SNR Region Research Articles

Selection of Parity Check Equations For the Iterative Message-Passing Detection of M-Sequences

We consider the joint detection and decoding of m-sequences. The receiver has to decide whether an m-sequence is received and possibly to decode its initial state. To do so, it implements an iterative message-passing decoding algorithm that operates on a parity check matrix, built upon a number of reference parity-check equations satisfied by the m-sequence. This matrix concatenates several elementary parity check matrices which are derived from reference equations. Unlike the conventional decoding case, the detection problem imposes to consider false alarms that may occur when the decoder is only fed with noise. While absorbing sets are known to be responsible for the error floor phenomenon of iterative message-passing decoders, we show that they may have a beneficial effect on the detection performance, in that they may prevent the decoder to produce false alarms. We further compute the number of hybrid cycles of length six and eight in the Tanner graph of the decoder and use the minimization of this number as criterion to derive an algorithm for selecting the reference parity check equations. This algorithm was found to be efficient for minimizing the probability of false alarm and decreases also the probability of wrong detection in the very small SNR region. This has been achieved at the cost of a reduction of the probability of correct detection.

Minimum Sum-Mean-Square-Error Frequency-Domain Pre-Coding for Downlink Multi-User MIMO System in the Frequency-Selective Fading Channel

This paper proposes a new frequency-domain pre-coding algorithm for the downlink multi-user MIMO system in a frequency-selective fading channel, where each user is equipped with multiple antennas. The proposed algorithm is based on the minimum sum-mean-square-error (Min-SMSE) criterion, which is able to eliminate both the multi-user and multi-antenna interferences, resulting in an improved bit error rate (BER) performance. Compared with the traditional optimal Min-SMSE algorithm, the proposed algorithm can reduce the computational complexity through simplifying the iterative and power allocation processes. Furthermore, the theoretical BER and ergodic sum-rate are derived in detail. In addition, we define and analyze the complexity of the pre-coding algorithms. Simulation results show that the proposed algorithm compares favorably with the optimal Min-SMSE and traditional block diagonalization (BD) algorithms in the sense of the ergodic sum-rate due to the approximately equal power allocation. The BER performance of the proposed algorithm is close to that of the optimal one and much better than that of the BD algorithm in both the uncorrelated and correlated channels. Moreover, the computational complexity of the sub-optimal Min-SMSE algorithm is significantly less than that of its optimal counterpart, especially in the low SNR region.

Multipair Massive MIMO Relaying With Pilot-Data Transmission Overlay

We propose a pilot-data transmission overlay scheme for multipair massive multiple-input multiple-output (MIMO) relaying systems employing either half-duplex or full-duplex (FD) communications at the relay station (RS). In the proposed scheme, pilots are transmitted in partial overlap with data to decrease the channel estimation overhead. The RS can detect the source data with minimal destination pilot interference by exploiting the asymptotic orthogonality of massive MIMO channels. Then pilot-data interference can be effectively suppressed with the assistance of the detected source data in the destination channel estimation. Due to the transmission overlay, the effective data period is extended, hence improving system throughput. Both theoretical and simulation results confirm that the proposed pilot-data overlay scheme outperforms the conventional separate pilot-data design in the limited coherence interval scenario. Moreover, at asymptotically high and low SNR regions, the proposed scheme is superior regardless of the coherence interval length. Because of simultaneous transmission, the proper power allocation of source data transmission and relay data forwarding can further improve the system performance. Hence a power allocation problem is formulated and a successive convex approximation approach is proposed to solve the non-convex optimization problem with the FD pilot-data transmission overlay.

Low Complexity Capacity Maximizing Transmit Antenna Selection Schemes for Massive MIMO Wireless Communications

Recently massive MIMO systems have attracted a lot of attention. A serious limitation in implementing massive MIMO is the number of RF chains required, which is due to its high implementation cost and power consumption. Antenna selection is a wise remedy, that not only reduces the number of required RF chains, but also improves the system’s performance. In this work, two low complexity capacity-maximizing transmit antenna selection (TAS) schemes, one for low SNR region and one for medium to high SNR region, are proposed. It is shown that the proposed antenna selection schemes enhance the MIMO link’s capacity at low SNRs, and select only one antenna in more than $$90\%$$ of channel realizations, which in terms of numbers of required RF chains is very promising. The performance of the proposed schemes are compared to an existing high performance greedy TAS technique in terms of average capacity and complexity. Finally, a close analytical approximation for average capacity of the proposed capacity-based subset selection scheme is presented.

