1,235 research outputs found
Computable lower bounds for deterministic parameter estimation
This paper is primarily tutorial in nature and presents a simple approach(norm minimization under linear constraints) for deriving computable lower bounds on the MSE of deterministic parameter estimators with a clear interpretation of the bounds. We also address the issue of lower bounds tightness in comparison with the MSE of ML estimators and their ability to predict the SNR threshold region. Last, as many practical estimation problems must be regarded as joint detection-estimation problems, we remind that the estimation performance must be conditional on detection performance, leading to the open problem of the fundamental limits of the joint detectionestimation performance
MSE lower bounds for deterministic parameter estimation
This paper presents a simple approach for deriving computable lower bounds on the MSE of deterministic parameter estimators with a clear interpretation of the bounds. We also address the issue of lower bounds tightness in comparison with the MSE of ML estimators and their ability to predict the SNR threshold region. Last, as many practical estimation problems must be regarded as joint detection-estimation problems, we remind that the estimation performance must be conditional on detection performance
Performance analysis of pre-equalized multilevel partial response schemes
In order to achieve high speed on electrical interconnects, channel attenuation at high frequencies must be dealt with by proper transceiver design. In this paper we investigate finite-complexity MMSE pre-equalization under an average transmit power constraint, to compensate for channel distortion in the case of both full-response and precoded partial response signaling with L-PAM mapping, and consider the resulting error performance for symbol-by-symbol detection and sequence detection. For a representative electrical interconnect, we point out that the constellation size (2-PAM or 4-PAM), the type of signaling (full response or partial response), the detection method (symbol-by-symbol detection or sequence detection) and the number of pre-equalizer taps should be carefully selected in order to achieve satisfactory error performance at high data rates. For several scenarios, precoded duobinary 4-PAM is found to yield the best error performance for given average transmit power
Large-System Analysis of Joint Channel and Data Estimation for MIMO DS-CDMA Systems
This paper presents a large-system analysis of the performance of joint
channel estimation, multiuser detection, and per-user decoding (CE-MUDD) for
randomly-spread multiple-input multiple-output (MIMO) direct-sequence
code-division multiple-access (DS-CDMA) systems. A suboptimal receiver based on
successive decoding in conjunction with linear minimum mean-squared error
(LMMSE) channel estimation is investigated. The replica method, developed in
statistical mechanics, is used to evaluate the performance in the large-system
limit, where the number of users and the spreading factor tend to infinity
while their ratio and the number of transmit and receive antennas are kept
constant. The performance of the joint CE-MUDD based on LMMSE channel
estimation is compared to the spectral efficiencies of several receivers based
on one-shot LMMSE channel estimation, in which the decoded data symbols are not
utilized to refine the initial channel estimates. The results imply that the
use of joint CE-MUDD significantly reduces rate loss due to transmission of
pilot signals, especially for multiple-antenna systems. As a result, joint
CE-MUDD can provide significant performance gains, compared to the receivers
based on one-shot channel estimation.Comment: The paper was resubmitted to IEEE Trans. Inf. Theor
On an Achievable Rate of Large Rayleigh Block-Fading MIMO Channels with No CSI
Training-based transmission over Rayleigh block-fading multiple-input
multiple-output (MIMO) channels is investigated. As a training method a
combination of a pilot-assisted scheme and a biased signaling scheme is
considered. The achievable rates of successive decoding (SD) receivers based on
the linear minimum mean-squared error (LMMSE) channel estimation are analyzed
in the large-system limit, by using the replica method under the assumption of
replica symmetry. It is shown that negligible pilot information is best in
terms of the achievable rates of the SD receivers in the large-system limit.
The obtained analytical formulas of the achievable rates can improve the
existing lower bound on the capacity of the MIMO channel with no channel state
information (CSI), derived by Hassibi and Hochwald, for all signal-to-noise
ratios (SNRs). The comparison between the obtained bound and a high SNR
approximation of the channel capacity, derived by Zheng and Tse, implies that
the high SNR approximation is unreliable unless quite high SNR is considered.
Energy efficiency in the low SNR regime is also investigated in terms of the
power per information bit required for reliable communication. The required
minimum power is shown to be achieved at a positive rate for the SD receiver
with no CSI, whereas it is achieved in the zero-rate limit for the case of
perfect CSI available at the receiver. Moreover, numerical simulations imply
that the presented large-system analysis can provide a good approximation for
not so large systems. The results in this paper imply that SD schemes can
provide a significant performance gain in the low-to-moderate SNR regimes,
compared to conventional receivers based on one-shot channel estimation.Comment: re-submitted to IEEE Trans. Inf. Theor
Past observable dynamics of a continuously monitored qubit
Monitoring a quantum observable continuously in time produces a stochastic
measurement record that noisily tracks the observable. For a classical process
such noise may be reduced to recover an average signal by minimizing the mean
squared error between the noisy record and a smooth dynamical estimate. We show
that for a monitored qubit this usual procedure returns unusual results. While
the record seems centered on the expectation value of the observable during
causal generation, examining the collected past record reveals that it better
approximates a moving-mean Gaussian stochastic process centered at a distinct
(smoothed) observable estimate. We show that this shifted mean converges to the
real part of a generalized weak value in the time-continuous limit without
additional postselection. We verify that this smoothed estimate minimizes the
mean squared error even for individual measurement realizations. We go on to
show that if a second observable is weakly monitored concurrently, then that
second record is consistent with the smoothed estimate of the second observable
based solely on the information contained in the first observable record.
Moreover, we show that such a smoothed estimate made from incomplete
information can still outperform estimates made using full knowledge of the
causal quantum state.Comment: 11 pages, 4 figure
A virtual MIMO dual-hop architecture based on hybrid spatial modulation
International audienceIn this paper, we propose a novel Virtual Multiple-Input-Multiple-Output (VMIMO) architecture based on the concept of Spatial Modulation (SM). Using a dual-hop and Decode-and-Forward protocol, we form a distributed system, called Dual-Hop Hybrid SM (DH-HSM). DH-HSM conveys information from a Source Node (SN) to a Destination Node (DN) via multiple Relay Nodes (RNs). The spatial position of the RNs is exploited for transferring information in addition to, or even without, a conventional symbol. In order to increase the performance of our architecture, while keeping the complexity of the RNs and DN low, we employ linear precoding using Channel State Information (CSI) at the SN. In this way, we form a Receive-Spatial Modulation (R-SM) pattern from the SN to the RNs, which is able to employ a centralized coordinated or a distributed uncoordinated detection algorithm at the RNs. In addition, we focus on the SN and propose two regularized linear precoding methods that employ realistic Imperfect Channel State Information at the Transmitter. The power of each precoder is analyzed theoretically. Using the Bit Error Rate (BER) metric, we evaluate our architecture against the following benchmark systems: 1) single relay; 2) best relay selection; 3) distributed Space Time Block Coding (STBC) VMIMO scheme; and 4) the direct communication link. We show that DH-HSM is able to achieve significant Signal-to-Noise Ratio (SNR) gains, which can be as high as 10.5 dB for a very large scale system setup. In order to verify our simulation results, we provide an analytical framework for the evaluation of the Average Bit Error Probability (ABEP)
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