Adaptive Beamforming Based on Flamingo Search Algorithm with Early-Stop Strategy

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

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.

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.

The problem of cochannel interference (CCI) suppression using a noise-plus-interference whitening matched filter (WMF) is addressed. Binary phase-shift keying modulated transmission over a Nakagami-m fading channel is considered in a bandlimited microcellular wireless system. It is shown that the signal-to-interference-plus-noise ratio (SINR) of the WMF can not exceed that of the conventional matched filter (CMF) receiver for synchronous CCI, but in the asynchronous channel, CCI whitening can be used to improve receiver performance. The SINR-maximizing filter (SINRMF) in an asynchronous channel is derived and shown to be composed of a WMF followed by a discrete time filter. The SINRs of the WMF and SINRMF receivers are analytically evaluated for a standard raised-cosine (RC) and a Beaulieu-Tan-Damen pulse. It is shown that for the RC pulse, the WMF can achieve a SINR gain as large as 1.76 dB over the CMF receiver provided that the transmission is free of intersymbol interference (ISI). The SINR of the ISI-impaired system is also evaluated and the conditions under which this system can achieve close to ISI-free SINR are studied. The SINR is evaluated for the SINRMF and it is shown that this filter can restore much of the SINR loss incurred due to ISI introduced by the WMF.

A novel beamforming technique using mmWave antenna arrays for 5G wireless communication networks

When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

This paper presents a robust adaptive beamforming algorithm based on an attention convolutional neural network (ACNN) for coprime sensor arrays, named the CAWE-ACNN algorithm. In the proposed algorithm, via a spatial and channel attention unit, an ACNN model is constructed to enhance the features contributing to beamforming weight vector estimation and to improve the signal-to-interference-plus-noise ratio (SINR) performance, respectively. Then, an interference-plus-noise covariance matrix reconstruction algorithm is used to obtain an appropriate label for the proposed ACNN model. By the calculated label and the sample signals received from the coprime sensor arrays, the ACNN is well-trained and capable of accurately and efficiently outputting the beamforming weight vector. The simulation results verify that the proposed algorithm achieves excellent SINR performance and high computation efficiency.

This paper addresses the robustness of adaptive narrowband beamforming with respect to bandwidth based on the loss of performance in terms of signal-to-interference-plus-noise ratio (SINR). The criterion used by Zatman to define a narrowband environment, i.e., the ratio between the jammer plus noise covariance matrix and the noise eigenvalue, is studied from the point of view of a loss of SINR after narrowband beamforming under non narrowband conditions. Using theoretical results about the eigenvalues and eigenvectors of covariance matrices for signals closely spaced in frequency by Lee, it is shown that Zatman's criterion can be interpreted as an upper bound on the SINR loss which is nearly reached under certain conditions that are specified.

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.

This paper deals with the problem of adaptive beamforming using a uniform linear array to suppress the coherent interference in the presence of multiple GPS signals. For coping with the performance degradation due to the presence of coherent interference, a matrix reconstruction scheme in conjunction with an iterative algorithm is designed to alleviate the effect of the coherent interference. And then an interference-blocking (IB) transformation is developed for removing coherent interference, while the desired signals and noise retained. Adaptive beamforming is then performed based on the IB transformation data consisting of the desired signals and noise to produce maximum output signal-to-interference-plus-noise ratio (SINR). Simulation examples for illustration and comparison are also given.

The performance of adaptive beamforming degrades in presence of signal model mismatches. In particular, when the desired signal is present in training snapshots, the adaptive beamforming is quite sensitive to desired signal steering vector mismatch. Therefore, a robust adaptive beamforming for actual system is proposed based on the reconstruction of interference covariance matrix and mismatched steering vector compensation. In the proposed method, the interference covariance matrix is firstly reconstructed by using Root-MUSIC method to estimate Direction-of-Arrival (DOA) of signals, where the desired signal component is removed from the training snapshots. Subsequently, the mismatched desired signal steering vector is compensated by solving a quadratically constrained quadratic programming problem. Simulation results show that the performance of proposed algorithm outperforms the existing robust adaptive beamforming, and the output signal-to-interference-plus-noise ratio (SINR) is close to optimal values. Therefore, the proposed algorithm could be significantly effective for actual system.

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.

We propose an adaptive transmit and receive beam forming (TRBF) scheme for Time Division Duplex Multiple Input and Multiple Output (TDD-MIMO) system. Through analyzing the anti-jamming mechanism and deficiency from the point of subspace projection, we solve the optimization problem of designing TRBF and give an adaptive scheme. Firstly, the receiver determines receive beam former according to the legitimate channel matrix and interference null space. Secondly, the receiver uses the receive beam former as the transmit beam former to send training sequences to the transmitter for estimating the receive space. Finally, the transmitter determines the transmit beam former to correct the transmit power pointing to the receive space for avoiding power leakage. Since all of the transmit power reaches receiver and is collected, the receiver can get the maximum signal-to interference plus noise ratios (SINR). Simulation results show that the proposed method outperforms conventional beam forming significantly and has a similar performance to the theoretical value in the presence of repressive and deceptive interference.

A widely linear momentum linearly constrained constant modulus algorithm for the multi-access interferences (MAI) suppression in direct sequence code division multiple access (DS-CDMA) systems is proposed and analyzed in this paper. The widely linear estimation enables constant modulus algorithm (CMA) to produce better output signal to interference plus noise ratio (SINR) and the momentum fastens the convergence. Simulations have confirmed that the proposed algorithm performs better in a DS-CDMA system by employing a BPSK modulation than other algorithms that do not use widely linear processing and momentum.

Closed-form expressions for the output signal-to-interference-plus-noise ratio (SINR) in ultra-wideband (UWB) receivers are derived for the IEEE channel models. Unlike results in the literature where only the inter-symbol and/or multiple-access interferences are considered, the derivation in this paper also takes into account inter-path and inter-chip interferences. Effects of the spreading gain and the pulse duration on the output SINR are examined. As an application, the optimal integration interval that maximizes the output SINR for a transmitted reference UWB receiver is studied.