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

Optimizing Pilot Spacing in MU-MIMO Systems Operating Over Aging Channels

In the uplink of multiuser multiple input multiple output (MU-MIMO) systems operating over aging channels, pilot spacing is crucial for acquiring channel state information and achieving high signal-to-interference-plus-noise ratio (SINR). Somewhat surprisingly, very few works examine the impact of pilot spacing on the correlation structure of subsequent channel estimates and the resulting quality of channel state information considering channel aging. In this paper, we consider a fast-fading environment characterized by its exponentially decaying autocorrelation function, and model pilot spacing as a sampling problem to capture the inherent trade-off between the quality of channel state information and the number of symbols available for information carrying data symbols. We first establish a quasi-closed form for the achievable deterministic equivalent SINR when the channel estimation algorithm utilizes multiple pilot signals. Next, we establish upper bounds on the achievable SINR and spectral efficiency, as a function of pilot spacing, which helps to find the optimum pilot spacing within a limited search space. Our key insight is that to maximize the achievable SINR and the spectral efficiency of MU-MIMO systems, proper pilot spacing must be applied to control the impact of the aging channel and to tune the trade-off between pilot and data symbols.

Designing FDA Radars Robust to Contaminated Shared Spectra

This paper considers the problem of jointly designing the transmit waveforms and weights for a frequency diverse array (FDA) in a spectrally congested environment in which unintentional spectral interferences exist. Exploiting the properties of the interference signal induced by the processing of the multi-channel mixing and low-pass filtering FDA receiver, the interference covariance matrix structure is derived. With this, the receive weights are formed using the minimum variance distortionless response (MVDR) method for interference cancellation. Owing to the fact that the resulting output signal-to-interference-plus-noise ratio (SINR) is a function of the transmit waveforms and weights, as well as due to the ever-greater competition for the finite available spectrum, a joint design scheme for the FDA transmit weights and the spectrally compatible waveforms is proposed to efficiently use the available spectrum while maintaining a sufficient receive SINR. The performance of the proposed technique is verified using numerical simulations in terms of the achievable SINR, spectral compatiblity, as well as several aspects of the synthesized waveforms.

MIMO Multifunction RF Systems: Detection Performance and Waveform Design

This paper studies the detection performance of a multiple-input-multiple-output (MIMO) multifunction radio frequency (MFRF) system, which simultaneously supports radar, communication, and jamming. We show that the detection performance of the MIMO MFRF system improves as the transmit signal-to-interference-plus-noise-ratio (SINR) increases. To analyze the achievable SINR of the system, we formulate an SINR maximization problem under the communication and jamming functionality constraint as well as a transmit energy constraint. We derive a closed-form solution of this optimization problem for energy-constrained waveforms and present a detailed analysis of the achievable SINR. Moreover, we analyze the SINR for systems transmitting constant-modulus waveforms, which are often used in practice. We propose an efficient constant-modulus waveform design algorithm to maximize the SINR. Numerical results demonstrate the capability of a MIMO array to provide multiple functions, and also show the tradeoff between radar detection and the communication/jamming functionality.

Pilot contamination mitigation under smart pilot allocation strategies within massive MIMO-5G system

Within massive multiple-input-multiple-output (Massive MIMO) system, pilot contamination (PC) is deemed as a stumbling block in boosting the spectral efficiency (SE) regarding fifth-generation (5G) wireless communication network. To alleviate efficacy of PC, efficient sectorization-based pilot allocation (ES-PA) scheme is recommended, here users equipment (UE) are divided corresponding to their signal-to-interference-plus-noise-ratio (SINR) within two zones, i.e., cell center zone and edge zone. Smart antenna technique is used to split up edge zone further into N uniform sectors. The UE present in the cell center zone are allotted with identical pilot sequences on account of lower inter-cell-interference (ICI), whereas UE present in each sector of edge zone is allotted with mutually orthogonal pilot sequences to diminished PC. The simulation results illustrates that this recommended approach substantially attenuate strength of PC, avail lower mean squared error (MSE), greater data rate and superior SE as compared to conventional pilot allocation methods. In another effective proposed scheme II for mitigating PC, all active users are initially classified between high interference UH and low interference UL users premised on their large scale-fading. An efficient pilot allocation approach in accordance with edge weighted interference graph (EWIG) is recommended to clarify low interference users UL. Simulation output reveals that recommended scheme II upgrade both uplink achievable rate (R) and SINR. Additionally, the recommended approach is considerably competent of mitigating PC and maximizing system performance.

