Adaptive Multicell 3D Beamforming in Multi-Antenna Cellular Networks

We consider a cellular network with multi-antenna base stations (BSs) and single-antenna users, multicell cooperation, imperfect channel state information, and directional antennas each with a vertically adjustable beam. We investigate the impact of the elevation angle of the BS antenna pattern, denoted as tilt, on the performance of the considered network when employing either a conventional single-cell transmission or a fully cooperative multicell transmission. Using the results of this investigation, we propose a novel hybrid multicell cooperation technique in which the intercell interference is controlled via either cooperative beamforming in the horizontal plane or coordinated beamfroming in the vertical plane of the wireless channel, denoted as adaptive multicell 3D beamforming. The main idea is to divide the coverage area into two disjoint vertical regions and adapt the multicell cooperation strategy at the BSs when serving each region. A fair scheduler is used to share the time-slots between the vertical regions. It is shown that the proposed technique can achieve performance comparable to that of a fully cooperative transmission but with a significantly lower complexity and signaling requirements. To make the performance analysis computationally efficient, analytical expressions for the user ergodic rates under different beamforming strategies are also derived.Comment: Accepted for publication in IEEE Transaction on Vehicular Technolog

Distributed Multicell Beamforming Design Approaching Pareto Boundary with Max-Min Fairness

This paper addresses coordinated downlink beamforming optimization in multicell time-division duplex (TDD) systems where a small number of parameters are exchanged between cells but with no data sharing. With the goal to reach the point on the Pareto boundary with max-min rate fairness, we first develop a two-step centralized optimization algorithm to design the joint beamforming vectors. This algorithm can achieve a further sum-rate improvement over the max-min optimal performance, and is shown to guarantee max-min Pareto optimality for scenarios with two base stations (BSs) each serving a single user. To realize a distributed solution with limited intercell communication, we then propose an iterative algorithm by exploiting an approximate uplink-downlink duality, in which only a small number of positive scalars are shared between cells in each iteration. Simulation results show that the proposed distributed solution achieves a fairness rate performance close to the centralized algorithm while it has a better sum-rate performance, and demonstrates a better tradeoff between sum-rate and fairness than the Nash Bargaining solution especially at high signal-to-noise ratio.Comment: 8 figures. To Appear in IEEE Trans. Wireless Communications, 201

System Level Simulation and Radio Resource Management for Distributed Antenna Systems with Cognitive Radio and Multi-Cell Cooperation

4th International Conference on Future Generation Communication Technologies (FGCT 2015), Luton, United Kingdom.The performance of wireless networks will experience a considerable improvement by the use of novel technologies such as distributed antenna systems (DASs), multi-cell cooperation (MCC), and cognitive radio (CR). These solutions have shown considerable gains at the physical-layer (PHY). However, several issues remain open in the system-level evaluation, radio resource management (RRM), and particularly in the design of billing/licensing schemes for this type of system. This paper proposes a system-level simulator (SLS) that will help in addressing these issues. The paper focuses on the description of the modules of a generic SLS that need a modification to cope with the new transmission/economic paradigms. An advanced RRM solution is proposed for a multi-cell DAS with two levels of cooperation: inside the cell (intra-cell) to coordinate the transmission of distributed nodes within the cell, and between cells (inter-cell or MCC) to adapt cell transmissions according to the collected inter-cell interference measurements. The RRM solution blends network and financial metrics using the theory of multiobjective portfolio optimization. The core of the RRM solution is an iterative weighted least squares (WLS) optimization algorithm that aims to schedule in a fair manner as many terminals as possible across all the radio resources of the available frequency bands (licensed and non-licensed), while considering different economic metrics. The RRM algorithm includes joint terminal scheduling, link adaptation, space division multiplexing, spectrum selection, and resource allocation

Optimize Power Allocation Scheme to Maximize Sum Rate in CoMP with Limited Channel State Information

