On the joint impact of bias and power control on downlink spectral efficiency in cellular networks
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Cell biasing and downlink transmit power are two controls that may be used to improve the spectral efficiency of cellular networks. With cell biasing, each mobile user associates with the base station offering, say, the highest biased signal to interference plus noise ratio. Biasing affects the cell association decisions of mobile users, but not the received instantaneous downlink transmission rates. Adjusting the collection of downlink transmission powers can likewise affect the cell associations, but in contrast with biasing, it also directly affects the instantaneous rates. This paper investigates the joint use of both cell biasing and transmission power control and their (individual and joint) effects on the statistical properties of the collection of per-user spectral efficiencies. Our analytical results and numerical investigations demonstrate in some cases a significant performance improvement in the Pareto efficient frontiers of both a mean-variance and throughput-fairness tradeoff from using both bias and power controls over using either control alone.Keywords:
Biasing
Spectral Efficiency
Transmitter power output
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In this paper, we propose an antenna selection method in a wireless cognitive radio (CR) system, namely difference selection, whereby a single transmit antenna is selected at the secondary transmitter out of $M$ possible antennas such that the weighted difference between the channel gains of the data link and the interference link is maximized. We analyze mutual information and outage probability of the secondary transmission in a CR system with difference antenna selection, and propose a method of optimizing these performance metrics of the secondary data link subject to practical constraints on the peak secondary transmit power and the average interference power as seen by the primary receiver. The optimization is performed over two parameters: the peak secondary transmit power and the difference selection weight $\delta\in [0, 1]$. We show that, difference selection using the optimized parameters determined by the proposed method can be, in many cases of interest, superior to a so called ratio selection method disclosed in the literature, although ratio selection has been shown to be optimal, when impractically, the secondary transmission power constraint is not applied. We address the effects that the constraints have on mutual information and outage probability, and discuss the practical implications of the results.
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In the last decade, there has been an explosive increase in the demand for wireless network data traffic. To deal with such monumental consumer requirement for information communications, several notable technologies have been proposed, such as small cell networks (SCNs), device-to-device (D2D) communications.
In the first half of the thesis, we address the critical issue of interference management in the D2D enhanced cellular network. To reduce the severe interference caused by active D2D links, we consider a mode selection scheme based on the maximum received signal strength (MRSS) for each user equipment (UE) to control the D2D-to-cellular interference. This will mitigate the overlarge interference from the D2D links to the cellular links. Moreover, to improve the capacity of D2D-enhanced networks, we consider that the typical user is no longer a random user which is selected by a round-robin (RR) scheduler, as assumed in most studies in the literature. Instead, a cellular user with the maximum proportional fair (PF) metric is chosen by its serving BS as the typical user, which is referred to as the PF scheduler in the cellular tier. Furthermore, we quantify the performance gains brought by D2D communications in cellular networks and we find an optimum mode selection threshold to maximize the total area spectrum efficiency (ASE) in the network.
In the second half of the thesis, we adjust the antenna pattern to boost the area spectral efficiency (ASE) of cellular networks when considering the height of the base stations. Very recent studies have shown that the area spectral efficiency of downlink (DL) cellular networks will continuously decrease and finally crash to zero as the base station (BS) density increases towards infinity if the absolute height difference between BS antenna and user equipment (UE) antenna is larger than zero. Such a phenomenon is referred to as the ASE Crash. We revisit this issue by considering optimizing the BS antenna downtilt in cellular networks. We investigated the relationship between the BS antenna downtilt and the downlink network performance in terms of the coverage probability and the ASE. Our results reveal a notable conclusion that there exists an optimal antenna downtilt to achieve the maximum coverage probability for each BS density. After applying the optimal antenna downtilt, the network performance can be significantly improved, and hence the ASE crash can be delayed by nearly one order of magnitude in terms of the BS density.
Stochastic geometry
Spectral Efficiency
Cellular communication
Performance metric
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In cognitive radio networks, a secondary user (SU) can share the same frequency band with the primary user (PU) as long as the interference introduced to the later is below a predefined threshold. In this paper, the transmission performance in cognitive radio networks is studied assuming imperfect channel estimation, and taking quality of service ( QoS ) constraints into consideration. It is assumed that the cognitive transmitter can perform channel estimation and send the data at two different rates and power levels depending on the activity of the primary users. The existence of the primary user can be detected by channel sensing. A two-state Markov chain process is used to model the existence of the primary users. The cognitive transmission is also configured as a state transition model depending on whether the rates are higher or lower than the instantaneous rates values. This paper studies the maximum capacity of the cognitive user under the delay constraint. We use the new metric concept of effective capacity of the channel and introduce an optimization problem for rate and power allocation under interference power constraints. An numerical example illustrates the average effective capacity optimization and the impact of other system parameters.
