Showing papers by "Matti Latva-aho published in 2012"

Weighted Sum-Rate Maximization in Wireless Networks: A Review

Abstract: The weighted sum-rate maximization (WSRMax) problem plays a central role in many network control and optimization methods, such as power control, link scheduling, cross-layer control, network utility maximization. The problem is NP-hard in general. In Weighted Sum-Rate Maximization in Wireless Networks: A Review, a cohesive discussion of the existing solution methods associated with the WSRMax problem, including global, fast local, as well as decentralized methods is presented. In addition, general optimization approaches, such as branch and bound methods, complementary geometric programming, and decomposition methods, are discussed in depth to address the problem. Through a number of numerical examples, the applicability of the resulting algorithms in various application domains is demonstrated. The presented algorithms and the associated numerical results can be very useful for network engineers or researchers with an interest in network design.

Coordination Mechanisms for Self-Organizing Femtocells in Two-Tier Coexistence Scenarios

Abstract: We propose and investigate distributed coordination mechanisms for controlling the co-channel interference generated by standalone femtocells in two-tier coexistence scenarios consisting of macrocells underlaid with short-range small cells. The rationale behind employing such mechanism is to opportunistically reuse resources without compromising ongoing transmissions on overlaid macrocells, while still guaranteeing Quality of Service in both tiers. Stochastic geometry is used to model network deployments, while higher-order statistics through the cumulants concept is utilized to characterize the probability distribution of the aggregate interference at the tagged receiver. To conduct our studies, we consider a shadowed fading channel model incorporating log-normal shadowing and Nakagami fading. In addition, various network algorithms, such as power control and frequency (re)allocation, are included in the analytical framework. To evaluate the performance of the proposed solutions, we also derive closed-form expressions for the outage probability and average spectral efficiency with respect to the tagged receiver. Results show that the analytical framework matches well with numerical results obtained from Monte Carlo simulations, and that the coordination mechanisms substantially improve the performance of overlaid macrocell networks, while also benefiting femtocells.

Efficiency of Wireless Networks under Different Hopping Strategies

Abstract: In this work we investigate whether it is preferable to have a large number of short single-hop links or a small number of long single-hops in a multi-hop wireless network. We derive analytical expressions to compute the metric aggregate multi-hop information efficiency under different hopping strategies, and analyze the trade-off involving robustness of single-hop links, interference and hopping strategy.

Effects of Feedback Delay in Partial Relay Selection Over Nakagami- $m$ Fading Channels

Abstract: This paper investigates the effect of feedback delay on the performance of amplify-and-forward (AF) relay selection over a Nakagami-m fading environment. Spatial diversity can be improved by employing multiple relays with selection; however, this diversity gain cannot be fully realized when the feedback delay is present in the decision metric. Hence, in this paper, we quantify this detrimental effect by deriving the exact closed-form solution to outage probability, average symbol error rate (SER), and generalized higher moments of signal-to-noise ratio (SNR) for both channel state information (CSI)-assisted and fixed-gain relay. Further, an exact closed form of the ergodic capacity for CSI-assisted relay is derived, and a tight approximation is provided for the fixed-gain relay case. To have a clear picture of the diversity gain variation, we analyze the system in high SNR and obtain simple asymptotic results. Monte Carlo simulation is used to verify the analytical work.

Optimal Transmission Capacity of Ad Hoc Networks with Packet Retransmissions

Abstract: In this paper we investigate the transmission capacity of wireless networks when packet retransmissions are allowed. We consider networks modeled as a homogeneous Poisson point process operating under different medium access control schemes, namely unslotted and slotted ALOHA, and CSMA with carrier sensing at the transmitter and with carrier sensing at the receiver. For these scenarios, we derive analytical expressions to compute the maximum number of retransmissions attempts that leads to the optimal transmission capacity. Numerical results based on our formulation show that CSMA with carrier sensing at the receiver (asynchronous transmissions) reaches the highest maximum transmission capacity when traffic intensity is low, while slotted ALOHA (synchronous transmissions) is the best choice when traffic intensity is high.

