Signal-to-interference-plus-noise Ratio Improvement Research Articles

Transmit–Receive Design for Airborne Radar With Nonuniform Pulse Repetition Intervals

This article aims to the joint design of transmit waveform and receive filter to enhance the clutter suppression capability for airborne radar with nonuniform pulse repetition interval (NUPRI). Specifically, a multipulse echo model with NUPRI incorporating a moving point-like target and signal-dependent clutter is first established. Then the 2-D range-Doppler plane is acquired by performing pulse compression and the windowed pulse Doppler processing on the echo. Further, the signal to interference plus noise ratio (SINR) of the interested area in the range-Doppler plane is formulated as a figure of merit to maximize along with constant modulus constraint on the waveform. To solve the resultant nonconvex problem, the sequential greedy optimization algorithm through alternately updating the transmit waveform and receive filter is proposed. Each iteration of the developed algorithm invokes coordinate descent framework and a Lagrangian-based algorithm to obtain the transmit waveform and receive filter, respectively. The analytical guarantee of the monotonic SINR improvement is proved. Finally, the performance of the proposed algorithm is assessed through numerical simulations showing its capability to suppress signal-dependent clutter.

Asynchronous and Non-Stationary Interference Cancellation in Multiuser Interference Channels

A single antenna interference cancellation (SAIC) scheme is proposed. The scheme is motivated by the challenging asynchronous and non-stationary interference cancellation problem in wireless communications. Suppose the existence of the single-user region (SUR) of the desired signal, we propose to first recognize the SUR via a novel detection scheme. The SUR detection scheme proposed consists of the pseudo-observation matrix construction and the information theoretic criterion-based source number estimation. A basis set for the desired signal is then learnt over the SUR, via dictionary learning techniques. In the final signal recovery stage, a novel constrained sparse coding (CSC) process is proposed. The CSC reforms the conventional sparse coding (SC) via incorporating signal-specific constraints. Unlike existing SAIC algorithms, the proposed scheme is completely independent of a prior knowledge on the interferences. Numerical results are provided to demonstrate the effectiveness of the above proposed schemes under varied interference intensities and environmental noise levels. The proposed scheme outperformed competing SAIC schemes by about 5dB signal-to-interference-plus-noise ratio (SINR) improvement. The proposed CSC scheme outperformed the conventional SC by about 9dB SINR improvement, besides the superior recovery fidelity of signal property.

Interference Minimization in 5G Physical-Layer Network Slicing

The interference resulting from densification of access points and the coexistence of different numerologies within the same spectrum severely hinders inter-slice isolation. We propose a slice allocation policy that enforces inter-slice isolation by minimizing the inter-slice interference suffered by each virtual operator. In detail, we design a binary quadratic non-convex optimization problem that minimizes i) the inter-slice interference generated by interfering base stations and ii) the inter-slice interference generated by the multiplexing of spectrum slices having different numerologies. We also provide a heuristic algorithm to render the solution scalable in practical scenarios. We assess the performance of both approaches by evaluating the signal-to-interference-plus-noise ratio (SINR) associated to each slice through simulations. Results reveal that the heuristic algorithm provides a solution comparable with the optimal one on different minimization scenarios. Moreover, a considerable SINR improvement is observed with respect to a base-line scheme that does not account for inter-slice interference.

Optimal Linear Detection of Signals in Cyclostationary, Linearly Modulated, Digital Communications Interference

Both economic incentives and policy trends motivate the study of spectrum sharing between radar and wireless communications as a means to mitigate spectrum scarcity. This paper proposes a novel, temporal signal processing algorithm for a radar to mitigate interference from cyclostationary, linearly modulated digital communications (LMDC) interference such as orthogonal frequency division multiplexing (OFDM) or code division multiple access (CDMA). The proposed algorithm has the form of a novel whitening filter followed by a matched filter, and as such it optimizes the statistical deflection among the class of all linear detection filters. The derived cyclostationary whitening filter has equivalent mathematical representations as: 1) the form of a multiuser detector followed by an interference canceler, and 2) a frequency-shift (FRESH) filter. Performance results indicate that the derived cyclostationary whitener can produce signalto-interference-plus-noise ratio (SINR) improvements ranging from negligible to up to 20 dB for the parameters used in this study. The cyclostationary whitener leads to the greatest SINR improvements when the interference-plus-noise is dominated by only a few LMDC signals, such as might occur in a near-far scenario.

