Waveform Design for Airborne MIMO Radar with Inaccurate Priori Knowledge

We consider the problem of waveform design for Multiple-Input Multiple-Output (MIMO) radar in the presence of signal-dependent interference embedded in white Gaussian disturbance. We present two sequential optimization procedures to maximize the Signal to Interference plus Noise Ratio (SINR), accounting for a constant modulus constraint as well as a similarity constraint involving a known radar waveform with some desired properties (e.g., in terms of pulse compression and ambiguity). The presented sequential optimization algorithms, based on a relaxation method, yield solutions with good accuracy. Their computational complexity is linear in the number of iterations and trials in the randomized procedure and polynomial in the receive filter length. Finally, we evaluate the proposed techniques, by considering their SINR performance, beam pattern as well as pulse compression property, via numerical simulations.

Signal to interference plus noise ratio (SINR) based call admission control (CAC) scheme admits incoming calls as long as the measured SINR is higher than threshold value (SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> ). If a high value of SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> is chosen, the signal quality will improve but this will increase the blocking probability (p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> ), and as a result, will decrease the network utilization. On the other hand, a low value of SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> will reduce p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> , however degrades the signal quality and increases outage probability (p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">out</sub> ). Hence, how to choose appropriate SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> is very important. In this paper, we focus on the following aspects. Firstly, an accurate upper bound of SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> is derived. Secondly, based on the upper bound of SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> and a lower bound from other literature, we design a fuzzy logic controller (FLC), which can adaptively adjust SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> according to the number of active users (AUs) in a cell and average arriving traffic intensity (AATI) in Erlang per cell. Finally, network performance based on FLC is compared with that based on optimal fixed SINR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> . Numerical results show that the proposed scheme based on FLC has better performance than the optimal fixed threshold CAC scheme.

This paper presents a theoretical analysis of subband adaptive array combining the cyclic prefix transmission scheme (SBAA-CP) in a multipath fading environment. The exact expressions for optimal weights, array outputs and the output signal to interference plus noise ratio (SINR) are derived. The analysis shows that use of the cyclic prefix data transmission scheme can significantly improve the performance of subband adaptive array (SBAA). We also show that if the output SINR is plotted versus the delay of the delay path then the output SINR of SBAA-CP is in effect the SINR of SBAA shifted by C samples to the right.

The aim of this paper is to present a non‐linear statistical model to fit and forecast the signal‐to‐interference plus noise ratio (SINR) in two‐tier heterogeneous cellular networks which consist of macrocells and femtocells. Since in these networks the number and locations of femtocell base stations (FBS) are variable, SINR forecasting can be useful in some areas such as power control and handover management. So far, linear autoregressive (AR) models have commonly been used in forecasting the received signal strength (rss) in macrocellular networks. However, AR modelling results in high mean square error (MSE) when data are non‐linear. This paper focuses on SINR which takes into account signal strength, interference and noise effects. Moreover, macro‐femto cellular network is considered. The F ‐test results show that the SINR data are non‐linear, leading to use non‐linear models instead of AR model. A non‐linear logistic smooth threshold AR (LSTAR) model is utilised to model and forecast the SINR data. Kolmogorov–Smirnov (K‐S) test demonstrates that LSTAR provides good fitness to the SINR samples. The results indicate that LSTAR model achieves much better performance in modelling and forecasting of SINR data than the AR model.

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 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.

In downlink multiple streams multiple-input multiple-output (MIMO) system, adaptive modulation and coding (AMC) is used to increase spectrum efficiency (SE) due to selecting the modulation and coding rate scheme (MCS) dynamically. However, there is a gap between UE's signal to interference plus noise ratio (SINR) and that required by the MCS. In this paper, we propose a novel power loading algorithm using the SINR gap. The algorithm converts the SINR gap into the transmit power gap among different streams. Thus BS adjusts transmit power allocation for different streams and selects higher MCS than that without adjusting power. The results demonstrate that this proposed algorithm contributes large gain of SE for single user (SU-) MIMO based on singular value decomposition (SVD) preceding.

