A low cost soft mapper for turbo equalization with high order modulation

In an MMSE based turbo equalization system, a soft mapper calculates the symbol mean and variance based on extrinsic Log-Likelihood-Ratios (LLRs) information coming from a Soft-Input Soft-Output (SISO) decoder. In this paper, we investigate the complexity of this module, and in particular, we employ a 3-segment linear approximation approach to calculate the mean and variance of data symbols from LLRs. For FPGA and VLSI implementation, we propose novel piecewise linear functions which map LLR to the mean and variance directly without the use of any two-variable-input multipliers. Simulation results for 16-QAM and 64-QAM show that the no multiplier approach has close BER performance to the 3-segment linear approximation approach with multipliers. © 2012 IEEE

A low cost soft mapper for turbo equalization with high order modulation

In an MMSE based turbo equalization system, a soft mapper calculates the symbol mean and variance based on extrinsic Log-Likelihood-Ratios (LLRs) information coming from a Soft-Input Soft-Output (SISO) decoder. In this paper, we investigate the complexity of this module, and in particular, we employ a 3-segment linear approximation approach to calculate the mean and variance of data symbols from LLRs. For FPGA and VLSI implementation, we propose novel piecewise linear functions which map LLR to the mean and variance directly without the use of any two-variable-input multipliers. Simulation results for 16-QAM and 64-QAM show that the no multiplier approach has close BER performance to the 3-segment linear approximation approach with multipliers. © 2012 IEEE

Inter-carrier interference mitigation for underwater acoustic communications

Communicating at a high data rate through the ocean is challenging. Such communications must be acoustic in order to travel long distances. The underwater acoustic channel has a long delay spread, which makes orthogonal frequency division multiplexing (OFDM) an attractive communication scheme. However, the underwater acoustic channel is highly dynamic, which has the potential to introduce significant inter-carrier interference (ICI). This thesis explores a number of means for mitigating ICI in such communication systems. One method that is explored is directly adapted linear turbo ICI cancellation. This scheme uses linear filters in an iterative structure to cancel the interference. Also explored is on-off keyed (OOK) OFDM, which is a signal designed to avoid ICI

A Unified Framework for Linear-Programming Based Communication Receivers

It is shown that a large class of communication systems which admit a sum-product algorithm (SPA) based receiver also admit a corresponding linear-programming (LP) based receiver. The two receivers have a relationship defined by the local structure of the underlying graphical model, and are inhibited by the same phenomenon, which we call 'pseudoconfigurations'. This concept is a generalization of the concept of 'pseudocodewords' for linear codes. It is proved that the LP receiver has the 'maximum likelihood certificate' property, and that the receiver output is the lowest cost pseudoconfiguration. Equivalence of graph-cover pseudoconfigurations and linear-programming pseudoconfigurations is also proved. A concept of 'system pseudodistance' is defined which generalizes the existing concept of pseudodistance for binary and nonbinary linear codes. It is demonstrated how the LP design technique may be applied to the problem of joint equalization and decoding of coded transmissions over a frequency selective channel, and a simulation-based analysis of the error events of the resulting LP receiver is also provided. For this particular application, the proposed LP receiver is shown to be competitive with other receivers, and to be capable of outperforming turbo equalization in bit and frame error rate performance.Comment: 13 pages, 6 figures. To appear in the IEEE Transactions on Communication

Low-complexity soft-decision feedback turbo equalization for multilevel modulations

