arXiv subjects

Radha Krishna Ganti

Publications and source records attributed to Radha Krishna Ganti.

At least 37 records · Page 2Linked to original sources

arXiv2017

Error Vector Magnitude Analysis in Generalized Fading with Co-Channel Interference

In this paper, we derive the data-aided Error Vector Magnitude (EVM) in an interference limited system when both the desired signal and interferers experience independent and non identically distributed $κ$-$μ$ shadowed fading. Then it is analytically shown that the EVM is equal to the square root of number of interferers when the desired signal and interferers do not experience fading. Further, EVM is derived in the presence of interference and noise, when the desired signal experiences $κ$-$μ$ shadowed fading and the interferers experience independent and identical Nakagami fading. Moreover, using the properties of the special functions, the derived EVM expressions are also simplified for various special cases.

cs.IT↗

arXiv2017

Adaptive CSMA under the SINR Model: Efficient Approximation Algorithms for Throughput and Utility Maximization

We consider a Carrier Sense Multiple Access (CSMA) based scheduling algorithm for a single-hop wireless network under a realistic Signal-to-interference-plus-noise ratio (SINR) model for the interference. We propose two local optimization based approximation algorithms to efficiently estimate certain attempt rate parameters of CSMA called fugacities. It is known that adaptive CSMA can achieve throughput optimality by sampling feasible schedules from a Gibbs distribution, with appropriate fugacities. Unfortunately, obtaining these optimal fugacities is an NP-hard problem. Further, the existing adaptive CSMA algorithms use a stochastic gradient descent based method, which usually entails an impractically slow (exponential in the size of the network) convergence to the optimal fugacities. To address this issue, we first propose an algorithm to estimate the fugacities, that can support a given set of desired service rates. The convergence rate and the complexity of this algorithm are independent of the network size, and depend only on the neighborhood size of a link. Further, we show that the proposed algorithm corresponds exactly to performing the well-known Bethe approximation to the underlying Gibbs distribution. Then, we propose another local algorithm to estimate the optimal fugacities under a utility maximization framework, and characterize its accuracy. Numerical results indicate that the proposed methods have a good degree of accuracy, and achieve extremely fast convergence to near-optimal fugacities, and often outperform the convergence rate of the stochastic gradient descent by a few orders of magnitude.

cs.IT↗

arXiv2017

Efficient CSMA using Regional Free Energy Approximations

CSMA (Carrier Sense Multiple Access) algorithms based on Gibbs sampling can achieve throughput optimality if certain parameters called the fugacities are appropriately chosen. However, the problem of computing these fugacities is NP-hard. In this work, we derive estimates of the fugacities by using a framework called the regional free energy approximations. In particular, we derive explicit expressions for approximate fugacities corresponding to any feasible service rate vector. We further prove that our approximate fugacities are exact for the class of chordal graphs. A distinguishing feature of our work is that the regional approximations that we propose are tailored to conflict graphs with small cycles, which is a typical characteristic of wireless networks. Numerical results indicate that the fugacities obtained by the proposed method are quite accurate and significantly outperform the existing Bethe approximation based techniques.

cs.NI↗

arXiv2017

Joint Backhaul-Access Analysis of Full Duplex Self-Backhauling Heterogeneous Networks

With the successful demonstration of in-band full-duplex (IBFD) transceivers, a new research dimension has been added to wireless networks. This paper proposes an interesting use case of this capability for IBFD self-backhauling heterogeneous networks (HetNet). IBFD self-backhauling in a HetNet refers to IBFD-enabled small cells backhauling themselves with macro cells over the wireless channel. Owing to their IBFD capability, the small cells simultaneously communicate over the access and backhaul links, using the same frequency band. The idea is doubly advantageous, as it obviates the need for fiber backhauling small cells every hundred meters and allows the access spectrum to be reused for backhauling at no extra cost. This work considers the case of a two-tier cellular network with IBFD-enabled small cells, wirelessly backhauling themselves with conventional macro cells. For clear exposition, the case considered is that of FDD network, where within access and backhaul links, the downlink (DL) and uplink (UL) are frequency duplexed ($f1$, $f2$ respectively), while the total frequency spectrum used at access and backhaul ($f1+f2$) is the same. Analytical expressions for coverage and average downlink (DL) rate in such a network are derived using tools from the field of stochastic geometry. It is shown that DL rate in such networks could be close to double that of a conventional TDD/FDD self-backhauling network, at the expense of reduced coverage due to higher interference in IBFD networks. For the proposed IBFD network, the conflicting aspects of increased interference on one side and high spectral efficiency on the other are captured into a mathematical model. The mathematical model introduces an end-to-end joint analysis of backhaul (or fronthaul) and access links, in contrast to the largely available access-centric studies.

