Ahmed Abdelhadi

Spectrum sharing between S-band radar and LTE cellular system: A spatial approach

Spectrum sharing is a new way forward to solve spectrum scarcity problem. In this paper, we propose a spatial approach for spectrum sharing between a MIMO radar and an LTE cellular system with NBS base stations (BS). The MIMO radar and LTE share NBS interference channels i.e. Hi, i = 1,2, ..., NBS. We propose projecting the radar signal onto the null space of interference channel between the MIMO radar and LTE using our proposed interference-channel-selection algorithm, in order to have zero-interference from the MIMO radar. We select interference channel with the maximum null space i.e. arg max1≤i≤NBS dim [N(Hi)] and project the radar signal onto the null space of this channel. Our proposed spatial spectrum-sharing algorithm is radar-centric such that it causes minimum loss in radar performance by carefully selecting the interference channel and at the same time protects the ith LTE BS from the radar interference. Through our analytical and simulation results we show that the loss in the radar performance is less when the proposed interference-channel-selection algorithm is used to select the channel onto which radar signals are projected.

A utility proportional fairness approach for resource allocation in 4G-LTE

In this paper, we introduce an approach for resource allocation of elastic and inelastic adaptive real-time traffic in fourth generation long term evolution (4G-LTE) system. In our model, we use logarithmic and sigmoidal-like utility functions to represent the users applications running on different user equipments (UE)s. We present a resource allocation optimization problem with utility proportional fairness policy, where the fairness among users is in utility percentage (i.e user satisfaction with the service) of the corresponding applications. Our objective is to allocate the resources to the users with priority given to the adaptive real-time application users. In addition, a minimum resource allocation for users with elastic and inelastic traffic should be guaranteed. Our goal is that every user subscribing for the mobile service should have a minimum quality-of-service (QoS) with a priority criterion. We prove that our resource allocation optimization problem is convex and therefore the optimal solution is tractable. We present a distributed algorithm to allocate evolved NodeB (eNodeB) resources optimally with a priority criterion. Finally, we present simulation results for the performance of our rate allocation algorithm.

Utility Proportional Fairness Resource Allocation with Carrier Aggregation in 4G-LTE

In this paper, we consider a resource allocation optimization problem with carrier aggregation in fourth generation long term evolution (4G-LTE). In our proposed model, each user equipment (UE) is assigned a utility function that represents the application type running on the UE. Our objective is to allocate the resources from two carriers to each user based on its application that is represented by the utility function assigned to that user. We consider two groups of users, one with elastic traffic and the other with inelastic traffic. Each user is guaranteed a minimum resource allocation. In addition, a priority resource allocation is given to the UEs running adaptive real time applications. We prove that the optimal rate allocated to each UE by the single carrier resource allocation optimization problem is equivalent to the aggregated optimal rates allocated to the same user by the primary and secondary carriers when their total resources is equivalent to the single carrier resources. Our goal is to guarantee a minimum quality of service (QoS) that varies based on the user application type. We present a carrier aggregation rate allocation algorithm to allocate two carriers resources optimally among users. Finally we present simulation results with the carrier aggregation rate allocation algorithm.

A robust optimal rate allocation algorithm and pricing policy for hybrid traffic in 4G-LTE

In this paper, we consider resource allocation optimization problem in the fourth generation long-term evolution (4G-LTE) with elastic and inelastic real-time traffic. Mobile users are running either delay-tolerant or real-time applications. The users applications are approximated by logarithmic or sigmoidal-like utility functions. Our objective is to allocate resources according to the utility proportional fairness policy. Prior utility proportional fairness resource allocation algorithms fail to converge for high-traffic situations. We present a robust algorithm that solves the drawbacks in prior algorithms for the utility proportional fairness policy. Our robust optimal algorithm allocates the optimal rates for both high-traffic and low-traffic situations. It prevents fluctuation in the resource allocation process. In addition, we show that our algorithm provides traffic-dependent pricing for network providers. This pricing could be used to flatten the network traffic and decrease the cost per bandwidth for the users. Finally, numerical results are presented on the performance of the proposed algorithm.

MIMO radar waveform design for coexistence with cellular systems

The design of multiple-input multiple-output (MIMO) radar waveforms with specified properties has a number of applications including clutter suppression and interference mitigation. In this paper, we design radar waveforms with the aim to mitigate radar interference to communication system. We design constant envelope (CE) transmit beampattern of a MIMO radar, when it is sharing its spectrum with a cellular system, with the constraint that the waveform is in the null space of interference channel between radar and communication system. We design the desired beampattern by unconstrained nonlinear optimization of the desired covariance matrix. We consider waveform design problem for a stationary maritime MIMO radar when interference channels are changing slowly and thus they can be included in the beampattern matching optimization problem. In addition, we also consider the case when the maritime MIMO radar is moving and thus experiences interference channels that are changing fast enough to be not included in the optimization problem. For this case, we design the CE waveform first and then project it onto the null space of interference channel, before transmission, in order to have zero interference to the communication system. We demonstrate, through simulations, the effect of including the constraint of spectrum sharing or the waveform be in the null space of interference channel on the CE waveform design.

