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13
A unified analysis of maxmin weighted SINR for MIMO downlink system
 IEEE Trans. Signal Process
, 2011
"... Abstract—This paper studies the maxmin weighted signaltointerferenceplusnoise ratio (SINR) problem in the multipleinputmultipleoutput (MIMO) downlink, where multiple users are weighted according to priority and are subject to a weightedsumpower constraint. First, we study the multiplein ..."
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Abstract—This paper studies the maxmin weighted signaltointerferenceplusnoise ratio (SINR) problem in the multipleinputmultipleoutput (MIMO) downlink, where multiple users are weighted according to priority and are subject to a weightedsumpower constraint. First, we study the multipleinputsingleoutput (MISO) and singleinputmultipleoutput (SIMO) problems using nonlinear Perron–Frobenius theory. As a byproduct, we solve the open problem of convergence for a previously proposed MISO algorithm by Wiesel, Eldar, and Shamai in 2006. Furthermore, we unify our analysis with respect to the previous alternate optimization algorithm proposed by Tan, Chiang, and Srikant in 2009, by showing that our MISO result can, in fact, be derived from their algorithm. Next, we combine our MISO and SIMO results into an algorithm for the MIMO problem. We show that our proposed algorithm is optimal when the channels are rankone, or when the network is operating in the low signaltonoise ratio (SNR) region. Finally, we prove the parametric continuity of the MIMO problem in the power constraint, and we use this insight to propose a heuristic initialization strategy for improving the performance of our (generally) suboptimal MIMO algorithm. The proposed initialization strategy exhibits improved performance over random initialization. Index Terms—Beamforming, multipleinput–multipleoutput (MIMO), uplink–downlink duality.
Maximizing Sum Rates in Cognitive Radio Networks: Convex Relaxation and Global Optimization Algorithms
"... Abstract—A key challenge in wireless cognitive radio networks is to maximize the total throughput also known as the sum rates of all the users while avoiding the interference of unlicensed band secondary users from overwhelming the licensed band primary users. We study the weighted sum rate maximiza ..."
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Cited by 6 (3 self)
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Abstract—A key challenge in wireless cognitive radio networks is to maximize the total throughput also known as the sum rates of all the users while avoiding the interference of unlicensed band secondary users from overwhelming the licensed band primary users. We study the weighted sum rate maximization problem with both power budget and interference temperature constraints in a cognitive radio network. This problem is nonconvex and generally hard to solve. We propose a reformulationrelaxation technique that leverages nonnegative matrix theory to first obtain a relaxed problem with nonnegative matrix spectral radius constraints. A useful upper bound on the sum rates is then obtained by solving a convex optimization problem over a closed bounded convex set. It also enables the sumrate optimality to be quantified analytically through the spectrum of speciallycrafted nonnegative matrices. Furthermore, we obtain polynomialtime verifiable sufficient conditions that can identify polynomialtime solvable problem instances, which can be solved by a fixedpoint algorithm. As a byproduct, an interesting optimality equivalence between the nonconvex sum rate problem and the convex maxmin rate problem is established. In the general case, we propose a global optimization algorithm by utilizing our convex relaxation and branchandbound to compute an optimal solution. Our technique exploits the nonnegativity of the physical quantities, e.g., channel parameters, powers and rates, that enables key tools in nonnegative matrix theory such as the (linear and nonlinear) PerronFrobenius theorem, quasiinvertibility, FriedlandKarlin inequalities to be employed naturally. Numerical results are presented to show that our proposed algorithms are theoretically sound and have relatively fast convergence time even for largescale problems. Index Terms—Optimization, convex relaxation, cognitive radio networks, nonnegative matrix theory. I.
Routing, Scheduling and Power Allocation in Generic OFDMA Wireless Networks: Optimal Design and Efficiently Computable Bounds
"... Abstract—The goal of this paper is to determine the data routes, subchannel schedules, and power allocations that maximize a weightedsum rate of the data communicated over a generic OFDMA wireless network in which the nodes are capable of simultaneously transmitting, receiving and relaying data. T ..."
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Abstract—The goal of this paper is to determine the data routes, subchannel schedules, and power allocations that maximize a weightedsum rate of the data communicated over a generic OFDMA wireless network in which the nodes are capable of simultaneously transmitting, receiving and relaying data. Two instances are considered. In the first instance, subchannels are allowed to be timeshared by multiple links, whereas in the second instance, each subchannel is exclusively used by one of the links. Using a change of variables, the first problem is transformed into a convex form. In contrast, the second problem is not amenable to such a transformation and results in a complex mixed integer optimization problem. To develop insight into this problem, we utilize the first instance to obtain efficiently computable lower and upper bounds on the weightedsum rate that can be achieved in the absence of timesharing. Another lower bound is obtained by enforcing the scheduling constraints through additional power constraints and a monomial approximation technique to formulate the design problem as a geometric program. Numerical investigations show that the obtained rates are higher when timesharing is allowed, and that the lower bounds on rates in the absence of timesharing are relatively tight. Index Terms—Crosslayer design, geometric programming, monomial approximation, timesharing, selfconcordance. I.
