The performance of fano-multiple symbol differential detection

An architecture of decision feedback differential phase detection (DF-DPD) of M-ary DPSK signals is proposed. Conventional differential detection of M-ary DPSK signals uses the phase difference between a current symbol and the previous symbol. This method can make the receiver architecture simple. But it has poorer BER performance than coherent detection because it uses the previous noisy signal as the phase reference. To improve the BER performance of conventional differential detection, multiple symbol differential detection methods, such as maximum likelihood differential detection (ML-DD), Viterbi-DD, decision feedback differential detection (DF-DD), and DF-DPD, using L-1 past detected symbols, have been proposed. As L increases, the BER performance of DF-DPD improves but the complexity of the architecture increases dramatically. Thus, this paper proposes the simplified DF-DPD architecture, replacing the conventional delay and addition architecture with one accumulator. The proposed architecture also has a good BER performance with minimizing the phase error of the current received symbol using the accumulated phase differences of all DPD. The simulation results show that the BER performance of the proposed architecture approaches that of coherent detection.

In this paper we present decision-feedback differential detection (DF-DD) schemes for autocorrelation-based detection in impulse-radio ultra-wideband (IR-UWB) systems, a signaling scheme regarded as a promising candidate in particular for low-complexity wireless sensor networks. To this end, we first discuss ideal noncoherent sequence estimation and approximations thereof based on block-wise multiple-symbol differential detection (MSDD) and the Viterbi algorithm (VA) from the perspective of tree-search/trellis decoding. Exploiting relations well-known from tree-search decoding, we are able to derive the novel decision-feedback differential detection (DF-DD) schemes. A comprehensive comparison with respect to performance and complexity of the presented schemes in a typical IR-UWB scenario reveals-along with novel insights in techniques for complexity reduction of the sphere decoder applied for MSDD- that sorted DF-DD achieves close-to-optimum performance at very low, and in particular constant receiver complexity.

In distributed space-time coding cooperative systems, differential detection gains much attention because it needs no channel state information at the receivers. But conventional differential detection performs about 3dB loss than coherent detection. In this paper, we propose a multiple-symbol differential detection algorithm for relay networks based on maximum-likelihood principle. The simulation results show that the multiple-symbol differential detection can narrow the performance gap between the conventional differential detection and coherent detection for Alamouti and square real orthogonal coding systems with corresponding numbers of relays, especially in high signal-tonoise ratio regime. And with the increase of observation window size, the Doppler effect on performance is decreased and the error floor encountered in conventional differential detection can be eliminated provided that the value of observation window size is sufficiently high.

Approximately 3 dB signal-to-noise ratio (SNR) loss is always paid with conventional differential space-time block codes (STBCs), compared with coherent STBCs. In this paper, a multiple-symbol differential detection (MSDD) technique is proposed for M-ary phase-shift keying (PSK) STBCs. The new scheme can greatly narrow the 3-dB performance gap by extending the observation interval for differential decoding. The technique uses maximum-likelihood sequence detection instead of traditional symbol-by-symbol detection, and is carried out on the slow, flat Rayleigh fading channel. A generalized decision metric is derived for an observation interval of arbitrary length. It is shown that for a moderate number of symbols, MSDD provides approximately 1.5 dB performance improvement over conventional differential detection. In addition, a closed-form pairwise error probability and approximate bit-error probability (BEP) are derived for multiple-symbol differential binary PSK STBC. Results show that the theoretical BEP matches simulation results well. The BEP is shown to converge asymptotically with the number of symbols in the observation interval to that of the differential scheme with coherent detection.

In this paper, we propose a novel multiple symbol differential detection (MSDD) based on symbol error position estimation (SEPE) and compensation for use in terrestrial digital multimedia broadcasting (T-DMB) system. By estimating the symbol error position and compensating for the symbol error using MSDD outputs, it can improve the receive performance of T-DMB system. Also by providing soft-outputs to Viterbi decoder, an additional coding gain can be obtained. Simulation results in the typical urban (TU) channel show that the proposed algorithm is superior to the conventional differential detection (DD) and hard decision based MSDD T-DMB receivers.

In this paper, multiple-symbol differential detection (MSDD) is applied to the differential single-carrier frequency-division multiple access (SC-FDMA) system. Both time domain and frequency domain MSDD are investigated to compensate for the performance loss of conventional differential detection comparing with coherent detection. The decision metric of time and frequency domain MSDD for SC-FDMA are derived respectively. Simulation results demonstrate the effectiveness of MSDD in some situations.

We consider multiple?symbol differential detection (MSDD) for multiple?input multiple?output Rayleigh?fading channels. MSDD, which jointly processes blocks of received symbols to detect N -1 data symbols, allows for power?efficient transmission without requiring channel state information at the receiver. In previous work, we showed that computationally efficient sphere decoding algorithms can be used to accomplish MSDD. In this paper, we analyze the computational complexity of this sphere?decoding based MSDD. In particular, we prove by means of a lower bound that the complexity of the Fincke?Pohst multiple?symbol differential sphere decoder (FP?MSDSD), while being very low over wide ranges of N and signal?to?noise ratios, is exponential in N in principle. We further derive expressions for the exact complexity of FP?MSDSD, which allow for quick assessment of ranges of useful window sizes N.

