Noise-limited Environment Research Articles

Active sonar detection with acoustic spiral waves: experiment and modeling

Active spiral-wave active localization is a technique for determining location of acoustic targets [after Dzikowicz et al., JASA 146, 4821–4830 (2019)], which relies on measuring the phase difference between a reference and spiral wavefronts. This research presents a monostatic model of spiral detection and tracking for multiple targets in sparse noise limited environments. Simulation and experimental results from an acoustic spiral wave beacon in a small underwater test tank will be presented. Results show good agreement to resolve targets in horizontal and vertical dimensions with a compact aperture. [Work supported by ONR 321MS.]

Deep reinforcement learning for cognitive active-sonar employment

We introduce a framework to leverage deep reinforcement learning (RL) for active sonar employment, wherein we train an RL agent to select waveform parameters, which maximize the probability of single-target detection. We first simulate raw sonar returns of targets and clutter in reverberation and noise using a physics-based sonar-simulation model, the Sonar Simulation Toolkit (SST), then process the resulting signatures into network inputs via an in-house signal and information processing model of an archetypal antisubmarine warfare (ASW) processing chain. We demonstrate that the trained RL agent is able to appropriately select between continuous wave (CW) and hyperbolic frequency modulated (HFM) waveforms depending on target trajectory, as well as select an optimal bandwidth and pulse length trade-off (when constrained by a constant time-bandwidth product), when presented with sonar returns from a reverb-limited or noise-limited environment.

Robust Control for the Detection Threshold of CFAR Process in Cluttered Environments.

The constant false alarm rate (CFAR) process is essential for target detection in radar systems. Although the detection performance of the CFAR process is normally guaranteed in noise-limited environments, it may be dramatically degraded in clutter-limited environments since the probabilistic characteristics for clutter are unknown. Therefore, sophisticated CFAR processes that suppress the effect of clutter can be used in actual applications. However, these methods have the fundamental limitation of detection performance because there is no feedback structure in terms of the probability of false alarm for determining the detection threshold. This paper presents a robust control scheme for adjusting the detection threshold of the CFAR process while estimating the clutter measurement density (CMD) that uses only the measurement sets over a finite time interval in order to adapt to time-varying cluttered environments, and the probability of target existence with finite measurement sets required for estimating CMD is derived. The improved performance of the proposed method was verified by simulation experiments for heterogeneous situations.

Mobility-Driven Association Policies for Dense Wireless Networks

The primary approach to increase coverage and capacity in infrastructure-based wireless networks is densification. Densification, however, presents a major challenge when serving mobile users, which is the overhead associated with the increased rate of base station handovers. Assuming a prior knowledge of a mobile’s trajectory and base stations’ locations, we formulate the problem of determining the sequence of handovers that optimize the trade-off between the mobile user’s perceived throughput and handover overheads in noise-limited environments. Under appropriate conditions, we show that the problem reduces to determining a maximum weight path in a directed acyclic graph induced by the mobile user’s trajectory. In practice, knowledge of a mobiles’ trajectory may be limited and one may also want to limit the handover complexity, whence we propose a new class of mobility-driven greedy association policies. The greedy policies are based on defining a handover support set, which constrains both the possible handovers and the complexity/information requirements. In a setting where base station locations follow a Poisson point process, we show that the performance of such handover processes follows a continuous-time Markov process which can be analyzed using complex variable techniques. This enables one to explore the optimization size/shape of the handover support set for mobility-driven greedy handover strategies and their relative performance compared to traditional association policies.

Filtering DC Bias in a Hard-Limited Radar Signal Processor Using Code Imbalance

A radar signal processor subchain containing a pulse compression module employing binary $\pm 1$ phase codes is studied in an effort to understand the behavior of the output mean and variance as functions of phase code imbalance, in noise-limited environments. It is a relatively simple subchain consisting of an R/Theta limiter, a pulse compressor using a length- $N$ phase code for match filtering, scaling by $1/N$ , and a squarer (also known as $I^2+Q^2$ ). The input to this system is a sampled input string assumed to be formed of a small dc bias with added two-dimensional Gaussian noise. The output of this system is studied for a range of values of the pulse compression code imbalance. Imbalance is the difference between the number of 1 and $-1$ elements in the binary phase code. A nonzero imbalance is sometimes a cause for concern, since the pulse compression dc gain is proportional to the code imbalance. Hence, the dc gain might be expected to yield a nonzero component at the output, resulting in an increased risk of false alarms on a radar return comprised of noise alone. However, we show that for imbalance of $\pm \sqrt{N}$ , any contribution from the dc bias is nearly eliminated. When $N$ is a perfect square, dc bias is completely eliminated, in theory at least. Analytical formulae are provided, along with simulation results for pulse compression code length $N=512$ .