Robust speech recognition system using multi-parameter bidirectional Kalman filter

A speech signal processing system using multi-parameter model bidirectional Kalman filter has been proposed in this paper. Conventional unidirectional Kalman filter usually performs estimation of current state speech signal by processing the time varying autoregressive model of speech signals from the past time states. A bidirectional Kalman filter utilizes the past and future measurements to estimate the current state of a speech signal that minimize the mean of the squared error using efficient recursive means. The matrices involved in the difference equations and the measurement equations of the bidirectional Kalman filter algorithm are kept constant throughout the process. With multi-parameter model, the proposed bidirectional Kalman filter relates more measurements from the future and past time states to the current time state. The proposed multi-parameter bidirectional Kalman filter has been implemented into a speech recognition system and its performance has been compared to other conventional speech processing algorithms. Compared to the single-parameter model bidirectional Kalman filter, the multi-parameter bidirectional Kalman filter improves the accuracy in the state prediction, reduces the speech information lost after the filtering process and better word error rate has been achieved at high SNR regions (clean, 20, 15, 10 dB).

Partial Jamming for Secure Two-Way Relay Systems Without Wiretap Information: One > Two

This paper investigates the issue that whether the jamming in the second time slot should be utilized for secure two-way amplify-and-forward relay systems. Particularly, a more realistic and severe scenario is considered: no information related to the eavesdroppers is available and the number of eavesdroppers is not less than that of legitimate nodes. The impact of the jamming modes on the secure performance is carried out and reveals a novel insight that one-time-slot jamming outperforms two-time-slot jamming in high SNR region, i.e., one > two. A low-complexity and robust joint relay and partial jammer selection criterion is proposed, in which only jamming in the first time slot is employed and no wiretap information is required. Simulation results highlight the effectiveness of our design.

Evidence for a wide electron spectra scatter among different SNR regions from high radio-frequency observations

AbstractIn the framework of the Sardinia Radio Telescope (SRT) Early Science Program, we obtained single-dish high-resolution imaging of the Supernova Remnants IC443 and W44 at 7 GHz. By coupling them with SRT 1.5 GHz maps, we provided spatially-resolved spectral measurements that are highlighting a spread in spectral slope distribution. The observed features range from flat or slightly inverted spectra corresponding to bright radio limbs and filaments, to relatively steep spectra in fainter radio regions. Different theoretical possibilities explaining the above challenging findings are discussed. In particular, we exclude that the observed region-dependent wide spread in spectral slope distribution could be related to absorption processes. Our high-frequency results can be directly related to distinct electron populations in the SNRs including secondary hadronic electrons and resulting from different shocks conditions and/or undergoing different cooling processes. Integrated fluxes associated with the whole SNRs obtained by SRT in comparison with previous results in the literature support the evidence for a slight spectral steepening above 1 GHz for both sources, which could be related to primary electrons or more likely secondary hadronic electrons cut-offs.

High-resolution spectral imaging of SNR W44 and IC443 at 22 GHz with the Sardinia Radio Telescope

AbstractIn the framework of the Astronomical Validation and Early Science activities of the Sardinia Radio Telescope (SRT, www.srt.inaf.it), we performed 22 GHz imaging observations of SNR W44 and IC443. Thanks to the single-dish imaging performances of SRT and innovative ad hoc imaging techniques, we obtained maps that provide a detailed view of the structure of the remnants. We are planning to exploit the high-frequency radio data of SNRs to better characterize the spatially-resolved spectra and search for possible spectral steepening or breaks in selected SNR regions, assessing the high-energy tail of the region-dependent electron distribution.