Extensive use of mobile applications throws many challenges in cellular systems like cell edge throughput, inter cell interference and spectral e�ciency. Many of these challenges have been resolved using Coordinated Multi-Point (CoMP), developed in the Third Generation Partnership Project for LTE-Advanced) to a great extent. CoMP cooperatively process signals from base sta- tions that are connected to various multiple terminals (user equipment (UEs)) at transmission and reception. This CoMP improves throughput, reduces or even removes inter-cell interference and increases spectral e�ciency in the downlink of multi-antenna coordinated multipoint systems. Many researchers addressed these issues assuming that BSs have the knowledge of the common control channels dedicated to all UEs and also about the full or partial channel state information (CSI) of all the links. From the CSI available at the BSs, multiuser interference can be managed at the BSs. To make this feasible, UEs are responsible for collecting downlink CSI. But, CSI measurement (instantaneous and/or statistical) is imperfect in nature because of the randomly varying nature of the channels at random times. These incorrect CSI values available at the BSs may, in turn, create multi-user interference. There are many techniques to suppress the multi-user interference, among which the feedback scheme is the one which is gaining a lot of attention. In feedback schemes, CSI information needs to be fed back to the base station from UEs in the uplink. It is obvious, the question arises on the type and amount of feedback need to be used. Research has been progressing in this front and some feedback techniques have been proposed. Three basic CoMP Feedback schemes are available. Explicit or statistical channel information feedback scheme in which channel information like channels's covariance matrix of the channel are shared between the transmitter and receiver. Next, implicit or statistical channel information feedback which contains information such as Channel quality indication or Precoding matrix indicator or Rank indicator. 1st applied to TDD LTE type structure and 2nd of feedback scheme can be applied in the FDD system. Finally, we have UE which tranmit the sounding reference signal (CSI). This type of feedback scheme is applied to exploit channel reciprocity and to reduce channel intercell interference and this can be applied in the TDD system. We have analyzed the scenario of LTE TDD based system. After this, optimization of power is also required because users at the cell edge required more attention than the user locating at the center of the cell. In my work, it shows estimated power gives exponential divercity for high SNR as low SNR too. In this method, a compression feedback method is analyzed to provide multi-cell spatial channel information. It improves the feedback e�ciency and throughput. The rows and columns of the channel matrix are compressed using Eigenmode of the user and codebook based scheme speci�ed in LTE speci�cation. The main drawback of this scheme is that spectral e�ciency is achieved with the cost of increased overheads for feedback and evolved NodeB (eNB). Other factor is complexity of eNodeB which is to be addressed in future work

Secure Satellite Communication Systems Design with Individual Secrecy Rate Constraints

In this paper, we study multibeam satellite secure communication through physical (PHY) layer security techniques, i.e., joint power control and beamforming. By first assuming that the Channel State Information (CSI) is available and the beamforming weights are fixed, a novel secure satellite system design is investigated to minimize the transmit power with individual secrecy rate constraints. An iterative algorithm is proposed to obtain an optimized power allocation strategy. Moreover, sub-optimal beamforming weights are obtained by completely eliminating the co-channel interference and nulling the eavesdroppers' signal simultaneously. In order to obtain jointly optimized power allocation and beamforming strategy in some practical cases, e.g., with certain estimation errors of the CSI, we further evaluate the impact of the eavesdropper's CSI on the secure multibeam satellite system design. The convergence of the iterative algorithm is proven under justifiable assumptions. The performance is evaluated by taking into account the impact of the number of antenna elements, number of beams, individual secrecy rate requirement, and CSI. The proposed novel secure multibeam satellite system design can achieve optimized power allocation to ensure the minimum individual secrecy rate requirement. The results show that the joint beamforming scheme is more favorable than fixed beamforming scheme, especially in the cases of a larger number of satellite antenna elements and higher secrecy rate requirement. Finally, we compare the results under the current satellite air-interface in DVB-S2 and the results under Gaussian inputs.Comment: 34 pages, 10 figures, 1 table, submitted to "Transactions on Information Forensics and Security

Capacity and Fairness of Distributed Antenna Systems in Multi-Cell Environments with User Scheduling, Power Control and Imperfect CSI

Distributed antenna systems (DASs) have attractedlots of attention as a method to improve the performance of futurewireless networks. Capacity analysis and optimum power allocationfor the physical layer of DASs have been extensively exploredin the literature. However, the study of cross-layer issues, suchas channel-aware scheduling and fairness evaluation, is relativelyscarce. This paper partially fills this gap by addressing the downlinkcapacity and fairness analysis of a DAS assisted by jointuser scheduling and transmit power control. The algorithm isevaluated in a multi-cell environment assuming imperfect channelstate information. The algorithm exploits the spatial diversityprovided by the distributed antennas in order to schedule over thesame frequency band a different user attached to each one of thedistributed nodes. The objective is to optimize the power levelsto control the interference created between the transmissionsof the selected users, thereby multiplexing as many of them aspossible while maximizing capacity. To achieve this goal, a sumratecapacity optimization with respect to the power levels ishere proposed by using a gradient descent iterative technique.The result is the set of optimum user-antenna pairs to bescheduled and their optimum power levels. Inter-cell interferenceis calculated by reusing the results of previous simulation runsin the transmission parameters of outer-cells, thereby efficientlyreplicating system-level behavior. The algorithm is also evaluatedin terms of fairness by using the spatial distribution of the usercapacity. Capacity and fairness of the algorithm considerablyoutperform previous solutions, particularly in scenarios withgood line-of-sight and optimum node location