Gary Boudreau

Coordinated Port Selection and Beam Steering Optimization in a Multi-Cell Distributed Antenna System using Semidefinite Relaxation

In this paper, we consider coordinated downlink transmission in a cellular system wherein each base station (BS) has multiple geographically dispersed antenna ports. Each port uses a fixed transmit power and the goal of the BSs is to collectively determine the subset of ports and the corresponding beam steering coefficients that maximize the minimum signal-to-interference-plus-noise ratio observed by the user terminals. This problem is NP-hard. To circumvent this difficulty, a two-stage polynomial-complexity technique that relies on semidefinite relaxation and Gaussian randomization is developed. It is shown that, for the considered scenarios, the port state vectors and beam steering coefficients generated by the proposed technique yield a performance comparable to that yielded by exhaustive search, but with a significantly less computational complexity. It is also shown that the proposed technique results in significant power savings when compared with other transmission strategies proposed in the literature.

An Efficient Clustering Algorithm for Device-to-Device Assisted Virtual MIMO

In this paper, the utilization of mobile devices (MDs) as decode-and-forward relays in a device-to-device assisted virtual MIMO (VMIMO) system is studied. Single antenna MDs are randomly distributed on a 2D plane according to a Poisson point process, and only a subset of them are sources leaving other idle MDs available to assist them (relays). Our goal is to develop an efficient algorithm to cluster each source with a subset of available relays to form a VMIMO system under a limited feedback assumption. We first show that the NP-hard optimization problem of precoding in our scenario can be approximately solved by semidefinite relaxation. We investigate a special case with a single source and analytically derive an upper bound on the average spectral efficiency of the VMIMO system. Then, we propose an optimal greedy algorithm that achieves this bound. We further exploit these results to obtain a polynomial time clustering algorithm for the general case with multiple sources. Finally, numerical simulations are performed to compare the performance of our algorithm with that of an exhaustive clustering algorithm, and it shown that these numerical results corroborate the efficiency of our algorithm.

Downlink Linear Transmission Schemes in a Single-Cell Distributed Antenna System with Port Selection

A cellular distributed antenna system (DAS) allows mobile user terminals (UTs) to be served at higher data rates as compared to conventional cellular systems by reducing the path loss and attaining macrodiversity gains. Moreover, such a cellular DAS can be perceived as a distributed multi-user multiple-input multiple-output system. In this paper, the block diagonalization and zero-forcing dirty-paper coding downlink transmission schemes are extended for a single-cell DAS with multi-antenna distributed antenna ports (DAPs) and multi-antenna UTs, where only a subset of all DAPs in the cell transmit to each UT. The aggregate cell spectral efficiency that is achieved by these schemes per frequency-time resource block is compared for both DAS and collocated antenna system (CAS) architectures, subject to the same total power constraint. The gains of the cellular DAS over the cellular CAS are demonstrated, and the effect of the number of antennas per DAP on the performance of the cellular DAS is investigated.

Optimal power allocation in device-to-device communication with SIMO uplink beamforming

Cellular and device-to-device (D2D) communication may cause significant inter-cell interference (ICI) at a neighboring base station (BS). In this work, we aim to maximize the sum rate of a cellular user (CU) and a D2D pair, with receive beamforming at the BS equipped with multiple antennas, subject to per-node power, maximum ICI, and minimum SINR constraints. We propose an efficient algorithm to maximize the sum rate in two steps. We first consider the D2D admissibility problem to determine whether the D2D pair can share the spectrum with the CU while satisfying all the constraints and SINR requirements. We then obtain the optimal beam vector and the optimal power levels of the CU and D2D transmitters in closed form. The performance of the proposed algorithm is studied numerically. It is shown the proposed optimal solution substantially outperforms a CU-priority heuristic approach that selects the maximum CU power with minimum D2D interference.

Distributed cached and segmented video download for video transmission in cellular networks

Wireless video accounted for more than half of the total data traffic in cellular networks in 2015, and this is expected to further increase in the upcoming years. Device-to-Device (D2D) communication, introduced by the LTE-Advanced (LTEA) standard, allows direct communication between devices in cellular networks. Here, we introduce the DIStributed, Cached, and Segmented video download (DISCS) algorithm for improving the throughput of video transmission in cellular networks based on D2D communications. The algorithm splits video files into pieces, which are distributed over selected user equipment (UEs) in the cellular network, to cache and forward the pieces using D2D communication. We used the Discrete EVent System Specification (DEVS) formalism to build an LTEA network model and used the model to study the performance of DISCS. Simulation results show that DISCS achieves significant performance improvements in terms of the cells aggregate data rate as well as the average data rate per user.

Using elected coordination stations for CSI feedback on CoMP downlink transmissions

The higher demand for data traffic and the emergence of new applications has made mobile networks challenging to maintain high data rates for users, in particular those located on the cells edges. The Coordinated Multipoint (CoMP) technology adopted in long-term evolution (LTE) cellular networks allows improving the cells edge performance. In order to improve throughput performance gain in the downlink, the CoMP scheduler needs to know/deal the channel information for all the collaborating Base Stations. To do so, we propose a method for handling Channel State Information (CSI) feedback, named DCEC: Direct CSI feedback to Elected Coordination station. The DCEC architecture aims to reduce the overhead and latency of the network, and subsequently increase its throughput. To model the proposed architecture in the cellular network, we have used the Discrete Event System Specification (DEVS) formalism. The simulation results demonstrate that the DCEC architecture significantly decreases the number of CSI feedback packets being transmitted within the network and reduces the feedback latency resulting in higher data rates for users.