New Weight Function for Adapting Handover Margin Level over Contiguous Carrier Aggregation Deployment Scenarios in LTE-Advanced System

In this paper, an Adaptive Handover Margin algorithm based on Novel Weight Function (AHOM-NWF) is proposed through Carrier Aggregation operation in Long Term Evolution—Advanced system. The AHOM-NWF algorithm automatically adjusts the Handover Margin level based on three functions, $$f(SINR), \; f(TL)\; {\text{and}}\; f(v)$$ , which are evaluated as functions of Signal-to-Interference-plus-Noise-Ratio (SINR), Traffic Load $$(TL)$$ , and User’s velocity $$(v)$$ respectively. The weight of each function is taken into account in order to estimate an accurate margin level. Furthermore, a mathematical model for estimating the weight of each function is formulated by a simple model. However, AHOM-NWF algorithm will contribute for the perspective of SINR improvement, cell edge spectral efficiency enhancement and outage probability reduction. Simulation results have shown that the AHOM-NWF algorithm enhances system performance more than the other considered algorithms from the literature by 24.4, 14.6 and 17.9%, as average gains over all the considered algorithms in terms of SINR, cell edge spectral efficiency and outage probability reduction respectively.

Time-Invariant Joint Transmit and Receive Beampattern Optimization for Polarization-Subarray Based Frequency Diverse Array Radar

We propose a polarization-subarray based frequency diverse array (FDA) radar with the subarray-based FDA as the transmit (Tx) array and the polarization-sensitive subarray-based FDA (PSFDA) as the receive (Rx) array. The subarray-based FDA has the capability to achieve a single maximum beampattern at the target location, while the PSFDA can provide an extra degree of freedom to further suppress the interference and, thus, to improve the radar's signal-to-interference-plus-noise ratio (SINR). The time-dependent frequency offsets are designed for the proposed radar to realize the time-invariant beampattern at the desired target location over the whole pulse duration. To further improve the target detection performance, the time-invariant joint Tx–Rx beampattern design is considered based on the output SINR maximization. To effectively solve the nonconvex output SINR maximization problem, a suboptimal alternating optimization algorithm is proposed to iteratively optimize the FDA Tx beamforming, the PSFDA spatial pointings, and the PSFDA Rx beamforming. Numerical experiments illustrate that the time-invariant and single-maximum joint Tx–Rx beampattern at the target location is achieved. Moreover, compared to the basic FDA and logarithmic frequency offset FDA as well as conventional phased array radars, the proposed polarization-subarray based FDA radar achieves a significant SINR improvement, particularly when the desired target and the interferences are spatially indistinguishable.

A Normalized Complex LMS Based Blind I/Q Imbalance Compensator for GFDM Receivers and Its Full Second-Order Performance Analysis

Generalized frequency division multiplexing (GFDM) has become one of the most important waveform candidates for air interface in 5G communications. However, like the standard orthogonal frequency division multiplexing (OFDM), its direct-conversion receivers are vulnerable to radio frequency impairments, due to their cost and size constraints. In this paper, the performance deterioration resulting from inphase/quadrature (I/Q) imbalance is first analyzed in terms of signal-to-interference plus noise ratio (SINR) for typical GFDM receivers. Next, a blind adaptive I/Q imbalance compensator based on normalized complex least mean square (NCLMS), originally designed for OFDM receivers, is extended for GFDM ones. In order to provide more physical insight into its compensation capability, a full second-order performance assessment is established, via a joint consideration of the weight error variance and its complementary variance of the proposed compensator in both the transient and steady-state stages. Apart from an accurate evaluation on its overall self-image attenuation performance, the proposed full second-order analysis is also able to quantify the individual contributions from both the I and Q channels of the compensator, an important finding missing in the literature and not possible to discover by using the standard variance analysis only. This analysis also facilitates theoretical quantifications of SINR improvements by NCLMS for GFDM receivers. Simulations on GFDM waveforms support the analysis.

Interference Mitigation for Indoor Optical Attocell Networks Using an Angle Diversity Receiver

In this paper, interference mitigation techniques based on angle diversity receivers (ADRs) are studied for optical attocell networks. Consisting of multiple photodiodes (PDs), an ADR requires appropriate signal combining schemes in order to mitigate intercell interference (ICI) in optical attocell networks. Four signal combining schemes, namely select best combining, equal gain combining, maximum ratio combining, and optimum combining are investigated. To further mitigate ICI, a novel double-source cell configuration with two transmission modes is also proposed. Results show that the systems with ADRs significantly outperform those with single-PD receivers in terms of signal-to-interference-plus-noise ratio (SINR). Also, compared to the conventional single-source cell configuration, the double-source cell configuration can provide an SINR improvement of over $\text{20}$ dB. Furthermore, an analytical framework is proposed to analyze the performance of optical attocell networks with ADRs, where different propagation scenarios such as line-of-sight and nonline-of-sight are considered. The accuracy of the proposed analytical model is validated by Monte Carlo simulations.