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By separately transmitting data and control signals from different tiers, dual connectivity (DC) delivers a potential solution to the handover and load balancing challenges brought by small cell deployment. In this paper, a tractable framework is developed for the downlink performance analysis of DC assisted heterogeneous cellular networks (HetNets). Based on a stochastic geometry model, accurate expressions of data-control joint coverage probability and average rate for a typical DC capable UE are derived and investigated under DC mode and single connectivity (SC) mode. It is observed that operating parameters like cell association bias and transmit power will change the optimum node density ratio to reach the maximum coverage probability and average rate, but they have little impact on the levels of maximum coverage and rate performance. Numerical results also reveal that better coverage and rate performance can be expected in scenarios with higher small cell path loss exponent.
Stochastic geometry
Coverage probability
Transmitter power output
Outage Probability
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This paper provides the signal-to-interference-plus-noise ratio (SINR) complimentary cumulative distribution function (CCDF) and average data rate of the normalized SNR-based scheduling in an uplink cellular network using stochastic geometry. The uplink analysis is essentially different from the downlink analysis in that the per-user transmit power control is performed and that the interferers are composed of at most one transmitting user in each cell other than the target cell. In addition, as the effect of multi-user diversity varies from cell to cell depending on the number of users involved in the scheduling, the distribution of the number of users is required to obtain the averaged performance of the scheduling. This paper derives the SINR CCDF relative to the typical scheduled user by focusing on two incompatible cases, where the scheduler selects a user from all the users in the corresponding Voronoi cell or does not select users near cell edges. In each case, the SINR CCDF is marginalized over the distribution of the number of users involved in the scheduling, which is asymptotically correct if the BS density is sufficiently large or small. Through the simulations, the accuracies of the analytical results are validated for both cases, and the scheduling gains are evaluated to confirm the multi-user diversity gain.
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Multicell Joint Processing has emerged as a new paradigm of cooperative communications, which aims at pushing the capacity limits of cellular systems by eliminating inter-cell interference. Its operation is based on the concept of Base Station cooperation, which is enabled through wideband error-free low-latency links to a central signal processor. This processor is responsible for jointly encoding or decoding the signals, which are transmitted to or received from the User Terminals of the cellular system. The rationale behind this cooperation is that spatially distributed Base Stations are able to act as multiple antennas of a single universal transceiver, which servers the entire cellular system. In this context, the objective is to determine the capacity performance of a multicell joint processing system under the limitations imposed by a practical cellular channel. Towards this end, a comprehensive cellular channel model is proposed, which accommodates continuous path loss functions, distributed User Terminals, multiple antennas and correlated flat fading. Focusing on the uplink channel, the per-cell sum-rate capacity is determined using asymptotic analysis and the derived closed-forms are verified through Monte Carlo simulations. The core of the analysis is based on free probability and random matrix theory, which provide the mathematical tools for studying the asymptotic eigenvalue distribution of the channel matrix. Based on this setting, it is observed that multicell processing effectively removes the interference-limited behavior of conventional cellular systems, since increasing the system power always results in higher capacity. The exact sum-rate capacity depends on the total received power across the system, which is determined by the user distribution, the cell density and the path loss. Including multiple antennas at the Base Stations results in a linear capacity scaling, whereas multiple antennas at the User Terminals do not provide a capacity enhancement. Similarly, antenna correlation at the Base Station side degrades the capacity, while correlation at the User Terminal has no effect. Furthermore, the distribution of the sum-rate capacity across individual User Terminal rates is investigated in terms of fairness. It is observed that by first decoding strong-channel User Terminals, rate fairness is promoted, but equal rate sharing can only be achieved by employing power control in parallel with heuristic user ordering. Focusing on the downlink channel, the per-cell sum-rate capacity is evaluated using duality principles and the individual user rates are calculated considering channel-dependent and random encoding orders. More specifically, three types of power allocations are considered: a) optimal power allocation with system power constraint as an upper bound, b) optimal power allocation with the more appropriate per-cell power constraint and c) uniform power allocation in the dual uplink domain. In this context, it is shown that the upper bound calculated considering a system power constraint is tight for the considered range of cellular parameters and it can be utilized to closely estimate the realistic downlink capacity of a per-cell power constrained system. Furthermore, the downlink user rate vectors are greatly affected by the employed encoding order. More specifically, by considering a user ordering which favours the deep-fade User Terminals, the fairness over the downlink rates can be promoted, while uniform power allocation favours user rate fairness on the expense of the sum-rate capacity.
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Cellular CDMA systems are usually affected by interference experienced by users in adjacent cells that decrease the Quality of Services in wireless communication network. Hence, interference is the limiting factor of capacity in CDMA cellular and it is one of the problems fighting against the high efficiency of any mobile network. In this paper, a mathematical model to estimate the average number of users contributing in inter-cell interference at the busy hours of CDMA network is proposed. As the power exponent value has significant affect on interferer signal attenuation and hence other-cells interference, measurements were carried through a drive test to determine the received power level at various distance from CDMA base stations at Baghdad. The results obtained show that the power exponent was 2.71. This value was applied in dual-slop path loss model to determine the expected interference factor, and the number of users that can be hold at each cell. Simulations showed that users at a boundary cell generate more interference than those close to the base station. Furthermore, it was denoted that greater number of users caused to increase the interference factor, and greater power exponent value result in interference factor reduction.