Power control for cellular communications with channel uncertainties,” in
 Proc. Am. Control Conf., St.
, 2009
"... ABSTRACT Power control in a codedivision multiple access (CDMA) based cellular network is a challenging problem because the communication channels change rapidly because of multipath fading. These rapid fluctuations cause detrimental effects on the control efforts required to regulate the signalt ..."
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ABSTRACT Power control in a codedivision multiple access (CDMA) based cellular network is a challenging problem because the communication channels change rapidly because of multipath fading. These rapid fluctuations cause detrimental effects on the control efforts required to regulate the signaltointerference plus noise ratios (SINRs) to the desired level. Thus, there is a need for powercontrol algorithms that can adapt to rapid changes in the channel gain caused by multipath fading. Much of the previous work has either neglected the effects of fast fading, assumed that the fading is known, or assumed that all the link gains are known. In this paper, we model the effects of fast fading and develop practical strategies for robust power control based on SINR measurements in the presence of the fading. We develop a controller for the reverse link of a CDMA cellular system, and use a Lyapunovbased analysis to prove that the SINR error is globally uniformly ultimately bounded. We also utilize a linear prediction filter that utilizes local SINR measurements and estimates of the Doppler frequency that can be derived from local SINR measurements to improve the estimate of the channel fading used in the controller. The powercontrol algorithm is simulated for a cellular network with multiple cells, and the results indicate that the controller regulates the SINRs of all the mobile terminals (MTs) with low outage probability. In addition, a pulsecodemodulation technique is applied to allow the control command to be quantized for feedback to the transmitter. Simulation results indicate that the outage probabilities of all the MTs are still within the acceptable range if at least 3bit quantization is employed. Comparisons to a standard algorithm illustrate the improved performance of the predictive controller.
Slow Admission and Power Control for Small Cell Networks via Distributed Optimization
"... Abstract—Although small cell networks are environmentally friendly and can potentially improve the coverage and capacity of cellular layers, it is imperative to control the interference in such networks before overlaying them in a macrocell network on a largescale basis. In recent work, we develope ..."
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Abstract—Although small cell networks are environmentally friendly and can potentially improve the coverage and capacity of cellular layers, it is imperative to control the interference in such networks before overlaying them in a macrocell network on a largescale basis. In recent work, we developed the joint admission and power control algorithm for twotier small cell networks in which the number of small cell users that can be admitted at their qualityofservice (QoS) constraints is maximized without violating the macrocell users ’ QoS constraints. The QoS metric adopted is outage probability. In this paper, we investigate the distributed implementation of the joint admission and power control problem where the small cells can determine jointly their admissibility and transmit powers autonomously. I.
EnergyInfeasibility Tradeoff in Cognitive Radio Networks: PriceDriven Spectrum Access Algorithms
"... Abstract—We study the feasibility of the total power minimization problem subject to power budget and SignaltoInterferenceplusNoise Ratio (SINR) constraints in cognitive radio networks. As both the primary and the secondary users are allowed to transmit simultaneously on a shared spectrum, unco ..."
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Abstract—We study the feasibility of the total power minimization problem subject to power budget and SignaltoInterferenceplusNoise Ratio (SINR) constraints in cognitive radio networks. As both the primary and the secondary users are allowed to transmit simultaneously on a shared spectrum, uncontrolled access of secondary users degrades the performance of primary users and can even lead to system infeasibility. To find the largest feasible set of secondary users (i.e., the system capacity) that can be supported in the network, we formulate a vectorcardinality optimization problem. This nonconvex problem is however hard to solve, and we propose a convex relaxation heuristic based on the sumofinfeasibilities in optimization theory. Our methodology leads to the notion of admission price for spectrum access that can characterize the tradeoff between the total energy consumption and the system capacity. Pricedriven algorithms for joint power and admission control are then proposed that quantify the benefits of energyinfeasibility balance. Numerical results are presented to show that our algorithms are theoretically sound and practically implementable. Index Terms—Optimization, cognitive radio networks, spectrum access control, power and admission control. I.
Wireless Network Optimization by PerronFrobenius Theory
"... Abstract—A basic question in wireless networking is how to optimize the wireless network resource allocation for utility maximization and interference management. In this paper, we present an overview of a PerronFrobenius theoretic framework to overcome the notorious nonconvexity barriers in wirel ..."