Filters that mitigate waveform modulation of radar clutter

Moving target indication (MTI) radars will require modified signal processing to be able to employ pulse-to-pulse agile waveforms. The main problem with conventional processing is that matched-filter pulse compression leads to range-sidelobe modulation (RSM) of clutter. Due to the fact that range sidelobes differ on each pulse, clutter energy that leaks into these sidelobes cannot be cancelled by subsequent processing. This study derives a figure-of-merit for pulse-compression filters that quantifies the signal-to-interference-plus-noise ratio (SINR) loss that results from RSM. Optimising this figure-of-merit results in sets of filters that mitigate RSM by producing matched sidelobes. The proposed filters are compared to low-sidelobe mismatch filters designed separately for each pulse. Simulation results indicate that an MTI radar could achieve a 5–10 dB improvement in SINR by using the proposed filters instead of low-sidelobe filters.

A New Iterative Approach in SINR Improvement of MIMO Radars by Using Combination of Orthogonal Waveforms

In this paper we consider joint waveform and filter design in multi-input multi-output (MIMO) radars in the presence of signal dependent interference to improve signal-to-interference-plus-noise ratio (SINR) of received signals. We have proposed two new iterative methods for this in which instead of direct design of waveforms, the coefficients of orthogonal waveform combinations are designed. In the first method, coefficients of combinations are calculated by solving a convex optimization problem. By extending the first method, we have proposed a method for multi-target case in presence of signal dependent interference. However, the computational complexity of the first method is high and therefore we have proposed the second method, which is more suitable for real time applications. In the second method, in each step, waveform combination coefficients and received filter coefficients are designed in closed form. Simulation results show that the proposed methods can achieve higher SINR in comparison to other methods which are used in MIMO and phased array radars.

A Geometric Approach to Covariance Matrix Estimation and its Applications to Radar Problems

A new class of disturbance covariance matrix estimators for radar signal processing applications is introduced following a geometric paradigm. Each estimator is associated with a given unitary invariant norm and performs the sample covariance matrix projection into a specific set of structured covariance matrices. Regardless of the considered norm, an efficient solution technique to handle the resulting constrained optimization problem is developed. Specifically, it is shown that the new family of distribution-free estimators shares a shrinkagetype form; besides, the eigenvalues estimate just requires the solution of a one-dimensional convex problem whose objective function depends on the considered unitary norm. For the two most common norm instances, i.e., Frobenius and spectral, very efficient algorithms are developed to solve the aforementioned one-dimensional optimization leading to almost closed form covariance estimates. At the analysis stage, the performance of the new estimators is assessed in terms of achievable Signal to Interference plus Noise Ratio (SINR) both for a spatial and a Doppler processing assuming different data statistical characterizations. The results show that interesting SINR improvements with respect to some counterparts available in the open literature can be achieved especially in training starved regimes.

Space-Time Transmit Code and Receive Filter Design for Colocated MIMO Radar

This paper deals with the design of multiple-input multiple-output radar space-time transmit code (STTC) and space-time receive filter (STRF) to enhance moving targets detection in the presence of signal-dependent interferences. An iterative procedure, whose convergence is analytically proved, is devised to maximize the Signal to interference plus noise ratio (SINR) accounting for both a similarity constraint and a constant modulus requirement on the probing waveform. Each iteration of the algorithm involves the solution of hidden convex problems. Specifically, both a convex problem (whose solution is provided in closed form) and a set of fractional programming problems, that can be globally solved in polynomial time via the Dinkelback's procedure, are settled. The computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. In particular, the proposed technique provides a monotonic SINR improvement without limitations on the size of the similarity constraint and ensures convergence to a stationary point filling these important gaps in the open literature. Besides, the reported results highlight that the new devised procedure outperforms both in the optimized SINR value and the computational complexity than the available counterparts.

