We consider a physical-layer network coding (PNC) scheme based on M-ary continuous phase frequency shift keying (M-CPFSK) modulation for a bidirectional relay network. In this scheme, the maximum-likelihood sequence detection (MLSD) algorithm for the relay receiver over Rayleigh fading channels is discussed. Moreover, an upper bound on the minimum Euclidean distance for the superimposed signals is analyzed and the corresponding lower bound for the average symbol error rate (SER) at the relay is derived. Numerical results are also sustained by simulations which corroborate the exactness of the theoretical analysis.

In this paper, the Voronoi region of the transmitted codeword is employed to improve the sphere bound on the maximum-likelihood decoding (MLD) performance of binary linear block codes over additive white Gaussian noise (AWGN) channels. We obtain the improved sphere bounds both on the frame-error probability and the bit-error probability. With the framework of the sphere bound proposed by Kasami et al., we derive the conditional decoding error probability on the spheres by defining a subset of the Voronoi region of the transmitted codeword, since the Voronoi regions of a binary linear block code govern the decoding error probability analysis over AWGN channels. The proposed bound improves the sphere bound by Kasami et al. and the sphere bound by Herzberg and Poltyrev. The computational complexity of the proposed bound is similar to that of the sphere bound by Kasami et al.

This paper proposes performance improvement schemes for non-coherent multiple-input multiple-output (MIMO) communication systems employing per transmit antenna differential mapping (PADM). PADM is one form of differential space-time coding (DSTC), which generates an independent differentially encoded sequence for each of the multiple transmit antennas by means of space-time coding and mapping. The features of the proposed schemes are as follows: 1) it employs an asymmetric space-time mapping instead of the conventional symmetric space-time mapping in order to lower the required signal to noise power ratio (SNR) for maintaining the bit error rate (BER) performance; 2) it employs an analytically derived branch metric criterion based on channel prediction for per-survivor processing (PSP) in order to track fast time-varying channels. Finally, computer simulation results confirm that the proposed schemes improve the required SNR by around 1dB and can track at the maximum Doppler frequency normalized by symbol rate of 5%.

A maximum-likelihood code acquisition scheme is investigated for frequency-selective fading channels with an emphasis on the decision strategies. Using the maximum-likelihood estimation technique, we first derive an optimal decision rule, which is optimal in the viewpoint of probability of detection. Based on the derived optimal decision rule, a practical and simple decision rule is also developed, and its performance is assessed for both single dwell and double dwell acquisition systems. Simulation results demonstrate that the proposed acquisition scheme significantly outperforms the previously proposed schemes in frequency-selective fading channels.

A joint continuous phase frequency shift keying (CPFSK) modulation and physical-layer network coding (PNC), i.e., CPFSK-PNC, is proposed for two-way relay channels (TWRCs). This letter discusses the signal detection of the CPFSK-PNC scheme with emphasis on the maximum-likelihood sequence detection (MLSD) algorithm for the relay receiver. The end-to-end error performance of the proposed CPFSK-PNC scheme is evaluated through simulations.

This letter presents a technique to reduce the complexity of the soft-output multiple-input multiple-output symbol detection based on Dijkstra's algorithm. By observing that the greedy behavior of Dijkstra's algorithm can entail unnecessary tree-visits for the symbol detection, this letter proposes a technique to evict non-promising candidates early from the search space. The early eviction technique utilizes layer information to determine if a candidate is promising, which is simple but effective. When the SNR is 30dB for 6×6 64-QAM systems, the average number of tree-visits in the proposed method is reduced by 72.1% in comparison to that in the conventional Dijkstra's algorithm-based symbol detection without the early eviction.

This letter proposes a low-complexity soft-detection algorithm for modified dual-carrier modulation (MDCM) in WiMedia ultra-wideband (UWB) systems. In order to reduce the complexity of soft-output maximum-likelihood detection (soft-MLD), which gives the optimal performance for MDCM symbols, the proposed algorithm utilizes the following three methods: real/imaginary separation, multiplierless distance calculation, and candidate set reduction. Through these methods, the proposed algorithm reduces the complexity of soft-MLD by 97%, while preventing the deterioration of its optimality. The performance of the proposed algorithm is demonstrated by simulations of 640–1024 Mbps transmission modes of the latest Release 1.5 standard of the WiMedia UWB.