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Abstract—A basic question in wireless networking is how to optimize the wireless network resource allocation for utility maximization and interference management. In this paper, we present an overview of a PerronFrobenius theoretic framework to overcome the notorious nonconvexity barriers in wireless utility maximization problems. Through this approach, the optimal value and solution of the optimization problems can be analytically characterized by the spectral property of matrices induced by nonlinear positive mappings. It also provides a systematic way to derive distributed and fastconvergent algorithms and to evaluate the fairness of resource allocation. This approach can even solve several previously open problems in the wireless networking literature, e.g., Kandukuri and Boyd (TWC 2002), Wiesel, Eldar and Shamai (TSP 2006), Krishnan and Luss (WCNC 2011). More generally, this approach links fundamental results in nonnegative matrix theory and (linear and nonlinear) PerronFrobenius theory with the solvability of nonconvex problems. In particular, for seemingly nonconvex problems, e.g., maxmin wireless fairness problems, it can solve them optimally; for truly nonconvex problems, e.g., sum rate maximization, it can even be used to identify polynomialtime solvable special cases or to enable convex relaxation for global optimization. To highlight the key aspects, we also present a short survey of our recent efforts in developing the nonlinear PerronFrobenius theoretic framework to solve wireless network optimization problems with applications in MIMO wireless cellular, heterogeneous smallcell and cognitive radio networks. Key implications arising from these work along with several open issues are discussed.
1Economics of Femtocell Service Provision
"... Abstract—Femtocells can effectively resolve the poor connectivity issue of indoor cellular users. This paper investigates the economic incentive for a cellular operator to add femtocell service on top of its existing macrocell service. We model the interactions between a cellular operator and users ..."
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Abstract—Femtocells can effectively resolve the poor connectivity issue of indoor cellular users. This paper investigates the economic incentive for a cellular operator to add femtocell service on top of its existing macrocell service. We model the interactions between a cellular operator and users as a Stackelberg game: the operator first determines spectrum allocations and pricings of femtocell and macrocell services, and then heterogeneous users choose between the two services and the amount of resource to request. In the ideal case where the femtocell service has the same full spatial coverage as the macrocell service, we show that the operator will choose to provide femtocell service only, as this leads to a better user Quality of Service and a higher operator profit. However, if we impose the constraint that no users ’ payoffs decrease after introducing the femtocell service, then the operator will always continue providing the macrocell service (with or without the femtocell service). Furthermore, we study the impact of operational cost, limited coverage, and spatial reuse on femtocell service provision. As the operational cost increases, fewer users are served by femtocell service and the operator’s profit decreases. When the femtocell service has limited spatial coverage, the operator always provides the macrocell service beside the femtocell service. However, when the coverage is high or the total resource is low, the operator will set the prices such that all users who can access femtocell will choose to use the femtocell service only. Finally, spatial reuse of spectrum will increase the efficiency of femtocell services, and gives the operator more incentives to allocate spectrum to femtocells.
DYNAMIC POWER TUNING FOR DOWNLINK INTERFERENCE MITIGATION IN HETEROGENEOUS LTE NETWORK
"... ABSTRACT Heterogeneous Long Term Evolution (LTE) network comprising femtocells leads to crosstier interference that arises between macrocells and femtocells in both uplink and downlink degrading the performance of the cellular system. The downlink interference from the femtocell to Macro User Equi ..."
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ABSTRACT Heterogeneous Long Term Evolution (LTE) network comprising femtocells leads to crosstier interference that arises between macrocells and femtocells in both uplink and downlink degrading the performance of the cellular system. The downlink interference from the femtocell to Macro User Equipments (MUE) being the most serious interference case is focused in this work. A power tuning technique has been proposed to mitigate this interference taking into consideration the number of User Equipments present in the interfering femtocells along with the information received from the interfered MUE. Simulation results show that this scheme mitigates the interference to the MUE effectively while the total transmission power of femtocells also reduce in the process of interference mitigation which is an added benefit obtained effortlessly in the dense deployment of femtocells.
Link Energy Minimization in IRUWB Based . . .
 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, ACCEPTED FOR PUBLICATION
, 2010
"... Impulse Radio Ultra WideBand (IRUWB) communication has proven to be an important technique for supporting highrate, shortrange, and lowpower communication. In this paper, using detailed models of typical IRUWB transmitter and receiver structures, we model the energy consumption per information ..."
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Impulse Radio Ultra WideBand (IRUWB) communication has proven to be an important technique for supporting highrate, shortrange, and lowpower communication. In this paper, using detailed models of typical IRUWB transmitter and receiver structures, we model the energy consumption per information bit in a single link of an IRUWB system, considering packet overhead, retransmissions, and a Nakagamim fading channel. Using this model, we minimize the energy consumption per information bit by finding the optimum packet length and the optimum number of RAKE fingers at the receiver for different transmission distances, using Differential Phaseshift keying (DBPSK), Differential Pulseposition Modulation (DPPM) and Onoff Keying (OOK), with coherent and noncoherent detection. Symbol repetition schemes with hard decision (HD) combining and soft decision (SD) combining are also compared in this paper. Our results show that at very short distances, it is optimum to use large packets, OOK with noncoherent detection, and HD combining, while at longer distances, it is optimum to use small packets, DBPSK with coherent detection, and SD combining. The optimum number of RAKE fingers are also found for given transmission schemes.