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Recently, a novel MLSE equalizer was reported, that does not require the explicit estimation of the channel impulse response. Instead, it utilizes, in an efficient manner, the estimates of the centers of the clusters formed by the received observations. In this paper, a novel cluster tracking scheme is presented, which extends the application of this equalizer in time-varying transmission environments. The proposed algorithm is shown to be equivalent in tracking performance with the classic LMS-based MLSE equalizer, yet much simpler computationally. This is a consequence of the fact that the new method allows for an efficient exploitation of the symmetries underlying the signaling scheme.  相似文献   
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Recently, a novel maximum-likelihood sequence estimation (MLSE) equalizer was reported that avoids the explicit estimation of the channel impulse response. Instead, it is based on the fact that the (noise-free) channel outputs, needed by the Viterbi algorithm, coincide with the points around which the received (noisy) samples are clustered and can thus be estimated directly with the aid of a supervised clustering method. Moreover, this is achieved in a computationally efficient manner that exploits the channel linearity and the symmetries underlying the transmitted signal constellation. The resulting computational savings over the conventional MLSE equalization scheme are significant even in the case of relatively short channels where MLSE equalization is practically applicable. It was demonstrated, via simulations, that the performance of this algorithm is close to that using a least-squares (LS) channel estimator, although its computational complexity is even lower than that of the least-mean squares (LMS)-trained MLSE equalizer. This paper investigates the relationship of the center estimation (CE) part of the proposed equalizer with the LS method. It is proved that, when using LS with the training sequence employed by CE, the two methods lead to the same solution. However, when LS is trained with random data, it outperforms CE, with the performance difference being proportional to the channel length. A modified CE method, called MCE, is thus developed, that attains the performance of LS with perfectly random data, while still being much simpler computationally than classical LS estimation. Through the results of this paper, CE is confirmed as a methodology that combines high performance, simplicity, and low computational cost, as required in a practical equalization task. An alternative, algebraic viewpoint on the CE method is also provided.  相似文献   
3.
The aim of this paper is to investigate receiver techniques for maximum likelihood (ML) joint channel/data estimation in flat fading multiple-input multiple-output (MIMO) channels, that are both (i) data efficient and (ii) computationally attractive. The performance of iterative least squares (LS) for channel estimation combined with sphere decoding (SD) for data detection is examined for block fading channels, demonstrating the data efficiency provided by the semi-blind approach. The case of continuous fading channels is addressed with the aid of recursive least squares (RLS). The observed relative robustness of the ML solution to channel variations is exploited in deriving a block QR-based RLS-SD scheme, which allows significant complexity savings with little or no performance loss. The effects on the algorithms’ performance of the existence of spatially correlated fading and line-of-sight paths are also studied. For the multi-user MIMO scenario, the gains from exploiting temporal/spatial interference color are assessed. The optimal training sequence for ML channel estimation in the presence of co-channel interference (CCI) is also derived and shown to result in better channel estimation/faster convergence. The reported simulation results demonstrate the effectiveness, in terms of both data efficiency and performance gain, of the investigated schemes under realistic fading conditions.  相似文献   
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The problem of finding N-K filters of an N-band maximally decimated FIR analysis filter bank, given K filters, so that FIR perfect reconstruction can be achieved, is considered. The perfect reconstruction condition is expressed as a requirement of unimodularity of the polyphase analysis filter matrix. Based on the theory of Euclidean division for matrix polynomials, the conditions the given transfer functions must satisfy are given, and a complete parameterization of the solution is obtained. This approach provides an interesting alternative to the method of the complementary filter in the case of N>2,K相似文献   
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In the context of the on‐going evolution of satellite communications (SatCom) systems to their next generation, and in the direction of their integration with fifth generation (5G) terrestrial networks, it is of interest to study in depth the applicability in realistic SatCom of waveforms that have shown promise to meet the 5G requirements. This paper presents a comparative study, based on total degradation (TD) over a range of output back‐off (OBO) values, on out‐of‐band emission and spectral efficiency, of frequency division multiple access (FDMA) schemes employing offset quadrature amplitude modulation‐based filter bank multi‐carrier (FBMC /OQAM), classical orthogonal FDMA (OFDMA), and their single‐carrier counterparts to illustrate the potential gains from the integration of the FBMC waveforms in the satellite context and standards. The air interface simulated follows the digital video broadcasting (DVB) family of standards for the satellite uplink, considering both time and frequency synchronization impairments and two typical input constellations. Our results confirm the superiority of the single‐carrier (SC) schemes in such a nonlinear environment. The SC‐FBMC waveform is shown to be the most practical candidate since it is shown to attain a TD performance similar to that of SC‐OFDM at absolutely no cost in spectral efficiency.  相似文献   
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