For maximum-likelihood (ML) estimation to jointly track carrier frequency offset (CFO) and channel impulse response (CIR) in orthogonal frequency division multiplexing (OFDM) systems, we present a finite high order approximation method utilizing the MATLAB ‘roots' command on the log-likelihood function derived from the OFDM received signal, coupled with an adaptive iteration algorithm. The tracking performance of this high order approximation algorithm is found to be excellent, and as expected, the algorithm outperforms the other existing first order approximation algorithms.

This paper proposes non-coherent multiple-input multi-ple-output (MIMO) communication systems employing per transmit antenna differential mapping (PADM), which generates an independent differentially encoded sequence for each of the multiple transmit antennas by means of space-time coding and mapping. At a receiver, the proposed PADM employs adaptive maximum-likelihood detection (MLD). The features of PADM are as follows: 1) it has excellent tracking performance for fast time-varying fading channels, because it can detect transmitted data without needing channel state information (CSI); 2) it can be applied not only to transmit diversity (TD) but also to spatial multiplexing (SM). In this paper, we analyze the adaptive MLD based on pseudo matrix inversion and derive its metric for data detection. In order to satisfy requirements on multiple transmitted sequences for the adaptive MLD, this paper proposes a mapping rule for PADM. Next, this paper describes a receiver structure based on per-survivor processing (PSP), which can drastically reduce the complexity of adaptive MLD. Finally, computer simulations confirm that the proposed non-coherent MIMO communication systems employing PADM have excellent tracking capability for TD and SM on fast time-varying fading channels.

This paper proposes an efficient list extension algorithm for soft-output multiple-input-multiple-output (soft-MIMO) detection. This algorithm extends the list of candidate vectors based on the vector selected by initial detection, in order to solve the empty-set problem, while reducing the number of additional vectors. The additional vectors are obtained from multiple detection orders, from which high-quality soft-output can be generated. Furthermore, a method to reduce the complexity of the determination of the multiple detection orders is described. From simulation results for a 44 system with 16- and 64-quadrature amplitude modulations (QAM) and rate 1/2 and 5/6 duo-binary convolutional turbo code (CTC), the soft-MIMO detection to which the proposed list extension was applied showed a performance degradation of less than 0.5 dB at bit error rate (BER) of 10-5, compared to that of the soft-output maximum-likelihood detection (soft-MLD) for all code rate and modulation pairs, while the complexity of the proposed list extension was approximately 38% and 17% of that of an existing algorithm with similar performance in a 44 system using 16- and 64-QAM, respectively.

The probability of making mistakes on the decoded signals at the relay has been used for the maximum-likelihood (ML) decision at the receiver in the decode-and-forward (DF) relay network. It is well known that deriving the probability is relatively easy for the uncoded single-antenna transmission with M-pulse amplitude modulation (PAM). However, in the multiplexing multiple-input multiple-output (MIMO) transmission, the multi-dimensional decision region is getting too complicated to derive the probability. In this paper, a high-performance near-ML decoder is devised by applying a well-known pairwise error probability (PEP) of two paired-signals at the relay in the MIMO DF relay network. It also proves that the near-ML decoder can achieve the maximum diversity of MSMD+MR min (MS,MD), where MS, MR, and MD are the number of antennas at the source, relay, and destination, respectively. The simulation results show that 1) the near-ML decoder achieves the diversity we derived and 2) the bit error probability of the near-ML decoder is almost the same as that of the ML decoder.

An efficient pruning method is proposed for the infinity-norm sphere decoding based on Schnorr-Euchner enumeration in multiple-input multiple-output spatial multiplexing systems. The proposed method is based on the characteristics of the infinity norm, and utilizes the information of the layer at which the infinity-norm value is selected in order to decide unnecessary sub-trees that can be pruned without affecting error-rate performance. Compared to conventional pruning, the proposed pruning decreases the average number of tree-visits by up to 37.16% in 44 16-QAM systems and 33.75% in 66 64-QAM systems.