This dissertation proposes two new decision feedback equalization schemes suitable for multilevel modulation systems employing turbo equalization. One is soft-decision feedback equalization (SDFE) that takes into account the reliability of both soft a priori information and soft decisions of the data symbols. The proposed SDFE exhibits lower signal to noise ratio (SNR) threshold that is required for water fall bit error rate (BER) and much faster convergence than the near-optimal exact minimum mean square error linear equalizer (Exact-MMSE-LE) for high-order constellation modulations. The proposed SDFE also offers a low computational complexity compared to the Exact-MMSE-LE. The drawback of the SDFE is that its coefficients cannot reach the matched filter bound (MFB) and therefore after a large number of iterations (e.g. 10), its performance becomes inferior to that of the Exact-MMSE-LE. Therefore, soft feedback intersymbol interference (ISI) canceller-based (SIC) structure is investigated. The SIC structure not only exhibits the same low complexity, low SNR threshold and fast convergence as the SDFE but also reaches the MFB after a large number of iterations. Both theoretical analysis and numerical simulations demonstrate why the SIC achieves MFB while the SDFE cannot. These two turbo equalization structures are also extended from single-input single-output (SISO) systems to multiple-input multiple-output (MIMO) systems and applied in high data-rate underwater acoustic (UWA) communications --Abstract, page iv

MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity

In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts

Extreme Learning Machine Based Non-Iterative and Iterative Nonlinearity Mitigation for LED Communications

This work concerns receiver design for light emitting diode (LED) communications where the LED nonlinearity can severely degrade the performance of communications. We propose extreme learning machine (ELM) based non-iterative receivers and iterative receivers to effectively handle the LED nonlinearity and memory effects. For the iterative receiver design, we also develop a data-aided receiver, where data is used as virtual training sequence in ELM training. It is shown that the ELM based receivers significantly outperform conventional polynomial based receivers; iterative receivers can achieve huge performance gain compared to non-iterative receivers; and the data-aided receiver can reduce training overhead considerably. This work can also be extended to radio frequency communications, e.g., to deal with the nonlinearity of power amplifiers

Simulation and Complexity Analysis of Iterative Interference Cancellation Receivers for LTE/LTE-Advanced

The paper details the simulation of a single user MIMO receiver operating according to the 3GPP/LTE standard applying a Parallel or Successive Interference Cancellation (PIC/SIC) strategy to a multicarrier (OFDMA/SC-FDMA) scheme. The algorithm details are analyzed and the PIC and SIC cancellation strategies are simulated and compared on random MIMO selective fading channels, considering limited complexities. The best PIC and SIC schemes for a given limited complexity (8 turbo decoding iterations per codeword) are compared for different codeblock lengths and spatial correlation scenarios over an EPA channel model. The 2 cycles SIC scheme shows the best performance over the selected scenarios, offering gains over the non-iterative schemes (measured at BLER values of 0.1) ranging from 1 to 4 dB in the considered cases. Larger gains are obtained with higher spatial correlation and shorter codeblock lengths. Better overall performance are obtained with lower spatial correlation and longer codeblock lengths

Low-complexity iterative receiver algorithms for multiple-input multiple-output underwater wireless communications

This dissertation proposes three low-complexity iterative receiver algorithms for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. First is a bidirectional soft-decision feedback Turbo equalizer (Bi-SDFE) which harvests the time-reverse diversity in severe multipath MIMO channels. The Bi-SDFE outperforms the original soft-decision feedback Turbo equalizer (SDFE) while keeping its total computational complexity similar to that of the SDFE. Second, this dissertation proposes an efficient direct adaptation Turbo equalizer for MIMO UWA communications. Benefiting from the usage of soft-decision reference symbols for parameter adaptation as well as the iterative processing inside the adaptive equalizer, the proposed algorithm is efficient in four aspects: robust performance in tough channels, high spectral efficiency with short training overhead, time efficient with fast convergence and low complexity in hardware implementation. Third, a frequency-domain soft-decision block iterative equalizer combined with iterative channel estimation is proposed for the uncoded single carrier MIMO systems with high data efficiency. All the three new algorithms are evaluated by data recorded in real world ocean experiment or pool experiment. Finally, this dissertation also compares several Turbo equalizers in single-input single-output (SISO) UWA channels. Experimental results show that the channel estimation based Turbo equalizers are robust in SISO underwater transmission under harsh channel conditions --Abstract, page iv