Cutoff Rate of Sparse Code Multiple Access in Downlink Broadcast Channels

For the sake of supporting massive connectivity in the future 5G networks, non-orthogonal multiple access (NOMA) techniques are advocated. As a promising NOMA technique, in recent years sparse code multiple access (SCMA) has attracted substantial attention. However, there is a paucity of studies on the theoretical analysis of its error-freely achievable data rate, especially, in the downlink context. Hence, we derive the cutoff rate of SCMA in downlink broadcast channels, which indicates the lower-bound of a system’s error-freely achievable rate. However, we will demonstrate that when considering the conventional categorization of pairwise error events, the accuracy of the cutoff rate rapidly degrades in the low-SNR region owing to the fact that multi-user SCMA systems typically encounter an extremely large constellation size. Alternatively, by invoking Bergmans’ concept from 1973 in the categorization of pairwise error events, we obtain a more accurate cutoff rate both in the low- SNR regions and the high-SNR regions. Moreover, we provide insights into the cutoff rate derivation process, which reveals some general guidelines for designing a beneficial codebook, capable of improving SCMA with respect to its original low-density signature-based counterpart.

Performance Analysis for Downlink Relaying Aided Non-Orthogonal Multiple Access Networks With Imperfect CSI Over Nakagami- ${m}$ Fading

Non-orthogonal multiple access (NOMA) has been conceived as a breakthrough technology for the fifth generation (5G) wireless networks. With imperfect channel state information (ICSI) taken into account, we study an NOMA-based downlink amplify-and-forward (AF) relaying network under Nakagami- ${m}$ fading in this paper. First, we investigate the system outage behavior, and close-form expressions for the exact and tight lower bounds of the outage probability are attained, respectively. By further evaluating the outage probability at the high SNR region, it is observed that an error floor exists in the outage probability due to the presence of ICSI. Finally, numerical results are presented to demonstrate the validity of our analysis and show the advantages of NOMA over conventional orthogonal multiple access. Moreover, simulation results verify that the optimal relay location for NOMA should be close to the source node.

Angle estimation for bistatic MIMO radar with unknown mutual coupling based on three-way compressive sensing

The problem of angle estimation for bistatic multiple-input multiple-output radar in the present of unknown mutual coupling (MC) is investigated, and a three-way compressive sensing (TWCS) estimation algorithm is developed. To exploit the inherent multi-dimensional structure of received data, a trilinear tensor model is firstly formulated. Then the de-coupling operation is followed. Thereafter, the high-order singular value decomposition is applied to compress the high dimensional tensor to a much smaller one. The estimation of the compressed direction matrices are linked to the compressed trilinear model, and finally two over-complete dictionaries are constructed for angle estimation. Also, Cramer-Rao bounds for angle and MC estimation are derived. The proposed TWCS algorithm is effective from the perspective of estimation accuracy as well as the computational complexity, and it can achieve automatically paired angle estimation. Simulation results show that the proposed method has much better estimation accuracy than the existing algorithms in the low signal-to-noise ratio scenario, and its estimation performance is very close to the parallel factor analysis (PARAFAC) algorithm at the high SNR regions.

Spectrum Sensing in Cognitive Radio Using Combined Sequential Energy Detector and Cyclostationary Feature Detector

In the following research, we derive a detector which is based on sequential probability ratio test (SPRT) and it uses Energy Detector (ED) which is followed by Cyclostationary Feature Detector (CFD). ED is a blind sensing technique and it is easy to implement while conceptually simple. However, it is highly affected by interference and noise uncertainties. Therefore, CFD is applied for fine sensing as research has shown that Cyclostationary Feature Detector is more suitable than the energy detection when noise uncertainties are unknown. Our method is novel in trying to derive a sequential Energy Detector and combine it with Cyclostationary Feature Detector for low SNR region where average sample number (ASN) as a random variable may take very high value to achieve a desired performance level for sequential Energy Detector. For this sequential Energy Detector is terminated after it reaches certain cut-off sample number, making it truncated sequential Energy Detector.

Modulation Designs for Visible Light Communications With Signal-Dependent Noise

This paper proposes efficient modulation design methods for single-carrier and multicarrier visible light communication systems with signal-dependent shot noise (SDSN). Improved constellations are obtained through solving optimization problems aiming at minimizing the system symbol error rate, subject to lighting constraints. For single-carrier systems, maximum likelihood based detection, is applied. Constellation and threshold values are optimized jointly. The proposed method outperforms both the uniform signaling and the square-root signaling. It is also observed that the uniform signaling outperforms the square-root signaling through the medium-to-high signal to noise region, while the latter performs better in lower SNR region. For multicarrier systems, we formulate a new channel model with the SDSN taken into account. By maximizing the minimum Euclidean distance between the symbols, improved constellations are designed under different lighting constraints. Furthermore, the multicarrier part of design embraces the DC-informative design framework, and thus achieve high power efficiency. The performance gain of our DC-informative optical OFDM (DCIO-OFDM) over OFDM-QPSK ranges from 5 to 30dB even in moderate dimensional signal space.