cs.NI↗

arXiv2016

SIR Asymptotics in General Network Models

In the performance analyses of wireless networks, asymptotic quantities and properties often pro- vide useful results and insights. The asymptotic analyses become especially important when complete analytical expressions of the performance metrics of interest are not available, which is often the case if one departs from very specific modeling assumptions. In this paper, we consider the asymptotics of the SIR distribution in general wireless network models, including ad hoc and cellular networks, simple and non-simple point processes, and singular and bounded path loss models, for which, in most cases, finding analytical expressions of the complete SIR distribution seems hopeless. We show that the lower tails of the SIR distributions decay polynomially with the order solely determined by the path loss exponent or the fading parameter, while the upper tails decay exponentially, with the exception of cellular networks with singular path loss. In addition, we analyze the impact of the nearest interferer on the asymptotic properties of the SIR distributions, and we formulate three crisp conjectures that -if true- determine the asymptotic behavior in many cases based on the large-scale path loss properties of the desired signal and/or nearest interferer only.

cs.IT↗

arXiv2016

Maximal Packing with Interference Constraints

In this work, we study the problem of scheduling a maximal set of transmitters subjected to an interference constraint across all the nodes. Given a set of nodes, the problem reduces to finding the maximum cardinality of a subset of nodes that can concurrently transmit without violating interference constraints. The resulting packing problem is a binary optimization problem and is NP hard. We propose a semi-definite relaxation (SDR) for this problem and provide bounds on the relaxation.

cs.IT↗

arXiv2016

Coverage Analysis In Downlink Poisson Cellular Network With $κ$-$μ$ Shadowed Fading

The downlink coverage probability of a cellular network, when the base station locations are modelled by a Poisson point process (PPP), is known when the desired channel is Nakagami distributed with an integer shape parameter. However, for many interesting fading distributions such as Rician, Rician shadowing, $κ$-$μ$, $η$-$μ$, etc., the coverage probability is unknown. $κ$-$μ$ shadowed fading is a generic fading distribution whose special cases are many of these popular distributions known so far. In this letter, we derive the coverage probability when the desired channel experiences $κ$-$μ$ shadowed fading. Using numerical simulations, we verify our analytical expressions.

cs.IT↗

arXiv2016

Adaptive Modulation with Impulsive Interference

In this letter, we analyze power and rate adaptation in a point-to-point link with Rayleigh fading and impulsive interference. We model the impulsive interference as a Bernoulli-Gaussian random process. Adaptation is used to maximize the average spectral efficiency by changing power and rate of the transmission subject to an average power and instantaneous probability of error constraints. Without impulsive interference, it is well known that water-filling is optimal for block fading. We provide two simple schemes that show that the conventional water-filling algorithm is not optimal in an impulsive interference channel.

cs.IT↗

arXiv2016

A Linearization Technique for Self-Interference Cancellation in Full-Duplex Radios

The fundamental problem in the design of a full-duplex radio is the cancellation of the self-interference (SI) signal generated by the transmitter.Current techniques for suppressing SI rely on generating a copy of the SI signal and subtracting it partly in the RF (radio frequency) and digital domains. A critical step in replicating the self-interference is the estimation of the multi-path channel through which the transmitted signal propagates to the antenna. Since there is no prior model on the number of multipath reflections, current techniques assume a tap delay line filter (in the RF and digital domain) with a large number of taps, and estimate the taps in the analog and the digital domain. Assuming such a model leads to a large form-factor for the analog and RF circuits and increased complexity in the digital domain. In this paper, using a linearization technique, we show that the self-interference channel in an indoor environment can be effectively modelled as $H(f)=C_0 + C_1f$ in the frequency domain. Thus, the effective self-interference channel can be represented by two parameters $C_0$ and $C_1$, irrespective of the multipath environment. We also provide experimental evidence to verify the above channel model and propose novel low-complexity designs for self-interference cancellation. Linearization not only aids in the practicality of analog cancellation by reducing the form factor, but also results in a simpler SI filter model in the digital domain due to dimensionality reduction of the channel parameters. Therefore this method can enable the widespread adoption of full-duplex techniques to portable devices in addition to infrastructure base-stations.