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To reduce energy consumption, a device in a long range wide area network (LoRaWAN) needs to adjust its transmit power according to the distance from its tagged gateway. It is important to measure the performance of the LoRaWANs uplink with power control. In this article, we focus on the analysis of the coverage probability and the meta distribution of the signal-to-interference ratio (SIR) for a LoRaWAN uplink with fractional power control (FPC). The LoRaWAN uplink is analyzed based on the Poisson point process. We present the possible reductions in transmit power of devices whilst ensuring that the received signal power is greater than the receiver sensitivity. We derive the coverage probability of a LoRaWAN uplink and show how power control influences it. Finally, utilizing the meta distribution of SIR, the fine-grained information of the LoRaWAN is revealed. The results show that the power control greatly increases the successful probability of edge-devices with little effect on the probability of inner-devices if an appropriate FPC coefficient is chosen. This is because the LoRa signal can be demodulated at a very low required SIR threshold.
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In this paper we analyze the problem of optimizing the switching levels of adaptive modulation for a two-user system under constant power condition, in order to maximize the overall system throughput for a target average bit-error-rate (BER) for each user. Since the optimal switching levels depend on the probability density of the signal-to-interference-noise ratio (SINR), expression for this probability density is derived and the optimal switch levels are obtained through a Lagrange optimization technique. This approach can be readily extended to multiple-user case. It is shown by simulation that the proposed jointly optimizing method achieves the average BER target for each user while an individually optimizing method fails. The efiects of these two methods and of the interference coe-cients on the average system throughput are also analyzed. DOI: 10.2529/PIERS061113041157 Wireless communication channels typically exhibit channel quality ∞uctuations, and to mitigate their detrimental efiects a number of approaches have been proposed in the literature. Methods based on adaptive modulation according to the near-instantaneous channel quality information have gained popularity. For Rayleigh fading channel, Chung and Goldsmith (1) showed that variable power variable-rate schemes are optimal, but they also found that the extra throughput achieved by the additional variable power assisted adaptation over the constant power variable rate schemes is marginal for most types of fading channels. Constant power variable rate adaptive scheme is also analyzed by Choi and Hanzo (2), where the target average BER forms the constraint condition. They established the relationship among the optimal mode switching levels, and found that although such relationship holds regardless of the underlying channel scenarios, the switching levels do depend on the statistics of the channel quality. The above studies were focused on single user scenario. Yet in wireless communication, a user typically sufiers from the interference of other users, which in the GSM system may be due to multipath channel conditions, and in the CDMA system may stem from the loss of orthogonality among the spread sequences. Several approaches have been proposed based on power control and base station selection (3,4), with little consideration for adaptive modulation. In (5) Qiu and Chawla approached the multiuser problem by using power control and adaptive modulation. They showed that adaptive modulation without power control scheme outperforms SINR-balance power control scheme in terms of overall throughput, a flnding that indicates the signiflcance of constant power adaptive modulation for multiuser system. In their approach, the switching levels were obtained by using the method due to Webb and Steele, and a parametric approximation for throughput for all modulation modes was also adopted. In this paper we propose a constant-power adaptive modulation scheme for downlink trans- mission in a multiuser system. It is based on a Lagrangian optimization technique. We consider two-user case here to highlight the concept. Extension to multiuser case can be readily carried out. The downlink transmission model is shown in Fig. 1, which is similar to the one used in (6). The received signals are for user 1
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In cellular networks, each mobile station adjusts its power level under control of its base station, i.e., through uplink transmit power control, which is essential to reach desired signal-to-interference-plus-noise ratio (SINR) at the base station and to limit inter-cell interference. The optimal levels of transmit power in a network depend on path loss, shadowing, and multipath fading, as well as the network configuration. However, since path loss is distance dependent and the cell association distances are correlated due to the cell association policies, the performance analysis of the uplink transmit power control is very complicated. Consequently, the impact of a specific power control algorithm on network performance is hard to quantify. In this paper, we analyze three uplink transmit power control schemes. We assume the standard power-law path loss and composite Rayleigh-lognormal fading. Using stochastic geometry tools, we derive the cumulative distribution function and the probability density function of the uplink transmit power and the resulting network coverage probability. It is shown that the coverage is highly dependent on the severity of shadowing, the power control scheme, and its parameters, but invariant of the density of deployment of base stations when the shadowing is mild and power control is fractional. At low SINRs, compensation of both path loss and shadowing improves the coverage. However, at high SINRs, compensating for path loss only improves coverage. Increase in the severity of shadowing significantly reduces the coverage.
Transmitter power output
Stochastic geometry
Coverage probability
Signal-to-interference-plus-noise ratio
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