Due to the reuse factor reduction, the same frequencies are reused in adjacent neighboring cells, which causes an attendant increase in co-channel interference (CCI). CCI has already become the limiting factor in the performance of orthogonal frequency division multiplexing (OFDM) based cellular systems. Joint maximum likelihood sequence estimation (JMLSE) based interference cancellation algorithms have been under intense research. However, despite the fact that the error probability of JMLSE is critical for analyzing the performance, to the best of our knowledge, the mathematical expression has not been derived for MQAM-OFDM yet. Direct computation of the error probability involves integrating a multi-dimensional Gaussian distribution that has no closed-form solution. Therefore, an alternative way is to upper and lower bound the error probability with computable quantities. In this paper, firstly, both the upper and the conventional lower error probability bounds of JMLSE are derived for MQAM-OFDM systems based on a genie-aided receiver. Secondly, in order to reduce the gap between the conventional lower bound and the simulation results, a tighter lower bound is derived by replacing the genie with a less generous one. Thirdly, those derived error probability bounds are generalized to the receiver diversity scheme. These error probability bounds are important new analytical results that can be used to provide rapid and accurate estimation of the BER performance over any MQAM scheme and an arbitrary number of interferers and receive antennas.

Due to the reuse factor reduction, the attendant increase in co-channel interference (CCI) becomes the limiting factor in the performance of the orthogonal frequency division multiplexing (OFDM) based cellular systems. In the previous work, we proposed the least mean square-blind joint maximum likelihood sequence estimation (LMS-BJMLSE) algorithm, which is effective for CCI cancellation in OFDM systems with only one receive antenna. However, LMS-BJMLSE requires a long training sequence (TS) for channel estimation, which reduces the transmission efficiency. In this paper, we propose a subcarrier identification and interpolation algorithm, in which the subcarriers are divided into groups based on the coherence bandwidth, and the slowest converging subcarrier in each group is identified by exploiting the correlation between the mean-square error (MSE) produced by LMS and the mean-square deviation (MSD) of the desired channel estimate. The identified poor channel estimate is replaced by the interpolation result using the adjacent subcarriers' channel estimates. Simulation results demonstrate that the proposed algorithm can reduce the required training sequence dramatically for both the cases of single interference and dual interference. We also generalize LMS-BJMLSE from single antenna to receiver diversity, which is shown to provide a huge improvement.

In this paper, we investigate two receiver structures for spatially multiplexed transmission on MIMO frequency selective fading channels. Those receivers compensate the IAI (Inter-Antenna Interference) and ISI (Inter-Symbol Interference) in the time domain. We first propose the MIMO sequential equalizer in which the block of several receives symbols is processed symbol by symbol by MLD (Maximum Likelihood Detection). Next we investigate the MIMO MLSE (Maximum Likelihood Sequence Estimation) receiver in which the terminated block trellis is decoded by the Viterbi algorithm. The bit error rates of two time domain receivers are examined through computer simulations and we also compare their BER characteristics to those of the conventional MIMO SC-FDE.

Conventional RFID interrogators use symbol-by-symbol-based detectors such as the matched filter and the edge detector for signal detection which do not sufficiently exploit the structure of the data-encoded waveforms. In this paper we propose a Viterbi-based algorithm to detect the data sequence of the RFID systems using the EPC-Global Generation-2 standard. By decomposing the associated data-encoded waveform on a half-cycle basis, the proposed approach first transfer the representation of the data-encoding scheme to a trellis diagram and thus leads to the application of the Viterbi algorithm for data sequence estimation. Also, different from the traditional Viterbi algorithm using correlation coefficient as the branch metrics, the proposed algorithm uses the absolute correlation coefficient as our branch metric which can exactly save the computational complexity of the Viterbi algorithm up to 50 percent. As compared to conventional approaches, the proposed algorithm can significantly improve the system performance due to its full exploitation of the baseband signal structure.