An Improved Energy Detection Scheme based on Channel Estimation

Energy detection is most commonly employed technique for spectrum sensing in cognitive radio networks due to its low computational and implementation complexities. However, the performance of energy detector deteriorate considerably under severe fading environment especially in low SNR region. The performance metrics used for energy detector are probability of detection, probability of false alarm and number of samples requirements. The detection threshold plays a significant role in PU signal detection and thus must be chosen appropriately to meet tradeoff between probability of detection and probability of false alarm under severe fading. In this paper, we have proposed adaptive threshold detection scheme for severe fading environment to work under low SNR. The simulated results are presented to validate the proposed scheme and it has been shown that proposed scheme is more robust against noise uncertainty under severe fading environment and performs better than conventional energy detection scheme to yield same detection performance.

Achievable Rate and Energy Efficiency of Hybrid and Digital Beamforming Receivers with Low Resolution ADC

For 5G it will be important to leverage the available millimeter wave spectrum. To achieve an approximately omni- directional coverage with a similar effective antenna aperture compared to state of the art cellular systems, an antenna array is required at both the mobile and basestation. Due to the large bandwidth and inefficient amplifiers available in CMOS for mmWave, the analog front-end of the receiver with a large number of antennas becomes especially power hungry. Two main solutions exist to reduce the power consumption: Hybrid BeamForming (HBF) and Digital BeamForming (DBF) with low resolution ADC. Hybrid beamforming can also be combined with low resolution ADCs. This paper compares the spectral and energy efficiency based on the chosen RF-frontend configuration. A channel with multipath propagation is used. In contrast to previous publication, we take the spatial correlation of the quantization noise into account. We show that the low resolution ADC are robust to small Automatic Gain Control (AGC) imperfections. We showed that in the low SNR regime the performance of DBF even with 1-2 bit resolution outperforms HBF. If we consider the relationship of spectral and energy efficiency then DBF with 3-5 bits resolution achieves the best ratio of spectral efficiency per power consumption of the RF receiver frontend over a very wide SNR region. The power consumption model is based on components reported in literature.

Power Optimization of Three Dimensional Turbo Code Using a Novel Modified Symbiotic Organism Search (MSOS) Algorithm

In modern communication system error-control coding scheme is used to elevate the immunity of noisy communication channel. Turbo code (TC) is considered as one of the significant channel coding schemes which approaches to the Shannon limit. An upgraded version of TC named as 3 dimensional turbo code (3D-TC) has been emerged as a challenging research area in recent past. Meanwhile, considerable improvement in bit error rate (BER) performance of the TC has been achieved by incorporating suitable optimization algorithms. Motivated by above research trends, a modified symbiotic organisms search (MSOS) algorithm has been proposed by changing the organism structure and selection criteria of a newly developed symbiotic organisms search (SOS) algorithm. Subsequently the proposed MSOS has been used to design an improved 3D-TC. Here an optimal power allocation scheme of a new class of 3 dimensional turbo encoder has been investigated to improve its BER characteristics mainly in high SNR regions. Furthermore, the BER performance of the proposed 3D-TC code has been compared with conventional 2D serially concatenated and parallel concatenated turbo code as well as conventional 3D-TC. Finally, the BER performance of the proposed MSOS optimized 3D-TC has been compared with the SOS optimized 3D-TC and harmony search optimized 3D-TC.

Log-average-SNR ratio and cooperative spectrum sensing

In this paper, we analyze the spectrum-sensing performance of a cooperative cognitive radio (CR) network consisting of a number of CR nodes and a fusion center (FC). We introduce the log-average-SNR ratio that relates the average SNR of the CRnode- FC link and that of the primary-user-CR-node link. Assuming that the FC utilizes theK-out-of-N rule as its decision rule, we derive exact expressions for the sensing gain and the coding gain - parameters used to characterize the CR network performance at the high SNR region. Based on these results, we determine ways to optimize the performance of the CR network.