Min-SINR Maximization for mmWave Massive MISO-NOMA System With Randomly Directional Beamforming

Based on the high-direction characteristic of millimeter wave (mmWave) transmission, randomly directional beamforming (RDB) can be used for the mmWave massive multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) system to reduce the number of radio frequency (RF) chains. However, the impact of RDB on the signal-to-interference-plus-noise ratio (SINR) of each user is related to the corresponding beamforming gain and interference from other users. Thus, in this paper, we investigate the max-min SINR among all users to evaluate user fairness. In particular, we focus on the single-cell downlink mmWave MISO-NOMA system with RDB, where single-antenna users are divided into multiple NOMA clusters according to their azimuth angles. We formulate the minimum achievable SINR maximization problem associated with power allocation and propose the sum of power allocation coefficients based iterative algorithm (SPACIA) to find the max-min SINR. We also prove that the max-min SINR monotonically decreases as the number of paired users in an NOMA cluster increases as well as the number of beams in the cell with large-scale base station (BS) antenna array increases. Moreover, we derive the upper bound of the max-min SINR. Simulation results verify our theoretical analyses and demonstrate that the proposed algorithm guarantees user fairness, thus outperforming existing schemes.

Analysis and Design of Optimum Sparse Array Configurations for Adaptive Beamforming

In this paper, we analyze the effect of nonuniform array configurations on adaptive beamforming for enhanced signal-to-interference-plus-noise ratio (SINR). The array is configured using a given number of antennas or through a selection of subset of antennas from a larger available set, leading to a sparse array in both cases. The bounds on the highest achievable SINR for a given number of antennas are formulated and used to offer new insights into open-loop adaptive beamforming. The upper and lower bounds underscore the role of array configurations in optimizing performance for interference-free and interference-active environments, respectively. This paper considers the general case of multiple sources and interferences in the field of view. We formulate three angles, namely eigenspace angle, conventional angle, and minimum canonical angle for characterizing spatial separation between the source and interference subspaces, which represent performance loss incurred by interference nulling. Three sparse array design methods, incorporating these angles, are proposed. Simulation examples confirm the role of subspace angles in optimum beamforming and validate the utility of antenna selection algorithms for sparse array design.

Location-based achievable signal-to-interference-plus-noise ratio in visible light communication network with different topology parameters

In visible light communication (VLC) networks, light-emitting diodes (LEDs) as transmitters are densely deployed so that the interference between cells is serious. A variety of methods about interference management have been proposed to improve the signal-to-interference-plus-noise ratio (SINR). However, the achievable SINR has not been studied yet. We obtain the achievable signal-to-interference ratio and improve the SINR with the derived results. A simple analytic solution is provided to show the achievable SINR of two cells under a linear model. Furthermore, we discuss the effect of different parameters of the SINR distribution under the linear model.

Energy Harvesting for Internet of Things with Heterogeneous Users

We study the energy harvesting problem in the Internet of Things with heterogeneous users, where there are three types of single-antenna users: ID users that only receive information, EH users that can only receive energy, and ID/EH users that receive information and energy simultaneously from a multiantenna base station via power splitting. We aim to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of the ID users and ID/EH users by jointly designing the power allocation at the transmitter and the power splitting strategy at the ID/EH receivers under the maximum transmit power and the minimum energy harvesting constraints. Specifically, we first apply the semidefinite relaxation (SDR), zero-forcing (ZF), and maximum ratio transmission (MRT) techniques to solve the nonconvex problems. We then apply the zero-forcing dirty paper coding (ZF-DPC) technique to eliminate the multiuser interference and derive the closed-form optimal solution. Numerical results show that ZF-DPC provides higher achievable minimum SINR than SDR and ZF in most cases.

