SINR tight lower bound for asynchronous OFDM-based multiple-access networks

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.

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

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.

For future high-speed orthogonal frequency division multiplexing (OFDM) wireless communications, two major system requirements will exist: broadband transmission and rich interference elimination. Because of its broadband nature and limited frequency allocations worldwide, interference from co-located wireless LAN operating in the same frequency band will become a serious deployment issue, since interference may have a large amount of multipath and also have similar levels of received power compared to the desired signal. This paper presents recent investigations in OFDM smart antenna systems, more specifically the signal properties in the frequency domain, for co-channel interference detection and rejection. A novel architecture is proposed in this paper, which is a complexity-reduced frequency-domain technique using subcarrier clustering. Research results are presented and show that the proposed architecture can achieve high performance with low complexity, within a rich multipath environment with low signal to noise plus interference ratio (SNIR).

We propose a link adaptation and selection method for the links constituting an orthogonal frequency division multiplexing (OFDM) based wireless relay network. The proposed link adaptation and selection method selects the forwarding, modulation, and channel coding schemes providing the highest end-to- end throughput and decides whether to use the relay or not. The link adaptation and selection is done for each sub-channel based on instantaneous signal to interference plus noise ratio (SINR) conditions in the source-to-destination, source-to-relay and relay- to-destination links. The considered forwarding schemes are amplify and forward (AF) and simple adaptive decode and forward (DF). Efficient adaptive modulation and coding decision rules are provided for various relaying schemes. The proposed end-to-end link adaptation and selection method ensures that the end-to-end throughput is always larger than or equal to that of transmissions without relay and non-adaptive relayed transmissions. Our evaluations show that over the region where relaying improves the end- to-end throughput, the DF scheme provides significant throughput gain over the AF scheme provided that the error propagation is avoided via error detection techniques. We provide a frame structure to enable the proposed link adaptation and selection method for orthogonal frequency division multiple access (OFDMA)-time division duplex relay networks based on the IEEE 802.16e standard.

The use of orthogonal frequency division multiplexing (OFDM) in frequency selective fading environments has been well explored. However, OFDM is more prone to time selective fading as compared to single carrier systems. Rapid time variations destroy the subcarrier orthogonality and introduce inter-carrier interference (ICI). Besides this, obtaining reliable channel estimates for receiver equalization is a non-trivial task in rapidly fading systems. In our work, we have addressed the problem of channel estimation and ICI suppression by viewing the system as a state space model. Kalman filter is employed to estimate the channel; this is followed by a time domain ICI mitigation filter which maximizes the SINR (signal to interference plus noise ratio). This method is seen to provide significant SINR gain with low training overhead.

Based on the space alternating generalized expectation maximization (SAGE) technique, and the ordered serial interference cancellation (OSIC) algorithm, an improved low-complexity inter-carrier interference (ICI) mitigation scheme, named SAGE-OSIC, is proposed for high mobile orthogonal frequency division multiplexing (OFDM) systems, where the subcarriers are updated in series, according to the order of the decreasing signal to interference plus noise ratio (SINR) or signal to noise ratio (SNR). The computational complexity is investigated, and simulation studies are concluded over multipath fading and rapidly time-varying channels. It is indicated that the proposed SAGE-OSIC scheme significantly outperforms the existing low-complexity ICI mitigation methods based on SAGE, without any increase in the computational complexity, especially for the large Doppler shifts in highly mobile environments. Furthermore, it can also be concluded that the performance of the proposed SAGE-OSIC approaches that of the vertical Bell laboratory layered space-time (VBLAST) scheme, which demands very high computation.

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.

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 previously proposed first-order perturbation-based algorithm and linear constrained least mean square (LMS) based algorithm for channel matrix singular value decomposition (SVD) in multiple - input multiple - output (MIMO) orthogonal frequency division multiplexing (OFDM) systems are evaluated and compared in this paper from orthogonality, signal to noise plus interference ratio (SINR) and bit error rate (BER) view points. Due to approximations made in the perturbation-based algorithm to reduce its complexity, studies show that the estimates of the right and left singular matrices do not become unitary in this algorithm. This phenomenon causes more spatial interference and therefore the perturbation-based algorithm has less performance in comparison with the LMS-based algorithm at high SNRs.

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 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)

We consider a system where a licensed radio spectrum is shared by two networks, namely the primary network and the secondary network. The spectrum is licensed to the primary network, however the secondary network makes opportunistic access of the unused and/or underutilized portions of it by using cognitive radio technology. For such a system, we study the problem of joint power control and beamforming in the downlink of the cognitive radio network and formulate two iterative algorithms considering two different scenarios of spectrum sharing. In the first case, the primary network cooperates with the secondary network to jointly optimize the transmit beamforming weights and total transmitted power by both networks subject to signal to interference plus noise ratio (SINR) constraints of both primary and secondary users. In the second case, the secondary network jointly optimizes the transmit beamforming weights and its total transmitted power satisfying the SINR constraint of the secondary users and maximum tolerable interference constraint to the primary user. Simulation results are provided to show convergence behavior of the iterative algortihms.

Ultra-dense networks (UDNs) have been widely regarded as a promising technology to meet higher requirements of the fifth generation (5G) network. However, densely deployed femtocells bring an unprecedented challenge of importing severe co-channel interference (CCI), which greatly limits the performance of the network. Therefore, interference management in UDNs is particularly important. The conflict-graph is widely recognized as the representation of underlying interference constraints of the network. Most prior studies establish conflict-graphs based on accurate geographical distance information which is usually unavailable by the network operators in practice. A more practical neural network based conflict-graph construction approach, which utilizes up-link signal to interference plus noise ratio (SINR) data and up-link resource block (RB) allocation data, is proposed in this paper. These data are used to train a neural network for predicting the up-link SINR under single interfering user conditions. Utilizing the predicted SINR data as the edge weights of the constructed conflict-graph considers both the influence of inter-user interference and the interference tolerance ability of each user, which better reflects the resource reuse conflict between users. Users can collaborate and coordinate their resource allocation strategies according to the constructed conflict-graph so as to mitigate severe CCI in the network. Therefore, the proposed approach facilitates the realization of the intelligent resource allocation optimization. Furthermore, the proposed conflict-graph construction approach achieves quite a high accuracy, which has been verified by simulation results.

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.