The Third Generation Partnership Project (3GPP) has been studying dynamic allocation of sub-frames to uplink (UL) or downlink (DL) in Time Division Duplex (TDD), called ‘Dynamic TDD,’ since the Long Term Evolution (LTE) Rel. 11 timeframe. At the same time, 3GPP is also standardizing Enhanced Local Area (eLA) small-cell heterogeneous architectures for inclusion in LTE-B (LTE Rel. 12) as a solution offering high data rate to user terminals (UEs) along with high system capacity through spatial reuse of spectrum. In this paper, we focus on a particular eLA architecture proposed by DOCOMO, called the Phantom Cell architecture, that has the option to support dynamic TDD. For an arbitrarily-located UE in an eLA cell network, we apply results from stochastic geometry to derive expressions for the distribution of DL signal to interference plus noise ratio (SINR) at an arbitrary UE and the distribution of UL SINR at its serving eLA base station (BS). We use these results to study aspects of eLA cell system design, and the sensitivity of SINR to the extent of coordination across eLA cells employing dynamic TDD.

In the first part of the thesis we investigate bandwidth allocation in next generation cellular systems employing relays similar to LTE advanced systems with type-I relays. We jointly optimize the bandwidth and power usage under constraints on required rate, bandwidth and transmit power. We study scenarios wherein, the relay acts as a forwarder for multiple User Equipments (UEs/users) in both uplink and/or downlink. This includes scenarios when the relay has its own data to send along with forwarding the data of other users. We examine the weighted power minimization problem for relaying with multiple users. We also show specifi c results with N user scenario and also single user case in order to understand how the bandwidth and power are allocated. Numerical evaluations with N users on a three sector LTE-A cell employing Fractional Frequency Reuse (FFR) indicate that power savings of at least 3 dB can be achieved by optimizing over both bandwidth and power. Base stations with a large number of transmit antennas have the potential to serve a large number of users simultaneously at higher rates. They also promise a lower power consumption due to coherent combining at the receiver. However, the receiver processing in the uplink relies on the channel stimates which are known to su ffer from pilot contamination. In the second part of the thesis, we perform an uplink large system analysis of multi-cell multi-antenna system when the receiver employs a matched fi ltering and MMSE fi ltering with a pilot contaminated estimate. We find the asymptotic Signal to Interference plus Noise Ratio (SINR) as the number of antennas and number of users per base station grow large while maintaining a fixed ratio. To do this, we make use of the similarity of the uplink received signal in a multi-antenna system to the representation of the received signal in CDMA systems. The asymptotic SINR expression for both matched fi lter and the MMSE fi lter explicitly captures the e ffect of pilot contamination and that of interference averaging. This also explains the SINR performance of receiver processing schemes at di fferent regimes such as instances when the number of antennas are comparable to number of users as well as when antennas exceed greatly the number of users. Specifi cally, we explore the scenario where the number of users being served are comparable to the number of antennas at the base station. It is seen that MMSE fi lter is capable of suppressing the in-cell interference and that the interference power due to pilot contamination is the same as in a matched fi lter with a pilot contaminated estimate. We find the expression for the amount of interference suppression obtained using an MMSE filter which is an important factor when there are signi ficant number of users in the system as compared to the number of antennas. We validate the asymptotic expression through simulations and compare with an MMSE fi lter with a perfect estimate. Simulation results for achievable rate is close to theory for even a 10-antenna base station with 3 or more users per cell. In a typical set up, in terms of the five percentile SIR, the MMSE fi lter is shown to provide signifi cant gains over matched fi ltering and is within 5 dB of MMSE fi lter with perfect channel estimate. We also show that the achievable rates are within a 1 bit/symbol of the MMSE with perfect estimate when the number of users is comparable to the number of antennas.