Efficient Offline Waveform Design Using Quincunx/Hexagonal Time-Frequency Lattices

Conventional orthogonal frequency division multiplexing (OFDM) may turn to be inappropriate for future wireless cellular systems services, because of extreme natural and artificial impairments they are expected to generate. Natural impairments result from higher Doppler and delay spreads, while artificial impairments result from multisource transmissions and synchronization relaxation for closed-loop signaling overhead reduction. These severe impairments induce a dramatic loss in orthogonality between subcarriers and OFDM symbols and lead to a strong increase in intercarrier interference (ICI) and intersymbol interference (ISI). To fight against these impairments, we propose here an optimization of the transmit/receive waveforms for filter-bank multicarrier (FBMC) systems, with hexagonal time-frequency (TF) lattices, operating over severe doubly dispersive channels. For this, we exploit the Ping-pong Optimized Pulse Shaping (POPS) paradigm, recently applied to rectangular TF lattices, to design waveforms maximizing the signal-to-interference-plus-noise ratio (SINR) for hexagonal TF lattices. We show that FBMC, with hexagonal lattices, offers a strong improvement in SINR with respect to conventional OFDM and an improvement of around 1 dB with respect to POPS-FBMC, with rectangular lattices. Furthermore, we show that hexagonal POPS-FBMC brings more robustness to frequency synchronization errors and offers a 10 dB reduction in out-of-band (OOB) emissions, with respect to rectangular POPS-FBMC.

Clutter Mitigation using Space-TimeAdaptive Processing (STAP) Algorithms in Passive Radars

Objectives: In the current work, we propose a Space-Time Adaptive Processing (STAP) technique for bistatic passive radar by fully adaptive STAP to provide effective clutter mitigation by using only few set of data samples. Methods/ Statistical Analysis: Several methods exist but they are computationally complex or require the knowledge of the radar parameters. Moreover our modified Adaptive STAP technique aims two fold one is to improve the Signal to Interferenceplus- Noise Ratio (SINR), especially at short ranges and other greatly reduces the rank of the covariance matrix to further improve performance and reduce processing requirements. Findings: In this paper, propose a methodology to precisely approximate the Clutter Covariance Matrix (CCM) and implement STAP based on only few number of secondary data samples. We also simulated relationship for clutter suppression such that ,SINR for the optimum and tapered fully adaptive STAP, as well as Doppler straddling losses are deliberated clearly. We observed that in Optimum STAP, with its indirect uniform taper, fallouts in space-time filters with Doppler responses to be narrow, so there is increase in additional straddling losses, as compared to fully adaptive tapered. Correspondingly a distinct weight vector was calculated for every potential target Doppler, which penalties on optimum SINR curve to be smooth upper bound over the enactment feasible with other suboptimum STAP algorithm. Finally with less input interference-to-noise ratio, the optimum SINR achieves an SINR improvement of 76.01dB over the center of the Doppler space. Application/Improvements: As the STAP eliminates the clutter, hence non-cooperative transmitter meritoriously makes the target detection simple in severe environments like air-ground.

Successive QCQP Refinement for MIMO Radar Waveform Design Under Practical Constraints

The authors address the problem of designing a waveform for multiple-input multiple-output (MIMO) radar under the important practical constraints of constant modulus and waveform similarity. Incorporating these constraints in an analytically tractable manner is a longstanding open challenge. This is due to the fact that the optimization problem that results from signal-to-interference-plus-noise ratio (SINR) maximization subject to these constraints is a hard non-convex problem. The authors develop a new analytical approach that involves solving a sequence of convex quadratically constrained quadratic programing (QCQP) problems, which they prove converges to a sub-optimal solution. Because an improvement in SINR results via solving each problem in the sequence, they call the method Successive QCQP Refinement (SQR). Furthermore, the proposed SQR method can be easily extended to incorporate emerging requirements of spectral coexistence, as shown briefly in this paper. The authors evaluate SQR against other candidate techniques with respect to SINR performance, beam pattern, and pulse compression properties in a variety of scenarios. Results show that SQR outperforms state-of-the-art methods that also employ constant modulus and/or similarity constraints while being computationally less burdensome.

A Novel Algorithm for Improving the SINR of D2D Communication in the Cellular Network

In this paper, we investigate the interference scenario where multiple Device-to-Device (D2D) pairs reuse the spectrum resources allocated to one cellular user, and propose a novel algorithm for improving the signal-to-interference-plus-noise ratio (SINR) of D2D communication. We call this D2D SINR improvement algorithm as DSIA, and design it from the perspective of precoding and decoding. With the DSIA, each D2D pair involved in the network can obtain the corresponding precoding and decoding vectors which make the SINR of its receiver being maximized. In order to clearly describe the design procedure of the proposed algorithm, we first formulate an optimization problem with multiple variables to maximize the SINR of each D2D receiver, then simplify the objective function through mathematical derivation and seek out the relationship between the optimized variables which can transform the optimization problem to one of solving nonlinear equations, and finally propose the DSIA to work out the nonlinear equations. Numerical results show that the DSIA will enable D2D to achieve significant performance gains in terms of SINR and bit-error rate (BER) compared with the traditional spectrum orthogonal scheme.