Performance of Symbol-Level Combining and Bit-Level Combining in MIMO Multiple ARQ Systems

The performance of symbol-level combining (SLC) and bit-level combining (BLC) in multiple-input multiple-output (MIMO) multiple automatic repeat request (ARQ) systems is investigated. Considering the zero-forcing (ZF) detection under the assumption of perfect packet elimination for SLC, the two performance characteristics of Chase combining (CC) with SLC and BLC in MIMO multiple ARQ (MMARQ) systems are analyzed. First, the performance of a packet with the highest hybrid ARQ (HARQ) round in CC-SLC-ZF is not affected by the HARQ rounds of the other packets simultaneously sent. Second, the performance gain of CC-SLC-ZF over CC-BLC-ZF for a packet can be improved when the packets with higher HARQ rounds are simultaneously sent. The latter indicates that CC-SLC can provide an improved error performance for the packets transmitted only once when there is at least one retransmitted packet simultaneously sent. Therefore, even though incremental redundancy (IR) provides a significantly larger coding gain than CC, CC-SLC can provide a better throughput than IR-BLC as the average block error rate of a retransmitted packet approaches zero. Simulation results verify that the analyses remain valid regardless of the detection scheme and the throughput of CC-SLC at the high SNR region can be better than IR-BLC in MMARQ systems.

MIMO Cognitive Radio Spectrum Sharing Using Spatial Coding and User Scheduling for Fading Channels

Spectrum scarcity is one of the issue in wireless communication. Dynamic spectrum sharing is the solution for this problem in which the underutilized spectrums are utilized efficiently. Multiple Input Multiple Output (MIMO) based cognitive radio using spatial coding is used to dynamically share the spectrum which allows simultaneous usage of spectrum by more than one user. The drawback of spatial coding is the achievable capacity get reduced with the increased number of cognitive users which limits the number of users to share the spectrum. In order to maximize the number of secondary users sharing the spectrum of the primary user, this paper presents a cluster based multiple primary and secondary user’s MIMO spatial coding which provides higher capacity. The entire network is divided into number of cluster based on the location such that each cluster will be interference free from other. Each cluster is designed with one primary user and many secondary users and a User Scheduling algorithm called Cluster Based Max Signal Power User Scheduling (CBMSPUS) is proposed to select two best secondary users in each cluster. Since the performance of spatial coder depends on the channel matrix, this paper analyze the spatial pre-coder under Rayleigh, Rican and Nakagami fading channels with multiple users and evaluate the capacity of users under CBMSPUS scheduling algorithm. The results show that the Nakagami fading channel achieves high capacity than others. Primary user calculated capacity is 10.8bits/HZ /channel at low SNR region and 14.2 bits/HZ/channel at high SNR region. The secondary user archives maximum capacity of 9.8bits/HZ /channel at low SNR and 13 bits/HZ/channel at high SNR. The Proposed Scheduling method offers maximum of 15dB gain comparing FIFO scheduling algorithm.

Phase unwrapping with graph cuts optimization and dual decomposition acceleration for 3D high-resolution MRI data.

Existence of low SNR regions and rapid-phase variations pose challenges to spatial phase unwrapping algorithms. Global optimization-based phase unwrapping methods are widely used, but are significantly slower than greedy methods. In this paper, dual decomposition acceleration is introduced to speed up a three-dimensional graph cut-based phase unwrapping algorithm. The phase unwrapping problem is formulated as a global discrete energy minimization problem, whereas the technique of dual decomposition is used to increase the computational efficiency by splitting the full problem into overlapping subproblems and enforcing the congruence of overlapping variables. Using three dimensional (3D) multiecho gradient echo images from an agarose phantom and five brain hemorrhage patients, we compared this proposed method with an unaccelerated graph cut-based method. Experimental results show up to 18-fold acceleration in computation time. Dual decomposition significantly improves the computational efficiency of 3D graph cut-based phase unwrapping algorithms. Magn Reson Med 77:1353-1358, 2017. © 2016 International Society for Magnetic Resonance in Medicine.