This paper proposes a novel MIMO system that introduces a heterogeneous stream (HTS) scheme and a blind signal detection method for mobile radio communications. The HTS scheme utilizes different modulation or coding methods for different MIMO streams, and the blind detection method requires no training sequences for signal separation, detection, and channel estimation. The HTS scheme can remove the ambiguity in identifying separated streams without unique words that are necessary in conventional MIMO blind detection. More specifically, two examples of HTS are considered: modulation type HTS (MHTS) and timing-offset type HTS (THTS). MHTS, which utilizes different modulation constellations with the same bandwidth for different streams, has been previously investigated. This paper proposes THTS which utilizes different transmission timing with the same modulation. THTS can make the blind detection more robust and effective with fractional sampling. The blind joint processing of detection and channel estimation performs adaptive blind MIMO-MLSE and is derived from an adaptive blind MLSE equalizer that employs the recursive channel estimation with the Moore-Penrose generalized inverse. Computer simulations show that the proposed system can achieve superior BER performance with Eb/N0 degradation of 1 dB in THTS and 2.5 dB in MHTS compared with the ideal maximum likelihood detection.

This paper proposes a maximum likelihood sequence estimation (MLSE) for the differential space-time block code (DSTBC) in cooperation with blind linear prediction (BLP) of fast frequency-flat fading channels. This method that linearly predicts the fading complex envelope derives its linear prediction coefficients by the method of Lagrange multipliers, and does not require data of decision-feedback or information on the channel parameters such as the maximum Doppler frequency in contrast to conventional ones. Computer simulations under fast fading conditions demonstrate that the proposed method with an appropriate degree of polynomial approximation is superior in BER performance to the conventional method that estimates the coefficients by the RLS algorithm using a training sequence.

This paper proposes a new blind adaptive MLSE equalizer for frequency selective mobile radio channels. The proposed equalizer performs channel estimation for each survivor path of the Viterbi algorithm (VA), and restricts the number of symbol candidates for the channel estimation in order to reduce prohibitive complexity. In such channel estimation, autocorrelation matrices of the symbol candidates are likely to become singular, which increases the estimation error. To cope with the singularity, the proposed equalizer employs a recursive channel estimation algorithm using the Moore-Penrose generalized inverse of the autocorrelation matrix. As another problem, the blind channel estimation can yield plural optimal estimates of a channel impulse response, and the ambiguity of the estimates degrades the BER performance. To avoid this ambiguity, the proposed equalizer is enhanced so that it can take advantage of the fractional sampling. The enhanced equalizer performs symbol-spaced channel estimation for each fractional sampling phase. This equalizer combines separate channel estimation errors, and provides the sum to the VA processor as the branch metric, which tremendously reduces the probability that a correct estimate turns into a false one. Computer simulation demonstrates the effectiveness of the proposed equalizers in the frequency selective fading channels.

This paper proposes low-complexity blind detection for orthogonal frequency division multiplexing (OFDM) systems with the differential space-time block code (DSTBC) under time-varying frequency-selective Rayleigh fading. The detector employs the maximum likelihood sequence estimation (MLSE) in cooperation with the blind linear prediction (BLP), of which prediction coefficients are determined by the method of Lagrange multipliers. Interpolation of channel frequency responses is also applied to the detector in order to reduce the complexity. A complexity analysis and computer simulations demonstrate that the proposed detector can reduce the complexity to about a half, and that the complexity reduction causes only a loss of 1 dB in average Eb/N0 at BER of 10-3 when the prediction order and the degree of polynomial approximation are 2 and 1, respectively.

This letter reports laboratory experiments of trellis-coded multiple-antenna systems. We evaluate the effect of spatial interleaving for the vector Viterbi algorithm under several conditions such as line-of-sight (LOS), non-LOS propagation, frequency-flat and frequency-selective channels.

In this paper, a new algorithm for the optimal training sequence with respect to sequence length in 1-dimensional cluster-based sequence equalizers (1-D CBSE) is presented. The proposed method not only removes the step of random training sequence selection but also shortens the length of the selected training sequences. The superiority of the new method is demonstrated by presenting several simulation results of quadrature phase shift keying (QPSK) signaling schemes and related analyses.