In this chapter, an effective blind source separation (BSS) algorithm is applied to solve the co-channel interference problem in wireless communication systems. Algorithms developed for this purpose must not only have the capability of working in the complex domain and improving output signal to interference plus noise ratio (SINR), but also have relatively low computational complexity. We propose a fast Fourier transform (FFT)-based algorithm called feedback independent component analysis (FebICA) that is able to blindly separate complex modulated digital signals. By applying this algorithm to communication signals, it is observed that it has the advantages of SINR gain improvement as well as low computational complexity. The performance of the FebICA algorithm is shown to be better than the joint approximate diagonalization of eigen-matrices (JADE) algorithm in terms of the output SINR and requires lower computational complexity than the analytical constant modulus algorithm (ACMA). The algorithm is also shown to be more robust with increasing number of sources compared to other algorithms. The separation performance by using the collected field data has also been demonstrated.

Due to cell planning in a cellular communication network, it is difficult for a mobile user in a cell to get ranging measurements from other neighboring cells. Consequently, it is necessary to enhance signal sensitivity using long integration techniques so that the user position is obtained by trilateration. In order to maximize integration gain in coherent/noncoherent hybrid long integration, it is desirable to make SNR (signal to noise ratio) after coherent integration become as large as possible. Because SIR (signal to interference ratio) is not improved by the long integration, however, it is needed to mitigate CCI (Co-Channel Interference) so that the resultant hearability can be enhanced for weak signals. This paper presents a hybrid long integration scheme in presence of CCI. SNIR (signal to noise plus interference ratio) is employed to explain the loss induced by interference as well as noise. Together with interference cancellation and residual frequency estimation technique, design procedure of hybrid long integration is proposed to maximize SNIR. Simulation results show that hearability is greatly improved at most of cell coverage when the proposed method is used.

Compression ideas are applied to the design of exceedingly fast SAR imagery clutter covariance processors for use in knowledge-aided (KA) airborne moving target indicator (AMTI) radar subjected to severely taxing disturbances. Outstanding signal to interference plus noise ratio (SINR) radar performance is derived with radar-blind highly compressed SAR imagery.

The fifth generation of wireless communications (5G) promises massive increases in traffic volume and data rates, as well as improved reliability in voice calls. Jointly optimizing beamforming, power control, and interference coordination in a 5G wireless network to enhance the communication performance to end users poses a significant challenge. In this paper, we formulate the joint design of beamforming, power control, and interference coordination as a non-convex optimization problem to maximize the signal to interference plus noise ratio (SINR) and solve this problem using deep reinforcement learning. By using the greedy nature of deep Q-learning to estimate future rewards of actions and using the reported coordinates of the users served by the network, we propose an algorithm for voice bearers and data bearers in sub-6 GHz and millimeter wave (mmWave) frequency bands, respectively. The algorithm improves the performance measured by SINR and sum-rate capacity. In realistic cellular environments, the simulation results show that our algorithm outperforms the link adaptation industry standards for sub-6 GHz voice bearers. For data bearers in the mmWave frequency band, our algorithm approaches the maximum sum-rate capacity, but with less than 4% of the required run time.

We consider the downlink of a multiple-input multiple-output broadcast channel where the transmitter uses per user unitary and rate control (PU2RC) to perform the user scheduling and beamforming. The main shortcoming of the PU2RC scheme is in networks where the number of users is less than or comparable with the codebook size. In these networks, PU2RC cannot properly exploit the available channel dimensions. To deal with this problem, they propose two different approaches to enhance the throughput performance of the system. In the first approach, they try to find and assign unscheduled users to the unused channel dimensions. This is done through a signal-to-interference plus noise ratio (SINR) estimation method in which they approximate the SINR of the users along new beamforming vectors. In this approach, they usually achieve the maximum multiplexing order of the system. In the second approach, they adjust the SINR feedbacks according to the number of scheduled users. When the number of scheduled users is less than the number of transmitting antennas, the feedback SINRs are in fact underestimated. In this case, they correct the SINRs and improve the average throughput. The simulation results show that both proposed methods can effectively improve the performance of the PU2RC scheme.

We introduce the signal-to-interference plus noise ratio (SINR) metric as a tool for selecting a rank reduction transformation that maximizes the output SINR of a direct form space-time adaptive processor. The SINR metric is used to identify the eigenvectors with the greatest impact on the output SINR which become the columns of the rank reduction transformation. The SINR metric method exhibits a graceful degradation in performance as the rank of the transformation approaches one.