Analysis and Elimination of Self‐Induced Effect in SINR Estimation

The Signal‐to‐Interference‐plus‐Noise Ratio (SINR) is an important metric of wireless communication link quality. SINR estimates have several important applications. These include optimizing the transmit power level for a target quality of service, assisting with handoff decisions and dynamically adapting the data rate for wireless Internet applications. Accurate SINR estimation provides for both a more efficient system and a higher user‐perceived quality of service. In this paper, we develop new SINR estimators and compare their mean squared error (MSE) performance. We show that our new estimators dominate estimators that have previously appeared in the literature with respect to MSE. The sequence of transmitted bits in wireless communication systems consists of both pilot bits (which are known both to the transmitter and receiver) and user bits (which are known only by the transmitter). The SINR estimators we consider alternatively depend exclusively on pilot bits, exclusively on user bits, or simultaneously use both pilot and user bits. In addition, we consider estimators that utilize smoothing and feedback mechanisms. Smoothed estimators are motivated by the fact that the interference component of the SINR changes relatively slowly with time, typically with the addition or departure of a user to the system. Feedback estimators are motivated by the fact that receivers typically decode bits correctly with a very high probability, and therefore user bits can be thought of as quasipilot bits. For each estimator discussed, we derive an exact or approximate formula for its MSE. Satterthwaite approximations, noncentral F distributions (singly and doubly) and distribution theory of quadratic forms are the key statistical tools used in developing the MSE formulas. In the case of approximate MSE formulas, we validate their accuracy using simulation techniques. The approximate MSE formulas, of interest in their own right for comparing the quality of the estimators, are also used for optimally combining estimators. In particular, we derive optimal weights for linearly combining an estimator based on pilot bits with an estimator based on user bits. The optimal weights depend on the MSE of the two estimators being combined, and thus the accurate approximate MSE formulas can conveniently be used. The optimal weights also depend on the unknown SINR, and therefore need to be estimated in order to construct a useable combined estimator. The impact on the MSE of the combined estimator due to estimating the weights is examined. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004

A performance analysis of VDSL2 technologies in FttC or FttC/FttDp hybrid scenarios requires knowledge of the access network geometry, propagation, and crosstalk interference models. A simulation-based approach is commonly adopted for performance assessment. In this paper, we introduce a performance evaluation framework based on the log-normal approximation for the probabilistic description of the signal-to-interference plus noise ratio (SINR), which is then used to obtain the statistics of the achievable bit rate per user. A very good agreement has been observed between the exact and the approximated calculations of the bit rate up to 600 m from the Cabinet. In addition, the log-normal approximation has allowed to define a simple procedure, based on the equivalent number of co-located interferers , to evaluate the bit rate per user for generic access network geometry. Furthermore, two approximated formulas for bit rate have been obtained under high SINR and dominant far-end crosstalk (FEXT) conditions. They evidence the logarithmic decrease of the bit rate with the distance from the Cabinet and provide the accurate results for distances up to 400 m. Finally, when FEXT fluctuations are modeled in accordance with Beta distribution, we have observed the log-normal approximation still provides valid probabilistic description of the SINR.

The second part of the study of beamforming issues, based on positioning in ultra-dense millimeter wave radio access networks, is devoted to the formalization and software implementation of a complex simulation model of the functioning of a set of directional radio links. Each directional radio link between a base station (gNodeB – gNB), equipped with an antenna array, and a user equipment (UE), operating in omnidirectional mode, is formed according to the location of the UE, known at the gNB. The set of gNB→UE directional radio links, simultaneously operating in a common frequency range, is studied as a set of traffic beams, that implement space division multiple access (SDMA). Spatial multiplexing is implemented through three-dimensional beamforming at the gNB and makes it possible to compensate for propagation losses and high levels of interference. In the first part of the study, it was shown that the problem of practical implementation of SDMA in ultra-dense radio access networks is a significant (tens of dB) spread in the signal to interference plus noise ratio (SINR), depending on the arrangement of two devices. The purpose of this study is to establish the dependence of SINR on 1) the beamwidth of the gNB sector in the direction of the user equipment in the radio link of the signal of interest (SOI); 2) uncertainty of the UE location; 3) interference from radio links of signal not of interest (SNOI): a) within its sector, b) other sectors of its cell and c) other cells in the network. The simulation model developed and implemented in software in this work for the first time made it possible to establish the interdependence of the UE positioning error factors and the required width of the traffic beam for its service. In particular, it was found, that as the positioning error decreases from 10 to 1 m, the required beam width in the horizontal and vertical planes narrows to 3 °, which makes it possible to increase the SINR to 25 dB. A simultaneous transmission multiplexing study showed that for 64 spatially multiplexed UEs, as the cell size increases from 20 to 300 m, the SINR increases by approximately 30 dB, subject to a beamwidth constraint of 3°. Unlike similar studies, in this model, the contribution from interference from simultaneously operating traffic beams within its sector, other sectors of its cell and other cells in the network is shown separately for the first time, which allows to differentiate the origin of interference and use scientifically based beamwidth control for their compensation.