cs.NI↗

arXiv2015

Performance of Cloud Radio Networks

Cloud radio networks coordinate transmission among base stations (BSs) to reduce the interference effects, particularly for the cell-edge users. In this paper, we analyze the performance of a cloud network with static clustering where geographically close BSs form a cloud network of cooperating BSs. Because, of finite cooperation, the interference in a practical cloud radio cannot be removed and in this paper, the distance based interference is taken into account in the analysis. In particular, we consider centralized zero forcing equalizer and dirty paper precoding for cancelling the interference. Bounds are developed on the signal-to-interference ratio distribution and achievable rate with full and limited channel feedback from the cluster users. The adverse effect of finite clusters on the achievable rate is quantified. We show that, the number of cooperating BSs is more crucial than the cluster area when full channel state information form the cluster is available for precoding. Also, we study the impact of limiting the channel state information on the achievable rate. We show that even with a practically feasible feedback of about five to six channel states from each user, significant gain in mean rate and cell edge rate compared to conventional cellular systems can be obtained.

cs.IT↗

arXiv2015

Approximation of Capacity for ISI Channels with One-bit Output Quantization

Motivated by recent high bandwidth communication systems, Inter-Symbol Interference (ISI) channels with 1-bit quantized output are considered under an average-power-constrained continuous input. While the exact capacity is difficult to characterize, an approximation that matches with the exact channel output up to a probability of error is provided. The approximation does not have additive noise, but constrains the channel output (without noise) to be above a threshold in absolute value. The capacity under the approximation is computed using methods involving standard Gibbs distributions. Markovian achievable schemes approaching the approximate capacity are provided. The methods used over the approximate ISI channel result in ideas for practical coding schemes for ISI channels with 1-bit output quantization.

cs.IT↗

arXiv2015

Spatial CSMA: A Distributed Scheduling Algorithm for the SIR Model with Time-varying Channels

Recent work has shown that adaptive CSMA algorithms can achieve throughput optimality. However, these adaptive CSMA algorithms assume a rather simplistic model for the wireless medium. Specifically, the interference is typically modelled by a conflict graph, and the channels are assumed to be static. In this work, we propose a distributed and adaptive CSMA algorithm under a more realistic signal-to-interference ratio (SIR) based interference model, with time-varying channels. We prove that our algorithm is throughput optimal under this generalized model. Further, we augment our proposed algorithm by using a parallel update technique. Numerical results show that our algorithm outperforms the conflict graph based algorithms, in terms of supportable throughput and the rate of convergence to steady-state.

cs.NI↗

arXiv2014

Performance of PZF and MMSE Receivers in Cellular Networks with Multi-User Spatial Multiplexing

This paper characterizes the performance of cellular networks employing multiple antenna open-loop spatial multiplexing techniques. We use a stochastic geometric framework to model distance depended inter cell interference. Using this framework, we analyze the coverage and rate using two linear receivers, namely, partial zero-forcing (PZF) and minimum-mean-square-estimation (MMSE) receivers. Analytical expressions are obtained for coverage and rate distribution that are suitable for fast numerical computation. In the case of the PZF receiver, we show that it is not optimal to utilize all the receive antenna for canceling interference. With $α$ as the path loss exponent, $N_t$ transmit antenna, $N_r$ receive antenna, we show that it is optimal to use $N_t\left\lceil\left(1-\frac{2}α\right) \left( \frac{N_r}{N_t} -\frac{1}{2}\right)\right\rceil$ receive antennas for interference cancellation and the remaining antennas for signal enhancement (array gain). For both PZF and MMSE receivers, we observe that increasing the number of data streams provides an improvement in the mean data rate with diminishing returns. Also transmitting $N_r$ streams is not optimal in terms of the mean sum rate. We observe that increasing the SM rate with a PZF receiver always degrades the cell edge data rate while the performance with MMSE receiver is nearly independent of the SM rate.

cs.IT↗

arXiv2013

Load-Aware Modeling and Analysis of Heterogeneous Cellular Networks

Random spatial models are attractive for modeling heterogeneous cellular networks (HCNs) due to their realism, tractability, and scalability. A major limitation of such models to date in the context of HCNs is the neglect of network traffic and load: all base stations (BSs) have typically been assumed to always be transmitting. Small cells in particular will have a lighter load than macrocells, and so their contribution to the network interference may be significantly overstated in a fully loaded model. This paper incorporates a flexible notion of BS load by introducing a new idea of conditionally thinning the interference field. For a K-tier HCN where BSs across tiers differ in terms of transmit power, supported data rate, deployment density, and now load, we derive the coverage probability for a typical mobile, which connects to the strongest BS signal. Conditioned on this connection, the interfering BSs of the $i^{th}$ tier are assumed to transmit independently with probability $p_i$, which models the load. Assuming - reasonably - that smaller cells are more lightly loaded than macrocells, the analysis shows that adding such access points to the network always increases the coverage probability. We also observe that fully loaded models are quite pessimistic in terms of coverage.