Multistage Algorithm for Single-Channel Extended-Dwell Signal Integration

For small radar platforms, the increase in signal-to-interference-plus-noise ratio (SINR) needed to support effective operation must come through integration of target signal energy collected over a long dwell time. Conventional radar processing assumes a linear-phase signal model and utilizes Fourier-based methods to coherently integrate signal energy. Over an extended dwell, the target signal generally includes multiple nonlinear-phase components which limit the effectiveness of conventional methods. An algorithm is presented that estimates the linear- and nonlinear-phase components of the extended-dwell-time target signal in a multistage process. The combined phase components form the signal model used in a filter that achieves near optimal matching performance for extended dwell times over a wide range of target parameters. Results are presented for both noise-limited and clutter-limited environments. For the specific conditions discussed, typical increase in output SINR for a 500 ms dwell time is 12 dB over the conventional coherent processing methods.

An Analytical Model for LoS Probability and Area Transport Efficiency of Millimeter Wave Cellular Network

Millimeter wave based small cell deployment is a promising technique for the evolution of fifth generation (5G) cellular network. This paper investigates coverage probability of millimeter wave cellular network (MWCN) over Nakagami-m fading channel. Stochastic geometry based ITU-R statistical model is used for modeling the blockages in MWCN which accounts line of sight (LoS) propagation characteristics of urban environment. SNR distribution is also considered under nearest-neighbor and furthest-neighbor based receiver association schemes for better representation of coverage probability in noise limited environment. Furthermore, new performance metric, namely, area transport efficiency (ATE) is proposed to capture the impact of the different network parameters on the system performance. Numerical results are evaluated to compare the performance of the MWCN under nearest-neighbor and furthest-neighbor based receiver association schemes. It is seen that height of transmitter plays an important role in the performance of the MWCN. It is also observed that furthest-neighbor scheme outperforms nearest-neighbor scheme for low SNR threshold and higher BS heights. Whereas for high SNR threshold performance of nearest-neighbor scheme is better as compared to furthest-neighbor scheme.

Clustering for determining distributed antenna locations in wireless networks

In this paper we extend the concept of the well-known input–output clustering (IOC) technique in Uykan et al. (IEEE Trans Neural Netw 11(4):851–858, 2000) to antenna location optimization problem in wireless networks and propose an input–output space clustering criterion (IOCC) to optimize the locations of the remote antenna units (RAUs) of generalized distributed antenna systems (DASs) under sum power constraint. In IOCC, the input space refers to RAU location space and output space refers to location specific ergodic capacity space for noise-limited environments. Given a location-specific arbitrary desired ergodic capacity function over a geographical area, we define the error as the difference between actual and desired ergodic capacity. Following the major steps of the well-known IOC technique in Uykan et al. (IEEE Trans Neural Netw 11(4):851–858, 2000) and Uykan (IEEE Trans Neural Netw 14(3):708–715, 2003) we show that for the DAS wireless networks: (1) the IOCC provides an upper bound to the cell averaged ergodic capacity error; and (2) the derived upper bound is equal to a weighted quantization error function in location-capacity space (input–output space) and (3) the upper bound can be made arbitrarily small by a clustering process increasing the number of RAUs for a feasible DAS. IOCC converts the RAU location problem into a codebook design problem in vector quantization in input–output space, and thus includes the Squared Distance Criterion (SDC) for DAS in Wang et al. (IEEE Commun Lett 13:315–317, 2009) (and other related papers) as a special case, which takes only the input space into account. Computer simulations confirm the theoretical findings and show that the IOCC outperforms the SDC for DAS in terms of the defined cell averaged “effective” ergodic capacity.