Waveform optimization with SINR criteria for FDA radar in the presence of signal-dependent mainlobe interference

Waveform Optimization with Sinr Criteria for Fda Radar in the Presence of Signal-Dependent Mainlobe Interference

In this paper, we use joint perfect power control (PPC) and adaptive beamforming algorithms as constrained least mean square (CLMS) and conjugate gradient adaptive beamforming (CGBF) in a 2D urban environment. The CLMS algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. In addition, with the CGBF algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference (IPI) is canceled in other paths in each RAKE finger. The adaptability of the algorithms is closely observed for uniformly spaced linear array. In addition, in this paper, we present switched-beam (SB) technique. In the SB technique by using a number of fixed, independent, or directional antennas we increase the uplink capacity of the wireless systems. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless communication systems. Simulation results indicate that the SB technique is able to considerably increase the signal to interference plus noise ratio (SINR) of desired user in comparison with other algorithms. In addition, we observe that the SINR in the CLMS algorithm is lower than the CGBF algorithm. Finally, we discuss two parameters of the PCE and path-loss exponent and their effects on capacity of the system via some computer. Keywords: Adaptive beamforming, Power control, Wireless networks

Due to the development of the Internet of Things (IoT) and maritime wireless networks, the wireless networking of vessels will be the future trend. Furthermore, long-range (LoRa) technology is widely used in the marine field with the benefits of long range, lower power consumption, security, scalability, and robustness. In this study, LoRa is used as the solution for internal wireless networks of vessels as well as considering external and internal wireless communication, aiming to reduce construction and maintenance costs. The received signal strength (RSS) and signal to interference plus noise ratio (SINR) were measured and analyzed. The findings demonstrated that the mean value of the RSS and the SINR in the cockpit are above −81.70 dBm and 4.45 dB respectively, which indicates that there is a good communication link between the deck and the cockpit. Furthermore, the RSS value acquired by the nodes located on the same side of the gateway is stronger than that of the other nodes. Additionally, the RSS value acquired by the nodes close to the windows is found to be as high as 6–9 dB over that of the node located in the middle of the cockpit.

A heterogeneous network (HetNet) that consists of various wireless networks is being massively studied. Integration of the networks should be error free to achieve seamless communication. The seamless vertical handoff (VHO) remains a challenging problem in HetNet studies. Several criteria for VHO decision have been studied in the literature, such as Received Signal Strength (RSS) and Signal to Interference plus Noise Ratio (SINR). It has been shown that SINR based VHO has superior performance compare to RSS based VHO. However, there are some limitations in SINR based VHO scheme. This study aims to overcome those limitations by considering user velocity as an additional criterion for SINR based VHO decision. User velocity is represented in the value of additional SINR threshold. The basic principle of the proposed algorithm is that slow speed user should stay longer in WLAN cells and high speed user should stay longer in WCDMA cells. Simulation results show that there is a trade-off between average throughput and the number of unnecessary handoffs per call. In this study, optimum threshold is obtained when the high percentage of unnecessary handoffs reduction is reached with an acceptable value of average throughput for multimedia data transfer.

Recently, the use of LTE in the unlicensed spectrum has gained a lot of attention to address bandwidth crunch. Due to restriction on the transmission power in the unlicensed spectrum, LTE-U/LAA cells will get deployed mostly inside residential and office buildings to provide high data rates for indoor User Equipments (UEs). The UEs with high Signal-to-Interference plus Noise Ratio (SINR) experience good throughput, but the SINR decreases significantly due to walls and other obstacles that are present in the communication path. The coverage difference of licensed and unlicensed spectrum leads to different SINRs so, efficient placement of LAA Base Stations (BSs) inside the buildings is very crucial for attaining desirable SINR for the indoor UEs. Our primary objective is to find the optimal number of LAA/LTE-U BSs with minimum SINR requirements in the unlicensed band, and the secondary objective is to maximize the minimum SINR inside the building in the licensed band with power control. To do this, we formulate an optimization model (MinLF) to find the minimum number of LAA/LTE-U BSs along with their positions in indoor scenarios which resulted in Mixed Integer Linear Programming (MILP) problem. Further, to maximize the minimum SINR in the licensed spectrum, we formulate MinLPower model to find the optimal transmission power of each LTE-U/LAA cell inside the building which resulted in Mixed Integer Non-Linear Programming (MINLP) problem. Our proposed models achieve optimal placement with a maximum energy saving of 88% compared to the maximum power scheme.