On the impact of heterogeneous backhauls on coordinated multipoint transmission in femtocell networks

Abstract: The choice of a suitable backhaul constitutes one of the main performance bottlenecks in the emerging femtocell networks. In this paper, we study the impact of adopting a heterogenous backhaul (i.e., wired or over-the-air) with realistic quality-of-service requirements on coherent coordinated multipoint (CoMP) transmission in the downlink of femtocell networks. We formulate a cooperative game with continuum among the femtocell access points (FAPs) for performing CoMP in order to maximize the downlink rate while accounting for the constraints on the heterogeneous backhaul. In this respect, we propose a distributed algorithm that enables the FAPs to jointly decide on their cooperative partners as well as the choice of a backhaul strategy. In this respect, the proposed algorithm jointly addresses the problem of coalition formation as well as the optimization of the tradeoff between OTA and wired backhaul transmission modes, each of which is limited by a different factor such as delay or spectrum resources availability. We show that the proposed algorithm converges to a stable partition which constitutes the continuum core of the studied cooperative game. Simulation results show that our proposed scheme yields interesting gains in terms of the average downlink rate per FAP, reaching up to 26% relative to the classical of non-cooperative transmissions.

Transmission strategies for full duplex multiuser MIMO systems

Abstract: We introduce a full duplex multiuser multiple-input multiple-output (FD MU-MIMO) system, and consider the total throughput maximization problem under a sum power constraint in the downlink (DL) channel and per-user power constraints in the uplink (UL) channel. Due to the nature of asymmetric DL/UL capacity, a trivial method to this problem is to optimize the DL and UL channels sequentially. However, when the self-interference (SI) is large, the sum rate of the UL channel in this sequential design is dramatically degraded. Herein, a joint design is proposed, in which the DL and UL channels are optimized simultaneously. Since the objective function of the throughput maximization problem is non-convex, it is difficult to find the optimal solution. Thus, we propose a joint iterative algorithm to find a suboptimal design, using a local optimization strategy. Simulation results demonstrate that the iterative joint design outperforms the sequential design, and the FD MU-MIMO system is superior to the conventional half duplex (HD) system in terms of the total system throughput when the SI is sufficiently small. This makes the FD MU-MIMO techniques promising for small cell deployments where the transmit power is relatively small.

Performance analysis of full duplex and selective and incremental half duplex relaying schemes

Abstract: In this work we compare full-duplex (FD) and half-duplex (HD) relaying in terms of outage probability and throughput. We consider a practical FD relay model where the loop interference between transmitted and received signals is taken into account. We analyze two modes for FD transmission, block Markov encoding and multi-hop transmission without interference cancellation, and two different modes for HD transmission, which are based on selective and incremental decode-and-forward protocols. Results show that there is a tradeoff between SNR and information rate in which each scheme becomes more suitable.

On the dynamic formation of cooperative multipoint transmissions in small cell networks

Abstract: The ever-growing data rate requirements of next-generation mobile networks mandate a highly efficient exploitation of the spectral and energy resources. In this respect, a key technology which can allow high quality-of-service provisioning with reasonable energy expenditures is given by the deployment of Coordinated Multi-point (CoMP) transmissions for small cells. While the benefits of CoMP have been explored in the literature, little has been done to study how a network can adaptively decide on whether or not to adopt CoMP. To this end, in this paper, we propose a cooperative framework for small cell networks, in which groups of small cells dynamically decide when to perform CoMP transmission while optimizing the tradeoff between rate improvement and energy consumption. We formulate the problem as a dynamic coalitional game with the small base stations as players, and we provide a distributed algorithm that allows the small cells to self-organize into CoMP-based coalitions. The resulting network partition represents the ∊-core of the game, which is a key solution concept for dynamic coalition games. Simulation results show that the proposed dynamic coalition formation algorithm leads to a significant gain of up to 41% sum rate to transmit power ratio in the small cell tier.

Energy efficient power control and beamforming in multi-antenna enabled femtocells

Abstract: Energy efficient beamforming and power control problem is considered for a MISO (multiple input single output) network. We consider an active femtocell within the coverage area of a macrocell. The femto base station is equipped with multi antennas and the users are considered to be single antenna users. A beamforming and power control problem is formulated in order to minimize the energy consumption per bit in the downlink transmission in the femtocell. The objective function is introduced as “sum power/sum rate” which has the unit J/bit to measure the energy efficiency of the network. The problem is non-convex. We introduce a novel method to solve this problem with an approximation. We show that the problem can be solved with convex optimization techniques which has more practical interest even though the solution is suboptimal. In order to measure the energy efficiency we apply an existing power model which considers the total energy consumption of a base station. Thus we expect that our solution indicates realistic energy consumption measurements. Then we introduce a beamforming and power control algorithm which minimizes the energy consumption per bit transmission. Finally, the behavior of the objective function is observed in different antenna configurations by varying the user density in different channel environments.