Filter‐and‐forward relaying in cognitive networks with blind channel estimation

The authors study the design of cooperative beamforming for an underlay cognitive relay network over frequency selective fading channels. The network under consideration consists of one primary link, one secondary link and relay nodes that assist the communication. It is assumed imperfect blind channel estimation, i.e. only the second order statistics – with uncertainty – of the channel gain between the primary transmitter-relay and relay-primary receiver, is available. To mitigate the channel's frequency selectivity, each relay is equipped with a finite impulse response filter, which performs filter and forward relaying. The authors consider two different scenarios: in the first, the objective is to minimise the total transmit power of the relays subject to a constraint on the interference induce on the primary receiver. Furthermore, a constraint is also considered on the received signal-to-interference plus noise ratio (SINR) in the secondary receiver. In the second scenario, the objective is to maximise SINR in the secondary receiver, subject to constraints on the sum power of the relays and also on the noise and interference power in the primary receiver. Simulation results show how total power of relay varies with the uncertainty in the blind channel estimation in the first scenario. In addition, the achievable SINR deteriorates in the second scenario when the uncertainty increases.

SINR maximization in colocated MIMO radars using transmit covariance matrix

The main waveform design features in multiple-input multiple-output (MIMO) radars include (a) signal transmission with full rank covariance matrix in order to use the maximum waveform diversity and to suppress more number of interferers, (b) constant envelope in order to have simplicity in deployment and to reduce the destructive effect of nonlinear amplifiers and (c) small side lobe level (SLL) in order to reduce the effect of interferers with unknown location. Therefore, in order to maximize the signal-to-interference-plus-noise ratio (SINR) and to exploit the advantages of MIMO radars, in this paper we have proposed two full rank transmit covariance matrices and maximum achievable SINR is calculated analytically for both. We have shown that the two proposed covariance matrices can be used to generate BPSK waveforms which satisfy constant modulus constraint. Simulation results show that when the angle location of interferences is known, the first proposed matrix achieves a higher level of SINR compared to the second one, while the second proposed matrix has a lower SLL compared with the first one. Also we have shown that the two proposed covariance matrices can handle more interferences compared to phased-array and the recently proposed methods in MIMO radars.

A Per-User QoS Enhancement Strategy via Downlink Cooperative Transmission Using Distributed Antennas

In this letter, we address a strategy to enhance the signal-to-interference plus noise ratio (SINR) of the worst-case user by using cooperative transmission from a set of geographically separated antennas. Unlike previously reported schemes which are based on either the power control of individual antennas or cooperative orthogonal transmission, the presented strategy utilizes the minimum-mean-squared error (MMSE) filter structure for beamforming, which provides increased robustness to the external interference as well as the background noise at the receiver. By iteratively updating the cooperative transmission beamforming vector and power control (PC), the balanced SINR is obtained for all users, while the transmission power from each antenna also converges to within the constrained value. It is demonstrated that proposed MMSE beamforming significantly outperforms other existing schemes in terms of the achievable minimum SINR.

Robust Constrained-Optimization-Based Linear Receiver for High-Rate MIMO-OFDM Against Channel Estimation Errors

We consider multi-input multi-output-orthogonal frequency division multiplexing (MIMO-OFDM) transmission in a scenario that the adopted cyclic-prefix (CP) length is shorter than the channel delay spread for boosting data rate and, moreover, the channel parameters are not exactly known but are estimated using the least-squares (LS) training technique. By exploiting the receiver spatial resource, we propose a constrained-optimization-based linear equalizer which can mitigate inter-symbol interference and inter-carrier interference incurred by insufficient CP interval, and is robust against the net detrimental effects caused by channel estimation errors. The optimization problem is formulated in an equivalent unconstrained generalized-sidelobe-canceller (GSC) setup. The channel parameter error is explicitly incorporated into the constraint-free GSC system model through the perturbation technique; this allows us to exploit the presumed LS channel error property for deriving a closed-form solution, and can also facilitate an associated analytic performance analysis. A closed-form approximate signal-to-interference-plus-noise ratio (SINR) expression for the proposed robust scheme is given, and an appealing formula of the achievable SINR improvement over the nonrobust counterpart is further specified. Our analytic results bring out several intrinsic features of the proposed solution. Simulation study confirms the effectiveness of the proposed method and corroborates the predicted SINR results