Transmission of the multimedia video streaming has been an important topic in wireless communications. As a metric of video quality at the application layer, peak signal-to-noise ratio (PSNR) is affected by the capacity at the physical layer which can be improved by power controlling and precoding. This paper investigates an optimal power allocation scheme which can maximize the sum PSNR of all users in an SLNR-precoding-based multiuser multiple input single output (MISO) system. The power allocation problem can be transformed into a convex optimization problem when the system works in the high signal to interference plus noise ratio (SINR) region. Performance of the proposed power allocation scheme is evaluated through computer simulation. Results show that, when the system works in the high SINR region, performance improvement in terms of sum PSNR through power allocation is neglectable while the effects of different precoding schemes on the sum PSNR performance are obvious.

In dense deployment area of femtocell networks, interference becomes major problem normally decreasing signal to interference plus noise ratio (SINR) of connection between Femto User Equipment (FUE) and Femto Base Station (FBS). Thus, FUE must select appropriate FBS to get high SINR value in order for achieving high data rates. In this paper, we investigate cell selection process in Femtocell networks and problem related to interference. We propose cell selection method using bacterial foraging optimization algorithm (BFOA) to find the most appropriate FBS and resource blocks (RBs) for FUE. Simulation results show that proposed method has capability to converge in finding the best solution, i.e. FBS and RBs that will provide high link capacity for FUE.

This article investigates using DBF onboard AIS satellites with the objective to increase the signal-to-interference-plus-noise ratio (SINR) so that the number of decoded AIS messages can be increased. A DBF system is based on an array of antenna elements acting as independent receivers that capture radio frequency (RF) signals. These signals are converted into two digital streams of baseband I and Q signals, and then they are weighted (by changing their amplitude and phase) so that when they are combined together (summed) they create a desired output (i.e., the AIS signal of interest with a high level of SINR). The article presents an antenna array with a single-element radiation pattern optimized to mitigate interference. Based on this antenna array, static and adaptive DBF techniques have been compared in terms of SINR increase and system complexity (i.e., need for a large antenna, computational complexity of an adaptive DBF technique, etc.).

In a conventional cellular network, a terminal receives signals not only from the base station of that cell, but also from other cell base stations. This inter-cell interference has more impact on the cell-edge users, in multi cell environment. The inter-cell interference degrades the performance of wireless systems. Using Base Station Cooperation, the ability of a mobile station to receive signals from multiple base stations can be utilized as an opportunity to improve the spectral efficiency and to get higher data rates for cell edge users. In multi cell environment using base station cooperation overall interference can be minimized marginally, whereas the interference within the cooperation region is largely reduced. This leads to a question whether it is worth doing cooperation all the time. However increase in terms of throughput may not always be enough to increase the throughput of each of the user .Hence for such a scenario the distinct cooperation scheme is used. The distinct cooperation is a joint transmission scheme in which the selection criterion is based on user’s signal to interference plus noise ratio (SINR) is proposed and the capacity achieved through cooperation is shared equally among the cell-edge users. Here we will analyze the normal operation, full cooperation and distinct cooperation scheme in the downlink environment for cell edge users in cellular network and we will compare and see which method improves the user capacity and data rate.KeywordsCooperative transmissionfull cooperationDistinct cooperationsignal to interference plus noise ratio (SINR)

The coexistence problem occurs when a wireless body area network (WBAN) is close to other WBANs. The degraded communication performance may even threaten people’s life for medical applications. Therefore, a reliable method for coexistence state prediction is required to ensure this problem could be detected and handled in time. This chapter presents a machine learning based method for coexistence state prediction, in which decision tree (DT) and naive Bayes classifier (NBC) are considered as supervised learning methods. Firstly, the average packet error rate (PER) and other 11 features extracted from signal to interference plus noise ratio (SINR), which have less computational cost, are selected and improved to reflect human relative movement and interference strength for feature extraction. Then, a set of models based on DT and NBC are generated with various configurations of different features, the number of continuous SINRs and the decision function. Finally, all models are compared and the best one is selected for state prediction. In the experiment, the data for training and testing is collected by CC2530 2.4 GHz low-power transceivers. Simulation results show that, compared with NBC based method, the proposed method is better in terms of accuracy and timeliness.

In this paper we quantify theoretically the effect of the desired-signal power level on the mean square filter estimation error and the normalized output signal-to-interference-plus-noise-ratio (SINR) of sample matrix inversion (SMI)-type estimates of the minimum mean-square-error (MMSE) and the linearly constrained minimum variance (LCMV) filters. We prove that in finite data support situations filters that utilize a sample average estimate of the desired-signal-absent input correlation matrix exhibit superior normalized filter output SINR and mean square filter estimation error when compared to filters that utilize a sample average estimate of the desired-signal-present input correlation matrix. Finally, we investigate pilot-assisted and decision-directed adaptive filter implementations that exhibit near desired-signal-absent SMI-filtering performance while they are trained using desired-signal-present data/observations.