Target Detection Performance of Spectrum Sharing MIMO Radars

Future wireless communication systems are envisioned to share radio frequency spectrum with radars in order to meet the growing spectrum demands. In this paper, we address the problem of target detection by radars that project waveform onto the null space of interference channel in order to mitigate interference to cellular systems. We consider a multiple-input multiple-output (MIMO) radar and an MIMO cellular communication system with X base stations (BSs). We consider two spectrum sharing scenarios. In the first scenario, the degrees of freedom (DoF) available at the radar are not sufficient enough to simultaneously detect target and mitigate interference to X BSs. For this case, we select one BS among X BSs for waveform projection on the basis of guaranteeing minimum waveform degradation. For the second case, the radar has sufficient DoF to simultaneously detect target and mitigate interference to all X BSs. We study target detection capabilities of null-space projected (NSP) waveform and compare it with the orthogonal waveform. We derive the generalized likelihood ratio test for target detection and derive detector statistic for NSP and orthogonal waveform. The target detection performance for both waveforms is studied theoretically and via Monte Carlo simulations.

Spectrum sharing between public safety and commercial users in 4G-LTE

In this paper, we consider resource allocation optimization problem in fourth generation long term evolution (4G-LTE) for public safety and commercial users running elastic or inelastic traffic. Each mobile user can run delay-tolerant or real-time applications. In our proposed model, each user equipment (UE) is assigned a utility function that represents the application type running on the UE. Our objective is to allocate the resources from a single evolved node B (eNodeB) to each user based on the user application that is represented by the utility function assigned to that user. We consider two groups of users, one represents public safety users with elastic or inelastic traffic and the other represents commercial users with elastic or inelastic traffic. The public safety group is given priority over the commercial group and within each group the inelastic traffic is prioritized over the elastic traffic. Our goal is to guarantee a minimum quality of service (QoS) that varies based on the user type, the user application type and the application target rate. A rate allocation algorithm is presented to allocate the eNodeB resources optimally among public safety and commercial users. Finally, the simulation results are presented on the performance of the proposed rate allocation algorithm.

Beampattern analysis for MIMO radar and telecommunication system coexistence

In this paper, we present a beampattern analysis of the MIMO radar coexistence algorithm proposed in [1]. We extend the previous work and analyze the performance of MIMO radars by projecting finite alphabet constant-envelope waveforms onto the null-space of interference channel matrix. First, we compare and analyze the Cramér-Rao bound (CRB) on angle direction estimation. Second, we compare and analyze beampatterns of the original radar waveform and the null-projected radar waveform. Analytical and simulation results show minimal degradation of a radars angle estimation of a target and transmit-receive beampattern. We also propose methods to substantially improve angle estimation and beampatterns of a null projected radar waveform which will not only guarantee optimal performance of the radar but at the same time guarantee coexistence of the radar and communication systems.

A Utility Proportional Fairness Resource Allocation in Spectrally Radar-Coexistent Cellular Networks

Spectrum sharing is an elegant solution to addressing the scarcity of the bandwidth for wireless communications systems. This research studies the feasibility of sharing the spectrum between sectorized cellular systems and stationary radars interfering with certain sectors of the communications infrastructure. It also explores allocating optimal resources to mobile devices in order to provide with the quality of service for all running applications whilst growing the communications network spectrally coexistent with the radar systems. The rate allocation problem is formulated as two convex optimizations, where the radar-interfering sector assignments are extracted from the portion of the spectrum non-overlapping with the radar operating frequency. Such a double-stage resource allocation procedure inherits the fairness into the rate allocation scheme by first assigning the spectrally radar-overlapping resources.

On The Impact of Time-Varying Interference-Channel on the Spatial Approach of Spectrum Sharing between S-band Radar and Communication System

Spectrum sharing is a new approach to solve the congestion problem in RF spectrum. A spatial approach for spectrum sharing between radar and communication system was proposed, which mitigates the radar interference to communication by projecting the radar waveform onto null space of interference channel, between radar and communication system [1]. In this work, we extend this approach to maritime MIMO radar which experiences time varying interference channel due to the oscillatory motion of ship, because of the breaking of sea/ocean waves. We model this variation by using the matrix perturbation theory and the statistical distribution of the breaking waves. This model is then used to study the impact of perturbed interference channel on the spatial approach of spectrum sharing. We use the maximum likelihood (ML) estimate of targets angle of arrival to study the radars performance when its waveform is projected onto the null space of the perturbed interference channel. Through our analytical and simulation results, we study the loss in the radars performance due to the null space projection (NSP) of its waveform on the perturbed interference channel.