In this paper, we propose a new approach to the adaptive MLSE receiver, which is based on the delay estimation of the paths in the fading channel. The path delays are estimated by using the known training sequence, and based on this estimation the proposed MLSE tracks not the T-spaced equivalent channel but the variations of each path in the frequency-selective channel directly. It will be shown through computer simulations that the proposed MLSE can improve the performance of the conventional MLSE receivers, when the number of paths is small.

The maximum likelihood sequence estimator (MLSE) is usually implemented by the Viterbi algorithm (VA). The computational complexity of the VA grows exponentially with the length of the channel response. With some performance reduction, a decision-feedback equalizer (DFE) can be used to shorten the channel response. This greatly reduces the computational requirement for the VA. However, for many real-world applications, the complexity of the DFE/MLSE approach may be still too high. In this paper, we propose a constrained DFE that offers much lower VA computational complexity. The basic idea is to pose some constraints on the DFE such that the postcursors of the shortened channel response have only discrete values. As a result, the multiplication operations can be replaced by shift operations making the VA almost multiplication free. This will greatly facilitate the real world applications of the MLSE algorithm. Simulation results show that while the proposed algorithm basically offers the same performance as the original MLSE performance, the VA is much more efficient than the conventional approach.

This paper proposes a new nonlinear distortion compensation scheme for orthogonal multi-carrier modulation systems. Multi-carrier modulation is an effective technique for high speed digital transmission over time-dispersive channels, however, it is very sensitive to nonlinear distortion. The proposed scheme compensates for the performance degradation due to nonlinear distortion using the maximum likelihood (ML) detection criterion. While the ideal ML receiver requires a huge computational cost and is not feasible, the proposed decision algorithm can effectively reduce the computational cost. Instead of evaluating the likelihood function for all the possible sequences, the proposed scheme examines the sequences which differ by only one bit from the sequence decoded by the conventional receiver. Computer simulation results show that the proposed scheme can effectively compensate for the nonlinear distortion.

Future digital land mobile communication, for a moving picture, requires more transmission speed and less bit error rate than the existing system does for speech. In the system, the intersymbol interference may not be ignored, because of higher transmission speed. An adaptive equalizer is necessary to cancel intersymbol interference. To achieve low bit error rate performance on the mobile radio channel, trellis-coded modulation with interleaving is necessary. This paper proposes an interleaved trellis-coded modulation scheme combined with a decision feedback type adaptive equalizer of high performance. The reliable symbol reconstructed in the trellis decoder is used as the feedback signal. To make equalizer be free from decoding delay, deinterleaving is effectively utilized. The branch metric, for trellis-coded modulation decoding, is calculated as terms of squared errors between a received signal and an expected signal by taking the reconstructed symbol and the impulse response estimated by the recursive least squares algorithm into account. The metric is constructed to have good discrimination performance to incorrect symbols even in non-minimum phase and to realize path diversity effect in a frequency selective fading channel. Computer simulation results are shown for several channel models. On a frequency selective fading channel, average bit error rate is less than 1/100 of that of the RLS-MLSE equalizer for fdTs=1/1000 at average Eb/N0 beyond 15dB. Performance degradation due to equalization error is less than 1.8dB. Performance is greatly improved by the effect of the reconstructed symbol feedback.

This paper discusses the characteristics of the nonlinearly amplified spread–spectrum (SS) signals. We evaluate the symbol error–rate performance with the conventional receiver, changing the length of the spreading sequence. In addition, we also propose the receiver with MLSE. The configuration of the MLSE for the nonlinearly amplified signals is generally complicated; however we show that the complexity of the MLSE receiver can be reduced, as the number of required reference sequences in the receiver for an SS signal is small. As the result, it is shown that the error rate performance of the nonlinearly amplified SS signal can be improved by this proposed receiver and that the degradation caused by the nonlinear amplification can be made negligibly small with a sufficiently long spreading sequence.