cs.IT↗

arXiv2013

Towards Understanding the Fundamentals of Mobility in Cellular Networks

Despite the central role of mobility in wireless networks, analytical study on its impact on network performance is notoriously difficult. This paper aims to address this gap by proposing a random waypoint (RWP) mobility model defined on the entire plane and applying it to analyze two key cellular network parameters: handover rate and sojourn time. We first analyze the stochastic properties of the proposed model and compare it to two other models: the classical RWP mobility model and a synthetic truncated Levy walk model which is constructed from real mobility trajectories. The comparison shows that the proposed RWP mobility model is more appropriate for the mobility simulation in emerging cellular networks, which have ever-smaller cells. Then we apply the proposed model to cellular networks under both deterministic (hexagonal) and random (Poisson) base station (BS) models. We present analytic expressions for both handover rate and sojourn time, which have the expected property that the handover rate is proportional to the square root of BS density. Compared to an actual BS distribution, we find that the Poisson-Voronoi model is about as accurate in terms of mobility evaluation as hexagonal model, though being more pessimistic in that it predicts a higher handover rate and lower sojourn time.

cs.NI↗

arXiv2012

Modeling and Analysis of K-Tier Downlink Heterogeneous Cellular Networks

Cellular networks are in a major transition from a carefully planned set of large tower-mounted base-stations (BSs) to an irregular deployment of heterogeneous infrastructure elements that often additionally includes micro, pico, and femtocells, as well as distributed antennas. In this paper, we develop a tractable, flexible, and accurate model for a downlink heterogeneous cellular network (HCN) consisting of K tiers of randomly located BSs, where each tier may differ in terms of average transmit power, supported data rate and BS density. Assuming a mobile user connects to the strongest candidate BS, the resulting Signal-to-Interference-plus-Noise-Ratio (SINR) is greater than 1 when in coverage, Rayleigh fading, we derive an expression for the probability of coverage (equivalently outage) over the entire network under both open and closed access, which assumes a strikingly simple closed-form in the high SINR regime and is accurate down to -4 dB even under weaker assumptions. For external validation, we compare against an actual LTE network (for tier 1) with the other K-1 tiers being modeled as independent Poisson Point Processes. In this case as well, our model is accurate to within 1-2 dB. We also derive the average rate achieved by a randomly located mobile and the average load on each tier of BSs. One interesting observation for interference-limited open access networks is that at a given SINR, adding more tiers and/or BSs neither increases nor decreases the probability of coverage or outage when all the tiers have the same target-SINR.

cs.IT↗

arXiv2012

Modeling Non-Uniform UE Distributions in Downlink Cellular Networks

A recent way to model and analyze downlink cellular networks is by using random spatial models. Assuming user equipment (UE) distribution to be uniform, the analysis is performed at a typical UE located at the origin. While this method of sampling UEs provides statistics averaged over the UE locations, it is not possible to sample cell interior and cell edge UEs separately. This complicates the problem of analyzing deployment scenarios involving non-uniform distribution of UEs, especially when the locations of the UEs and the base stations (BSs) are dependent. To facilitate this separation, we propose a new tractable method of sampling UEs by conditionally thinning the BS point process and show that the resulting framework can be used as a tractable generative model to study cellular networks with non-uniform UE distribution.

cs.IT↗

arXiv2012

MIMO Interference Alignment in Random Access Networks

In this paper, we analyze a multiple-input multiple-output (MIMO) interference channel where nodes are randomly distributed on a plane as a spatial Poisson cluster point process. Each cluster uses interference alignment (IA) to suppress intra-cluster interference but unlike most work on IA, we do not neglect inter-cluster interference. We also connect the accuracy of channel state information to the distance between the nodes, i.e. the quality of CSI degrades with increasing distance. Accounting for the training and feedback overhead, we derive the transmission capacity of this MIMO IA ad hoc network and then compare it to open-loop (interference-blind) spatial multiplexing. Finally, we present exemplary system setups where spatial multiplexing outperforms IA due to the imperfect channel state information or the non-aligned inter-cluster interference.

cs.IT↗