Power Splitting-Based SWIPT With Decode-and-Forward Full-Duplex Relaying

This paper investigates simultaneous wireless information and power transfer (SWIPT) for a decode-and-forward (DF) full-duplex relay (FDR) network. A battery group consisting of two batteries is applied to utilize the relay-harvested energy for FDR transmission. The virtual harvest-use model and the harvest-use-store model are considered, respectively. By switching between two batteries for charging and discharging with the aid of power splitting (PS), concurrent source and relay transmissions can overcome spectral efficiency loss compared with half-duplex relay (HDR)-assisted PS-SWIPT. The outage probability for the virtual harvest-use model is presented in an exact integral form and the optimal PS (OPS) ratio that maximizes the end-to-end signal-to-interference-plus-noise ratio (e-SINR) is characterized in closed form via the cubic formula. The fundamental tradeoff between the e-SINR and recycled self-power is quantified. The OPS ratios and the corresponding outage probabilities in noise-limited and interference-limited environments are also derived. In the harvest-use-store model, a greedy switching (GS) policy is implemented with energy accumulation across transmission blocks. The OPS ratio of the GS policy is presented and the corresponding outage probability is derived by modeling the relay’s energy levels as a Markov chain with a two-stage state transition. Numerical results verify the performance improvement of the proposed scheme over HDR-assisted PS-SWIPT in terms of outage probability and average throughput.

Successive convex approximation for rate maximisation in cooperative multiple‐input–multiple‐output‐orthogonal frequency‐division multiplexing systems

In this study, the authors propose a continuous rate and power allocation algorithm for multiuser downlink multiple-input–multiple-output orthogonal frequency-division multiplexing systems with coordinated multi-point transmission. The optimisation problem is formulated as a weighted sum-rate maximisation problem subject to per-antenna power constraints across multiple cooperating base stations (BSs). The practical consideration of the per-antenna power constraint limits the average transmit antenna power which indirectly controls the inherent issue of high peak powers in OFDM. The proposed algorithm employs a successive convex approximation (SCA) technique to dynamically allocate powers to multiple co-channel user terminals. They provide a convexity proof of the transformed optimisation problem and they show that the proposed algorithm converges to a unique solution. They compare the proposed SCA algorithm with two alternative approaches: (i) iterative waterfilling (IWF) and (ii) zero-forcing beamforming (ZFB) with semi-orthogonal user selection under both per-antenna and per-BS power constraint scenarios. Their simulation results highlight that the proposed SCA algorithm outperforms the existing IWF and ZFB in noise-limited environments under both power constraint scenarios.

On Power Allocation Schemes for Bi-directional Communication in a Spectrum Sharing-based Cognitive Radio System

This paper presents the results of an investigation into bi-directional communication in spectrum sharing-based cognitive radio (Bi-CR) systems. A Bi-CR system can increase the spectral efficiency significantly by sharing the spectrum and through the bi-directional use of spatial resources for two-way communication. On the other hand, the primary user experiences more interference from the secondary users in a Bi-CR system. Satisfying the interference constraint by simply reducing the transmission power results in performance degradation for secondary users. In addition, secondary users also experience self-interference from echo channels due to full duplexing. These imperfections may weaken the potential benefits of the Bi-CR system. Therefore, a new way to overcome these defects in the Bi-CR system is needed.BR To address this need, this paper proposes some novel power allocation schemes for the Bi-CR system. This contribution is based on two major analytic environments, i.e., noise-limited and interference-limited environments, for providing useful analysis. This paper first proposes an optimal power allocation (OPA) scheme in a noise-limited environment and then analyzes the achievable sum rates. This OPA scheme has an effect in the noise-limited environment. In addition, a power allocation scheme for the Bi-CR system in an interference-limited environment was also investigated. The numerical results showed that the proposed schemes can achieve the full duplexing gain available from the bi-directional use of spatial resources.