Signaling overhead and feedback delay reduction in heterogeneous multicell cooperative networks

Heterogeneous networks (HetNets) and multicell cooperation are two key technologies in cellular networks that can improve network performance. The channel information of all the collaborating Base Stations (BSs) is one of the core factors to achieve better throughput performance gain in the coordinated multipoint (CoMP) communication. Here, we propose a novel method for handling Channel State Information (CSI) feedback in HetNet CoMP, named DCEC-HetNet: Direct CSI-feedback to Elected Coordination-station for Heterogeneous Networks. The DCEC-HetNet architecture aims to reduce the signaling overhead and feedback latency, and subsequently increase the throughput of the network. We use the Discrete Event System Specification (DEVS) formalism to model the cellular network. The simulation results demonstrate that the DCEC-HetNet architecture significantly decreases the number of CSI feedback packets being transmitted within the network, and reduces the feedback latency resulting in higher cell throughput.

Multi-Channel Resource Allocation Toward Ergodic Rate Maximization for Underlay Device-to-Device Communications

In underlay device-to-device (D2D) communications, a D2D pair reuses the cellular spectrum causing interference to regular cellular users. Maximizing the performance of underlay D2D communications requires joint consideration for the achieved D2D rate and the interference to cellular users. In this paper, we consider the D2D power allocation optimization over multiple resource blocks (RBs), aimed at maximizing either the ergodic D2D rate or the ergodic sum rate of D2D and cellular users, under the long-term sum-power constraint of the D2D users and per-RB probabilistic signal-to-interference-and-noise (SINR) requirements for all cellular users. We formulate stochastic optimization problems for D2D power allocation over time. The proposed optimization framework is applicable to both uplink and downlink cellular spectrum sharing. To solve the proposed stochastic optimization problems, we first convexify the problems by introducing a family of convex constraints as a replacement for the non-convex probabilistic SINR constraints. We then present two dynamic power allocation algorithms: a Lagrange dual-based algorithm that is optimal but with a high computational complexity and a low-complexity heuristic algorithm based on dynamic time averaging. Through simulation, we show that the performance gap between the optimal and heuristic algorithms is small, and the effective long-term stochastic D2D power optimization over the shared RBs can lead to substantial gains in the ergodic D2D rate and the ergodic sum rate.

Joint Power Optimization for Device-to-Device Communication in Cellular Networks With Interference Control

For device-to-device (D2D) communication under laid in a cellular network with uplink resource sharing, both cellular and D2D pairs may cause significant inter-cell interference (ICI) at a neighboring base station (BS). In this paper, under optimal BS receive beamforming, we jointly optimize the power of a cellular user (CU) and a D2D pair for their sum rate maximization, while satisfying minimum SINR requirements and worst-case ICI limit in multiple neighboring cells. We solve this non-convex joint optimization problem in two steps. First, the necessary and sufficient condition for the D2D admissibility under given constraints is obtained. Finally, we consider joint power control of the CU and D2D transmitters. We propose a power control algorithm to maximize the sum rate. Depending on the severity of ICI that D2D and CU may cause, we categorize the feasible solution region into five cases, each of which may further include several scenarios based on minimum SINR requirements. The proposed algorithm is optimal when ICI to a single neighboring cell is considered. For multiple neighboring cells, we provide an upper bound on the performance loss by the proposed algorithm and conditions for its optimality. We further extend our consideration to the scenario of multiple CUs and D2D pairs, and formulate the joint power control and CU-D2D matching problem. We show how our proposed solution for one CU and one D2D pair can be utilized to solve this general joint optimization problem. Simulation demonstrates the effectiveness of our power control algorithm and the nearly optimal performance of the proposed approach in the setting of multiple CUs and D2D pairs.

Per-Relay Power Minimization for Multi-user Multi-channel Cooperative Relay Beamforming

We investigate the optimal relay beamforming problem for multi-user peer-to-peer communication with amplify-and-forward relaying in a multi-channel system. Assuming each source-destination (S-D) pair is assigned an orthogonal channel, we formulate the problem as a min-max per-relay power minimization problem with minimum signal-to-noise (SNR) guarantees. After showing that strong Lagrange duality holds for this nonconvex problem, we transform its Lagrange dual problem to a semi-definite programming problem and obtain the optimal relay beamforming vectors. We identify that the optimal solution can be obtained in three cases, depending on the values of the optimal dual variables. These cases correspond to whether the minimum SNR requirement at each S-D pair is met with equality, and whether the power consumption at a relay is the maximum among relays at optimality. We obtain a semi-closed form solution structure of relay beam vectors, and propose an iterative approach to determine relay beam vector for each S-D pair. We further show that the reverse problem of maximizing the minimum SNR with per-relay power budgets can be solved using our proposed algorithm with an iterative bisection search. Through simulation, we analyze the effect of various system parameters on the performance of the optimal solution. Furthermore, we investigated the effect of imperfect channel side information of the second hop on the performance and quantify the performance loss due to either channel estimation error or limited feedback.