On the Benefits of MAI-Plus-Noise Whitening in TH-BPSK IR-UWB Systems

Multiaccess interference (MAI)-plus-noise whitening for detecting impulse radio ultra-wide bandwidth (IR-UWB) signals transmitted over ideal free-space and the IEEE 802.15.3a channels is considered. IR-UWB signals are very sparse in time and, thus, MAI-plus-noise whitening cannot introduce intersymbol interference (ISI) in IR-UWB systems operating on an ideal free-space channel. In addition, ISI in UWB multipath fading channels can be eliminated by a proper choice of the frame duration. An analytical expression for the signal-to-interference-plus-noise ratio (SINR) of IR-UWB systems after MAI-plus-noise whitening is derived and the SINR improvement due to whitening is investigated. It is shown that whitening can improve the performance of a variety of the well-known IR-UWB receivers, viz., soft-limiting, P-order metric, optimal, and the conventional matched filter receivers. It is also observed that MAI-plus-noise whitening can improve the overall SINR of the system and, thus, decrease the complexity of Rake receivers through reducing the number of their processing branches.

Auxiliary beam terrain‐scattered interference suppression: reflection system and radar performance

Terrain-scattered interference (TSI), that is, jammer signals reflected on the earth's surface, is a significant problem to military airborne radar. In auxiliary beam TSI suppression, the TSI in the main radar beam is estimated by a single or several auxiliary beams and is subtracted from the main beam channel. The signal to subtract is the auxiliary beam signals fed through an estimate of the ‘reflection system’, which describes scattering on the surface. The authors first present results on the structure of this TSI suppression, on the estimation of the reflection system and on the quality of the estimate. Then the authors derive theoretical expressions for the signal-to-interference plus noise ratio (SINR) and the remaining TSI power for a single auxiliary beam. Since the SINR is directly connected to the radar performance, it can be seen what factors affect the performance and how. It was noted that when the estimated reflection system is missing one or more delays of the true system, the TSI filter cannot suppress the TSI signal completely. This phenomenon, which is called ‘TSI leakage’, has a very large impact on the performance. The SINR cannot be kept constant. Instead, an ‘SINR improvement’ can be defined.

Maximum Likelihood Estimation of a Structured Covariance Matrix With a Condition Number Constraint

In this paper, we deal with the problem of estimating the disturbance covariance matrix for radar signal processing applications, when a limited number of training data is present. We determine the maximum likelihood (ML) estimator of the covariance matrix starting from a set of secondary data, assuming a special covariance structure (i.e., the sum of a positive semi-definite matrix plus a term proportional to the identity), and a condition number upper-bound constraint. We show that the formulated constrained optimization problem falls within the class of MAXDET problems and develop an efficient procedure for its solution in closed form. Remarkably, the computational complexity of the algorithm is of the same order as the eigenvalue decomposition of the sample covariance matrix. At the analysis stage, we assess the performance of the proposed algorithm in terms of achievable signal-to-interference-plus-noise ratio (SINR) both for a spatial and a Doppler processing. The results show that interesting SINR improvements, with respect to some existing covariance matrix estimation techniques, can be achieved.

Efficient design of radar waveforms for optimised detection in coloured noise

The authors present a computationally efficient method for designing practical radar transmit waveforms that maximize the signal-to-interference-plus-noise ratio (SINR) in a known additive coloured Gaussian noise environment. The problem reduces to a non-linear constrained optimisation in which the authors seek the SINR-maximising transmit waveform that has a specified envelope and an acceptable autocorrelation sequence (ACS). The waveform ACS can be constrained either directly or indirectly. The direct approach involves forcing the ACS magnitude below a specified level at each lag. This provides the greatest control over the waveform ACS, but it is too computationally demanding for many realistic problem sizes. Indirect methods of ACS constraint can be computationally less demanding, but they afford only inexact control over the waveform ACS. The leading indirect approach, which relies on the so-called similarity constraint, requires significantly fewer calculations than the direct approach, but it provides significantly less SINR improvement. The indirect approach presented here relies on a parametrisation of the phase perturbations of a linear frequency modulated waveform. This approach requires fewer calculations than the direct approach, and can provide more SINR improvement than the similarity constraint approach. As such, this new approach may be preferable when computation time is limited.