Energy efficient MIMO two-way relay system with physical layer network coding

Abstract: We investigate error performance and an optimum power allocation scheme for multiple-input multiple-output (MIMO) channel physical layer network coding (PNC) based two-way relay system. Zero forcing precoding technique is used at source nodes to facilitate PNC operations at the relay node. First, system error performance is investigated by introducing upper and lower bounds for BPSK modulation system. They are validated with numerical results and bounds provide accurate results at high SNR regime. Then, we consider sum rate maximization under a total power constraint to obtain the optimum power allocation scheme. Analytical solutions are derived and compared with other possible schemes, which are suboptimal. Numerical results confirm that the power allocation scheme provides the optimal solution for the achievable sum rate with the total available power and the relay position.

Enabling relaying over heterogeneous backhauls in the uplink of femtocell networks

Abstract: In this paper, we develop novel two-tier interference management strategies that enable macrocell users (MUEs) to improve their performance, with the help of open-access femtocells. To this end, we propose a rate-splitting technique using which the MUEs optimize their uplink transmissions by dividing their signals into two types: a coarse message that is intended for direct transmission to the macrocell base station and a fine message that is decoded by a neighboring femtocell and subsequently relayed over a heterogeneous (wireless/wired) backhaul. For deploying the proposed technique, we formulate a non-cooperative game between the MUEs in which each MUE can decide on its relaying femtocell while maximizing a utility function that captures both the achieved throughput and the expected backhaul delay. Simulation results show that the proposed approach yields up to 125% rate improvement and up to 2 times delay reduction with wired backhaul and, 150% rate improvement and up to 10 times delay reduction with wireless backhaul, relative to classical interference management approaches, with no cross-tier cooperation.

Joint pre-coder and decoder design for physical layer network coding based MIMO two-way relay system

Abstract: We investigate a joint precoder decoder design scheme for multiple-input multiple-output (MIMO) channel physical layer network coding (PNC) based two-way relay system. Precoders at source nodes and decoder at relay node are designed to facilitate PNC operations at the relay node. We consider minimizing the weighted mean square error (MSE) at relay node to enhance the accuracy of the PNC. Formulated optimization problem is non-convex and we propose an algorithm to solve it optimally. Numerical results confirm that the joint precoder decoder algorithm provides the optimal solution to minimizing weighted MSE with the total available power. Effect of weighting parameters, relay location and number of antennas at nodes are considered in the system analysis.

Enhanced performance of heterogeneous networks through full-duplex relaying

Abstract: In this article, we focus on the uplink of a heterogeneous network composed of a macrocell and an underlaid femtocell. We address the problem of the interference caused by the macro user (MU) on the femtocell [femto base station (FBS) and users]. The femtocell is composed of an user, a femto relay, which can be seen as another FBS or a dedicated relay, and an FBS. We assume a full-duplex relay (FDR) node which is able to transmit and receive simultaneously while suffering from residual self-interference. We focus on the performance of the femtocell according to different positions of the MU user. We derive closed-form expressions for the outage probability and spectral efficiency (throughput) taking into account the self-interference of the FDR node. Moreover, we assume that the nodes are able to apply successive interference cancellation on the MU signal. Our results show that FDR can considerably enhance the performance of the femtocell, even in the presence of strong self-interference at the FDR, allowing the femtocell to operate in a high rate regime.

Spatial capacity of ad hoc wireless networks with Poisson distributed nodes

Abstract: This paper introduces a novel approach to evaluate the performance of ad hoc networks based on their spatial capacity, defined as the maximum spatial spectral efficiency supported by the network while a zero outage probability is guaranteed for all communication links. Specifically, the spatial capacity together with upper and lower bounds is derived in closed-form for networks where transmitters follow a Poisson point process and their respective receivers are located at a fixed distance. In this scenario, the spatial capacity is achieved using a rate adaptation technique that adjusts the link spectral efficiency in accordance with the distance between the receivers and their closest interferers. Besides, the spatial capacity is analytically proved to be always greater than or equal to the maximum spatial spectral efficiency achieved when a fixed spectral efficiency and an unbounded outage probability are considered. Numerical results show that the spatial-capacity-achieving setting leads to a spatial spectral efficiency about 125% higher than the one reached with the fixed spectral efficiency strategy.

Impact of antenna correlation on the performance of partial relay selection

Abstract: Antenna correlation is generally viewed as an obstacle to realize the desired performance of a wireless system. In this article, we investigate the performance of partial relay selection in the presence of antenna correlation. We consider both channel state information (csi)-assisted and fixed gain amplify-and-forward (AF) relay schemes. The source and the destination are equipped with multiple antennas communicating via the best first hop signal-to-noise ratio (SNR) relay. We derived the closed form expression for outage probability, average symbol error rate (SER) for both schemes. Further, an exact expression is derived for the ergodic capacity in the csi-assisted relay case and an approximated expression is considered for the fixed gain case. Moreover, we provide simple asymptotic results and show that the diversity order of the system remains unchanged with the effect of antenna correlation for both types of relay schemes.