In this letter, we propose an efficient on-the-fly algorithm for maximum-likelihood decoding of Raptor codes used over the binary erasure channel. It is shown that our proposed decoding algorithm can reduce the actual elapsed decoding time by more than two-thirds with respect to an optimized conventional maximum-likelihood decoding.

The letter deals with direction-of-arrival (DOA) estimation under nonuniform white noise and moderately small signal-to-noise ratios. The proposed approach first uses signal subspace projection for received data vectors, which form an efficient iterative quadratic maximum-likelihood (IQML) approach to achieve fast convergence and high resolution capabilities. In conjunction with a signal subspace selection technique, a more exact signal subspace can be obtained for reducing the nonuniform noise effect. The performance improvement achieved by applying the proposal to the classic IQML method is confirmed by computer simulations.

An adaptive per-survivor processing maximum likelihood sequence estimation (PSP-MLSE) using state-space based recursive least-squares (RLS) is proposed for rapidly time varying multi-path fading channels. Unlike PSP-MLSE using Kalman filtering, it does not require the knowledge of model statistics, and with an aid of state-space modeling, it has a robust performance to the fade rate, compared to PSP-MLSE using conventional RLS.

This letter introduces an efficient near-maximum likelihood (ML) detector for a coded double space-time transmit diversity-orthogonal frequency division multiplexing (DSTTD-OFDM) system. The proposed near-ML detector constructs a candidate vector set through a relaxed minimization method. It reduces computational loads from O(2|A|2) to O(|A|2), where |A| is the modulation order. Numerical results indicate that the proposed near-ML detector provides both almost ML performance and considerable complexity savings.

Phase noise (PHN) can cause the common phase error (CPE) and the inter-carrier interference (ICI), both of which impair the accurate channel estimation in orthogonal frequency division multiplexing (OFDM) systems. In this letter, we build a new signal model parameterized by the channel impulse response, the CPE and the ICI. Based on this model, we derive the maximum likelihood estimator (MLE) and the minimum mean square error estimator (MMSEE). Simulation results show that the proposed schemes significantly improve the performance of OFDM systems in the presence of PHN.

This paper proposes a channel estimation technique which uses a postfixed pseudo-noise (PN) sequence combined with zero padding to accurately estimate the channel impulse response for mobile orthogonal frequency division multiplexing (OFDM) communications. The major advantage of the proposed techniques is the periodical insertion of PN sequences after each OFDM symbol within the original guard interval in conventional zero-padded OFDM or within the original cyclic prefix (CP) in conventional CP-OFDM. In addition, the proposed technique takes advantage of null samples padded after the PN sequences for reducing inter-symbol interference occurring with the information detection in conventional pseudo-random-postfix OFDM. The proposed technique successfully applies either (1) least-squares algorithm with decision-directed data-assistance, (2) approximate least-squares estimation, or (3) maximum-likelihood scheme with various observation windows for the purpose of improving channel estimation performance. Some comparative simulations are given to illustrate the excellent performance of the proposed channel estimation techniques in mobile environments.

We present a low-complexity maximum likelihood (ML) detector for a coded double space-time transmit diversity-orthogonal frequency division multiplexing (DSTTD-OFDM) system. The proposed ML detector exploits properties of two permuted equivalent channel matrices and multiple decision-feedback (DF) detections. This can reduce computational efforts from O(|A|4) to O(2|A|2) with maintaining ML performance, where |A| is the modulation order. Numerical results shows that the proposed ML detector obtains ML performance and requires remarkably lower computational loads compared with the conventional ML detector.

This letter deals with computationally efficient maximum-likelihood (ML) detection for the quasi-orthogonal space-time block code (QOSTBC) with four transmit antennas. The proposed ML detector uses a permutation based real-valued equivalent channel matrix representation. As a result, the complexity of ML detection problem is moderated from O(2|A|2) to O(4|A|), where |A| is modulation order. Numerical results show that the proposed ML detector provides ML performance and achieves greatly high computational savings.