Optimal Power Allocation and Outage Analysis for Cognitive MIMO Full Duplex Relay Network Based on Orthogonal Space-Time Block Codes

This paper investigates the power allocation and outage performance of MIMO full-duplex relaying (MFDR), based on orthogonal space-time block codes (OSTBC), in cognitive radio systems. OSTBC transmission is used as a simple means to achieve multi-antenna diversity gain. Cognitive MFDR systems not only have the advantage of increasing spectral efficiency through spectrum sharing, but they can also extend coverage through the use of relays. In cognitive MFDR systems, the primary user experiences interference from the secondary source and relay simultaneously, owing to full duplexing. It is therefore necessary to optimize the transmission powers at the secondary source and relay. In this paper, we propose an optimal power allocation (OPA) scheme based on minimizing the outage probability in cognitive MFDR systems. We also analyse the outage probability of the secondary user in noise-limited and interference-limited environments in Nakagami-m fading channels. Simulation results show that the proposed schemes achieve performance improvements in terms of reducing outage probability.

Optimal Power Allocation and Outage Analysis for Cognitive MIMO Full Duplex Relay Network Based on Orthogonal Space-Time Block Codes

This paper investigates power allocation and outage performance for the MIMO full duplex relaying (MFDR) based on orthogonal space-time block Codes (OSTBC) in cognitive radio systems. OSTBC transmission is used as a simple way to obtain multi-antenna diversity gain. Cognitive MFDR systems offer the advantage not only of increasing spectral efficiency by spectrum sharing but also of extending the coverage through the use of relays. In cognitive MFDR systems, the primary user experiences interference from the secondary source and relay simultaneously due to the full duplexing. What is therefore needed is a way to optimize the transmission powers at the secondary source and relay. Therefore, we propose an optimal power allocation (OPA) scheme based on minimizing the outage probability in cognitive MFDR systems. We then analyze the outage probability of the secondary user in the noise-limited and interference-limited environments under Nakagami-m fading channels. Simulation results show that the proposed schemes achieve performance improvement in terms of outage probability.

Cognitive Radio-Enabled Network-Based Cooperation: From a Connectivity Perspective

Cognitive radio (CR) enables dynamic spectrum access to provide universal connectivity across different types of radio access technologies, realizing seamless content delivery in the next generation wireless networking. As the most general cognitive radio network scenario, multiple ad hoc and infrastructure networks sharing the same spectrum are allowed to cooperate with each other by using other networks' nodes as relays to carry and forward traffic, forming an interconnected heterogeneous network. Previous research is limited to the connectivity analysis of hybrid wireless networks with path loss channel model. In this paper, we analyze the connectivity of the interconnected heterogeneous network consisting of multiple ad hoc networks and multiple infrastructure networks from a percolation-based perspective, considering both noise-limited and interference-limited environment with general fading channel model. The benefit of network-based cooperation is quantified in terms of the percolation threshold, facilitating proper network control and deployment. For example, using such quantification, we can specify the amount of infrastructure deployment or reliable connections to control the connectivity of existing ad hoc networks, and vice versa. Finally, we apply the analysis to the coexistence of primary and secondary networks, as the common CR scenario.

Optimal Power Allocation and Outage Analysis for Cognitive Full Duplex Relay Systems

This paper investigates the use of full duplex relaying (FDR) in cognitive radio systems. Cognitive full duplex relay networks (CogFRNs) offer the advantage not only of increasing spectral efficiency by spectrum sharing but also of extending coverage through the use of relays. Concurrent transmissions at the source and relay in CogFRNs can overcome a loss of resource efficiency in a way that conventional half duplex relay (HDR) systems cannot. However, in CogFRNs, the primary user experiences interference from the secondary source and relay simultaneously due to the effects of full duplexing. Satisfying the interference constraint by simply reducing transmission power results in performance degradation for the secondary user. What is therefore needed is a way to optimize the transmission powers at the secondary source and relay. To address this need, we propose an optimal power allocation scheme based on minimizing the outage probability in CogFRNs. We then analyze the outage probability of the secondary user in the noise-limited and interference-limited environments. In addition, we also propose an outage-constrained power allocation scheme which does not require the instantaneous channel state information (CSI) for the link between the primary and secondary users. Simulation results show that the proposed schemes achieve performance improvement in terms of outage probability.