Stable transmission capacity in Poisson wireless networks with delay guarantees

Abstract: In this paper, a new measure of outage-constrained network area spectral efficiency, coined as stable transmission capacity, is introduced, which is achievable under finite delay and queue-length stability. Specifically, this framework extends the transmission capacity formulation to scenarios with packet retransmissions and transmitters' queues with independent packet arrivals. This approach is applied to single-hop wireless networks with nodes being spatially distributed as Poisson point process, slotted ALOHA medium access protocol, packet arrivals following a geometrical distribution, and bounded number of retransmissions. The stable transmission capacity is then obtained as the solution of a constrained optimization problem with respect to the probability that a transmitter access the network, the link spectral efficiency, and the maximum number of retransmissions. Using the unconstrained stable transmission capacity as an upper bound, it is shown under which operating points and network parameters such limit can be achieved. Our numerical results also evince how the spatial density and the arrival process affect the network performance.

Sensor Integration to LTE/LTE-A Network through MC-CDMA and Relaying

Abstract: In this paper, we propose a method to connect a group of wireless sensors to LTE/LTE-A system by using the cellular users as mobile relays, with the basic principle of maintaining the normal traffic between the cellular users and eNodeB during the sensor data collection. The cellular spectrum is re-used on sensor-to-mobile relay link without employing additional frequency resources. Multi- carrier CDMA methods are suspected to be utilized by sensor nodes, where data of each sensor is spread to the whole re-used cellular spectrum to create a low data rate transmission. In order to avoid additional complex receiver on cellular terminals, the simple amplify-and-forward relaying scheme is used at mobile relays. Since eNodeB can observe the cellular traffic components in the re-used spectrum exactly, it has the capability of canceling them in the received overlapped signals, and detecting the sensor data by using advanced multi-user detection methods. Finally, the end-to-end outage probability is analyzed and a closed-form approximation is derived. The numerical results show that the approximate closed-form equation is significant and that the proposed scheme can be used to collect sensor data in LTE/LTE-A networks.

Enabling macrocell-femtocell coexistence through interference draining

Abstract: Underlay femtocells promise to enhance the coverage and rate performance of next-generation wireless networks. Nevertheless, many concerns still remain in the context of shared-spectrum operations and quality of service (QoS) provisioning at the macrocell users. In this paper, we introduce a novel approach for cooperative femtocell-to-femtocell interference management based on interference draining. Accordingly, a group of femtocells can decide to cooperate and improve their downlink rate, by exploiting the available frequency-spatial directions, and still guarantee a minimum target QoS at the closest MUEs. To address this problem, we use tools from cooperative game theory that enable the femtocells to decide, in a distributed manner, on whether to cooperate or not. In the proposed framework, each femtocell access point individually decides its own cooperative strategy, and maximizes a utility function that captures the cooperative gains and the limitations due to the macrocell users QoS targets. We show that, using the proposed approach, the femtocells can self-organize into a network partition composed of disjoint groups of femtocells which form the recursive core of the cooperative game. Simulation results show significant gains in terms of average payoff per femtocell, reaching up to 23%, for a network of K = 140 FBSs, relative to the non-cooperative approach.

On the fly self-organized base station placement

Abstract: In this paper, we address the deployment of base stations (BSs) in a one-dimensional network in which the users are randomly distributed. In order to take into account the users' distribution to optimally place the BSs we optimize the uplink MMSE sum rate. Moreover, given a massive number of antennas at the BSs we propose a novel random matrix theory-based technique so as to obtain tight approximations for the MMSE sum rate in the uplink. We investigate a cooperative (CP) scenario where the BSs jointly decode the messages and a non-cooperative (NCP) scheme in which the BS can only decode its own users. Our results show that the CP strategy considerably outperforms the NCP case. Moreover, we show that there exists a trade off in the BS deployment regarding the position of each BS. Thus, through location games we can optimize the position of each BS in order to maximize the system performance.

Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining

Abstract: The deployment of underlay small base stations (SBSs) is expected to significantly boost the spectrum efficiency and the coverage of next-generation cellular networks. However, the coexistence of SBSs underlaid to an existing macro-cellular network faces important challenges, notably in terms of spectrum sharing and interference management. In this paper, we propose a novel game-theoretic model that enables the SBSs to optimize their transmission rates by making decisions on the resource occupation jointly in the frequency and spatial domains. This procedure, known as interference draining, is performed among cooperative SBSs and allows to drastically reduce the interference experienced by both macro- and small cell users. At the macrocell side, we consider a modified water-filling policy for the power allocation that allows each macrocell user (MUE) to focus the transmissions on the degrees of freedom over which the MUE experiences the best channel and interference conditions. This approach not only represents an effective way to decrease the received interference at the MUEs but also grants the SBSs tier additional transmission opportunities and allows for a more agile interference management. Simulation results show that the proposed approach yields significant gains at both macrocell and small cell tiers, in terms of average achievable rate per user, reaching up to 37%, relative to the non-cooperative case, for a network with 150 MUEs and 200 SBSs.

Pragmatic multi-cell MIMO beamforming with decentralized coordination

Abstract: This paper considers a time division duplexing based coordinated multi-cell multiuser MIMO system Optimization problem is sum power minimization among base stations (BSs) with minimum SINR constraint per each user The problem is jointly non-convex with respect to transmit and receive beamformers We propose a MIMO beamforming design where transmit and receive beamformers are updated consecutively using decentralized coordination For receive beamforming, each user employs minimum mean squared error receiver which is then used as a precoder for uplink pilot signaling Due to precoded pilot signaling, local effective channel state information is available at each BS Using a primal decomposition method, originally centralized transmit beamforming optimization is decoupled between BSs and turned into a decentralized two-level optimization At each BS, a lower BS-level optimization is cast as a second order cone program and solved using standard convex optimization tools, whereas a higher network-level optimization is solved via a projected subgradient method requiring limited backhaul information exchange among BSs Alternating between receive and transmit beamforming optimization steps, algorithm converges to a locally optimal solution in a static channel scenario Numerical results show similar performance as in the centralized case Furthermore, significant performance gain over multi-cell MISO beamforming is demonstrated

Energy efficiency improvement in multi-cell networks with binary power control

Abstract: A multi-cell wireless network with full spectrum reuse is considered. The energy efficiency of the entire network is evaluated based on a predefined cost function. The energy consumption per bit (J/bit) is used as the evaluation metric. A method is proposed to improve the energy efficiency (EE) of the network employing cell coordination. The main idea is to get an insight on the EE of wireless networks and how to improve that of the network by using a binary power control mechanism. A SINR threshold is calculated based on the number of cells and channel gains of the network. Using binary power control, the users who do not obtain the required SINR are kept silent for a period of time until they get good channel conditions. It is then shown that this criterion outperforms the orthogonal resource allocation scheme and random cell switch off scheme. Finally, it is observed that the number of coordinating cells in a cluster is EE limited. Hence it can be used to determine the number of cells that should be operated inside a single cluster when binary power control is employed. The results obtained can be used as upper bounds for initial calibration of a practically implemented system.

Decentralized linear transceiver design in coordinated multi-cell multiuser MIMO systems

Abstract: This paper considers a downlink linear transmit and receive beamformer design in a coordinated multi-cell network where each multiantenna base station (BS) serves its own set of multiple antenna users. Optimization objective is to minimize sum transmission power among coordinated BSs while satisfying user specific minimum SINR targets. The problem is jointly non-convex in transmit and receive beamformers. Hence, even in a centralized case only a local optimal solution can be found by alternating optimization in which the transmit and receive beamformers are updated consecutively. The problem becomes even more complicated for a decentralized case since even if the channels from the BS to the neighboring cells' users are known, the receivers they are employing may not be. In order to obtain a decentralized implementation, each BS assumes worst case receivers for other cells' users when designing its own users' beamformers. Using this design approach, user specific SINR targets can be guaranteed using only local channel state information at each BS and some limited backhaul signaling among coordinated BSs. The proposed decentralized transceiver design algorithm is solved by repeating the following two optimization steps separately at each BS: transmit and receive beamformer optimization via alternating optimization and inter-cell interference power optimization via primal decomposition. Decentralized implementation comes at a cost of somewhat increased sum power compared to the centralized case. Numerical examples demonstrate fast convergence and significant gain over MISO system when SINR targets are low.

Effects of Feedback Delay on the Performance of Multiple Relay Network over Nakagami-m Fading Channels

Abstract: This paper studies the effect of feedback delay on the performance of amplify-and-forward (AF) relay selection over Nakagami-m fading environment. Spatial diversity can be improved by employing multiple relays with selection, however, this diversity gain cannot be fully realized when the feedback delay is present in the decision metric. Hence, we try to quantify this detrimental effect by deriving the exact closed form solution to outage probability and ergodic capacity for channel state information (CSI)-assisted relay. Further, we derive simple asymptotic results for outage to provide insight of the system performance and diversity. Monte Carlo simulation is used to verify the analytical work.