequency selective channel is discussed. The effect of delay spread on the selection gain is studied by simulating practical fading environments with different delay spreads. The effect of the variable signal constellation sizes and the number of transmitted streams on the bit error rate (BER) performance of the proposed system is also investigated in conjunction with the transmit antenna selection. Simulation results show that for low to moderate interference power, significant improvement in the system performance is achievable with the use of transmit antenna selection algorithms. Even though the gain due to selection in frequency selective channels is reduced compared to that in flat fading channels due to the inherent frequency diversity, the performance improvement is significant when the system is interference limited. The performance improvement due to reduced number of transmit streams at larger signal constellation sizes is found to be more significant in spatially correlated scenarios, and the gain due to selection is found to be reduced with the increased delay spread. It is found that employing transmit antenna selection algorithms in conjunction with adaptation of the number of transmitted streams and the signal constellation sizes can significantly improve the performance of MIMO systems with co-channel interference.

A System Level Energy Model and Energy-Quality Evaluation for Integrated Transceiver Front-Ends

As CMOS technology scales down, digital supply voltage and digital power consumption goes down. However, the supply voltage and power consumption of the RF front-end and analog sections do not scale in a similar fashion. In fact, in many state-of-the-art communication transceivers, RF and analog sections can consume more energy compared to the digital part. In this paper, first, a system level energy model for all the components in the RF and analog front-end is presented. Next, the RF and analog front-end energy consumption and communication quality of three representative systems are analyzed: a single user point-to-point wireless data communication system, a multi-user code division multiple access (CDMA)-based system and a receive-only video distribution system. For the single user system, the effect of occupied signal bandwidth, peak-to-average ratio (PAR), symbol rate, constellation size, and pulse-shaping filter roll-off factor is analyzed; for the CDMA-based multi-user system, the effect of the number of users in the cell and multiple access interference (MAI) along with the PAR and filter roll-off factor is studied; for the receive-only system, the effect of 1/f noise for direct-conversion receiver and the effect of IF frequency for low-IF architecture on the RF front-end power consumption is analyzed. For a given communication quality specification, it is shown that the energy consumption of a wireless communication front-end can be scaled down by adjusting parameters such as the pulse shaping filter roll-off factor, constellation size, symbol rate, number of users in the cell, and signal center frequency

Near-Optimum Soft Decision Equalization for Frequency Selective MIMO Channels

In this paper, we develop soft decision equalization (SDE) techniques for frequency selective multiple-input multiple-output (MIMO) channels in the quest for low-complexity equalizers with error performance competitive to that of maximum likelihood (ML) sequence detection. We demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered and linear in the signal constellation size. Building on the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. The first SDE algorithm adopts a zero-padded transmission structure to convert the challenging sequence detection problem into a block-by-block least-square formulation. It introduces key enhancement to the original PDA to enable applications in rank-deficient channels and for higher level modulations. The second SDE algorithm takes advantage of the Toeplitz channel matrix structure embodied in an equalization problem. It processes the data samples through a series of overlapping sliding windows to reduce complexity and, at the same time, performs implicit noise tracking to maintain near-optimum performance. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Simulation comparisons of our SDE methods with minimum-mean-square error (MMSE)-based MIMO DFE and sphere decoded quasi-ML detection are presented.

Errors and erasures decoding of bch and reed~solomon codes for reduced m-ary orthogonal signaling

The paper presents a comparison of communication systems using different signal constellation sizes and Reed-Solomon or Bose-Chaudhuri-Hocquengem codes with different rates so that the overall required bandwidth is the same for each system. In these comparisons, the channel symbol size is smaller than the code symbol size, so that a code symbol contains parts of multiple channel symbols. Thus, the normal assumption of independent code symbols does not apply. Instead, consideration must be taken to obtain the best arrangement of channel symbols in each code symbol. Analytical expressions are developed to compare the bit error probability performance of comparable systems, based on individual codewords using errors-only decoding and errors and erasures decoding with transmission over a Rayleigh fading channel.

Examination of an adaptive dfe and MLSE/near-MLSE for fading multipath radio channels

This paper examines the performance over an HF channel of two adaptive equalisers; the decision feedback equaliser (DFE) and the maximum likelihood sequence estimator (MLSE), or an approximation to it (near-MLSE). It is shown that the superiority of the more complex MLSE/near-MLSE over the DFE is not great, and that this advantage is only due to error propagation in the DFE. In the absence of any special arrangement by which the receiver can re-align itself (e.g. periodic training), 16-QAM appears to be the highest feasible signal constellation size. With the periodic insertion of known symbols into the data stream, it is shown that performance can be maintained near the level for which decision errors do not affect the tracking algorithm. With the facility of a request-for-training link to the transmitter, it is shown that performance can be significantly improved for all constellation sizes, with only a small loss in the useful data rate.