The conventional multiple-symbol differential detection (MSDD) of differential phase-shift keying (DPSK) signals is studied in the presence of frequency offset. It is shown that in the case of nonzero frequency offset, the performance of the conventional MSDD receiver degrades by increasing the number of observed samples. A double DPSK (DDPSK) modulation scheme is then introduced and it is shown that in the presence of nonzero frequency offset, an MSDD receiver with DDPSK modulation outperforms a conventional MSDD receiver with DPSK modulation, when both receivers use a large number of received samples. Examples lead to a conjecture that the performance of an optimum MSDD receiver with DDPSK modulation and an infinite number of received samples, approaches that of a conventional DPSK demodulator with two received samples.

Multiple-symbol differential detection (MSDD) is a promising technique to enhance the performance of ultra-wideband (UWB) communications without estimating the channel explicitly. In this context, the generalized log-likelihood ratio test (GLRT) for MSDD was developed, and the hard-output multiple-symbol detector was proposed, which exhibits considerable bit-error-rate (BER) performance improvement over transmitted reference transmissions. In this paper, we further improve the system performance by incorporating error correction code (ECC) and iterative processing at the receiver. The soft-input soft-output (SISO) MSDD is developed to deliver a posteriori information to the outer ECC decoder and enables iterative detection and decoding. Simulations show that the iterative processing achieves significant gains over the existing MSDD in UWB communications.

Multiple-symbol differential detection (MSDD) for multiple-input-multiple-output Rayleigh-fading channels is considered. MSDD, which jointly processes blocks of N received symbols to detect N-1 data symbols, allows for power-efficient transmission without requiring channel state information at the receiver. In previous work, the authors showed that computational efficient sphere decoding algorithms can be used to accomplish MSDD. In this correspondence, the computational complexity of this sphere-decoding based MSDD is analyzed. In particular, it is proven by means of a lower bound that the complexity of the Fincke-Pohst multiple-symbol differential sphere decoder (FP-MSDSD), while being very low over wide ranges of N and signal-to-noise ratios, is exponential in N in principle. Furthermore, both exact and simple approximate expressions for the complexity of FP-MSDSD are derived, which allow for quick assessment of ranges of useful window sizes N of FP-MSDSD and show that the exponential rate of growth of the complexity of FP-MSDSD is asymptotically equal to that of brute-force MSDD

This paper addresses a multiple-symbol differential detection scheme for star 16QAM. At the outset, we analytically scrutinized conventional differential detection of star 16QAM. As a result, it emerged that the energy penalty of differential amplitude detection as compared with ideal coherent detection is larger than that of phase detection. Then to improve the overall performance of star 16QAM, we propose an MLSE algorithm for a large C/N as well as a suboptimum algorithm. Both of them allow multiple-symbol differential amplitude and phase detection. Their performances are also evaluated through computer simulation.KeywordsPhase DetectionEnergy PenaltyCoherent DetectionDifferential DetectionObservation SymbolThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

A novel approach to UWB data detection with symbol-level synchronization

Multiple symbol differential detection of /spl pi//4 QPSK in land mobile satellite communication channels (modeled as correlated Rician fading) is studied. BER performance of this scheme in land mobile satellite communication channels are evaluated using union bounds of pairwise bit error probabilities for situations of ideal channel information and no channel information. It has been found that in light or medium fading Rician channels, about a 1 dB gain in E/sub b//N/sub o/ at a BER=10/sup -4/ can be achieved by using four-symbol differential detection instead of conventional two-symbol differential detection. It is also proved that multiple-symbol differential detection is not suitable for severe fading Rician channels or Rayleigh channels. The influence of the fading rate on the BER performance is also evaluated. Part of the results are compared with those from previous literature.

The performance of multiple symbol differential detection applied to differentially encoded QPSK signals, is examined by simulation in the mobile radio channel with slow Rayleigh and Rician fading, and cochannel interference (CCI). Performance gains observed in the slow Rician fading channel when compared to conventional differential detection, are maintained in the CCI environment. Using a signal quality measure from the multiple symbol differential detection algorithm for selection diversity, performance gains are observed over conventional differential detection in Rayleigh fading as well. >

P174 ATTENUATING MULTIPLES FOR LOW SIGNAL- TO-NOISE RATIO DATA USING OPTIMAL BEAMFORMING 1 Abstract This paper presents the theory of optimal beamforming and its application in attenuating multiples for low signalto-noise (S/N) ratio data. The key point of the theory is updating the constraint in optimal beamformer design by using adaptive beamformer with the quiescent weighted vector. Real data example shows that the newly developed optimal beamformer has improved the minimum variance unbiased (MVU) beamformer significantly in attenuating multiples for low folding and/or low S/N ratio data without much extra cost. Introduction The objective of seismic data processing is to