Performance of Adaptive MS-GSC in the Presence of Cochannel Interference

Minimum-selection generalized selection combining (MS-GSC) has been proposed as a power-saving variant of conventional generalized selection combining (GSC). Existing performance results of this scheme are limited to interference-free environments under multipath fading. This paper addresses the scenario when the received desired signal on each diversity branch is corrupted by multiple interfering signals and background noise, wherein desired and undesired signals undergo mutually independent Rayleigh fading. In the absence of perfect tracking of the instantaneous interference power on diversity branches, the adaptation thresholds that are set on the combined signal-to-noise ratio (SNR) to enhance either the spectral efficiency or power efficiency in noise-limited environments may not guarantee the target performance. This paper aims to study the effect of cochannel interference on the performance of bandwidth- and power-efficient SNR-based MS-GSC. Through the analysis, new analytical results for some important performance measures of adaptive MS-GSC schemes are presented. Numerical comparisons to clarify the impact of cochannel interference on the achieved performance of the adaptation schemes under consideration are provided.

An Intercell Interference Cancellation Method for Eigen-Beamforming Transmission

Eigen-beamforming (EB) transmission for multiple-input multiple-output (MIMO) systems is an effective means to maximize the receiver signal-to-noise ratio (SNR) in a noise-limited environment, but suffers a performance degradation when strong interference signals exist. In this letter, we propose an interference cancellation method for EB signals by constructing a new receive beamforming vector which jointly utilizes the EB matrix and minimum mean-square error (MMSE) spatial demultiplexing. The proposed method is shown to outperform the conventional EB receiver in the entire cell range, with a significant increase in the effective signal-to-interference plus noise ratio (SINR) near the cell boundary.

Radar target resolution probability in a noise-limited environment

This paper investigates the probability of a radar being able to resolve two point-targets in an environment in which additive noise is the primary limitation on resolution. The statistical properties of the radar cross-ambiguity function are developed and used to arrive at an expression for the target resolution probability. The analysis is verified through simulations.

Modeling the detection range of fish by echolocating bottlenose dolphins and harbor porpoises

The target strength as a function of aspect angle were measured for four species of fish using dolphin-like and porpoise-like echolocation signals. The polar diagram of target strength values measured from an energy flux density perspective showed considerably less fluctuation with azimuth than would a pure tone pulse. Using detection range data obtained from dolphin and porpoise echolocation experiments, the detection ranges for the Atlantic cod by echolocating dolphins and porpoises were calculated for three aspect angles of the cod. Maximum detection ranges occurred when the fish was broadside to the odontocete and minimum detection ranges occurred when the cod was in the tail aspect. Maximum and minimum detection ranges for the bottlenose dolphin in a noise-limited environment was calculated to be 93 and 70 m, respectively. In a quiet environment, maximum and minimum detection ranges for the bottlenose dolphin were calculated to be 173 and 107 m, respectively. The detection ranges for the harbor porpoise in a quiet environment were calculated to be between 15 and 27 m. The primary reason for the large differences in detection ranges between both species was attributed to the 36 dB higher source level of the bottlenose dolphin echolocation signals.

Interference robustness aspects of space-time block code-based transmit diversity

Transmit diversity, which was initially developed for noise-limited environments, has been promoted as a viable candidate for improving the link quality in both existing and future systems for wireless communication. However, to ensure efficient spectrum utilization, receivers operating within wireless multiuser networks must be robust not only to fading and noise but to interference from other system users as well. This work considers interference robustness aspects when transmit diversity, in the form of space-time block coding, is used in multiuser systems. Properties of the space-time block encoded signals such as code rate, block structure, diversity order, etc., and their implications on detection and interference rejection by means of noise whitening are discussed. To handle the presence of space-time block encoded interference, a space-time processing-based extension of an interference rejection combining algorithm is proposed. Results are presented indicating that transmit diversity based on space-time block codes (STBCs) of the linear dispersion type improve robustness against interference in terms of an increased diversity advantage. This can be achieved either by increasing the number of transmit antennas or by reducing the rate of the code. It is also shown, by analysis and by simulation examples, that the performance improvements obtained by using transmit diversity in multiuser systems may rapidly subside as the signal-to-interference ratio decreases. However, by using the proposed interference rejection scheme tailored to the space-time encoded structure, performance improvements of transmit diversity are also obtained in a multiuser environment.