arXiv subjects

Abhay Karandikar

Publications and source records attributed to Abhay Karandikar.

44 records · Page 3Linked to original sources

arXiv2010

Asymptotic Capacity of Wireless Ad Hoc Networks with Realistic Links under a Honey Comb Topology

We consider the effects of Rayleigh fading and lognormal shadowing in the physical interference model for all the successful transmissions of traffic across the network. New bounds are derived for the capacity of a given random ad hoc wireless network that reflect packet drop or capture probability of the transmission links. These bounds are based on a simplified network topology termed as honey-comb topology under a given routing and scheduling scheme.

cs.IT↗

arXiv2009

Rate Constrained Random Access over a Fading Channel

In this paper, we consider uplink transmissions involving multiple users communicating with a base station over a fading channel. We assume that the base station does not coordinate the transmissions of the users and hence the users employ random access communication. The situation is modeled as a non-cooperative repeated game with incomplete information. Each user attempts to minimize its long term power consumption subject to a minimum rate requirement. We propose a two timescale stochastic gradient algorithm (TTSGA) for tuning the users' transmission probabilities. The algorithm includes a 'waterfilling threshold update mechanism' that ensures that the rate constraints are satisfied. We prove that under the algorithm, the users' transmission probabilities converge to a Nash equilibrium. Moreover, we also prove that the rate constraints are satisfied; this is also demonstrated using simulation studies.

cs.GT↗

arXiv2009

A Stable On-line Algorithm for Energy Efficient Multi-user Scheduling

In this paper, we consider the problem of energy efficient uplink scheduling with delay constraint for a multi-user wireless system. We address this problem within the framework of constrained Markov decision processes (CMDPs) wherein one seeks to minimize one cost (average power) subject to a hard constraint on another (average delay). We do not assume the arrival and channel statistics to be known. To handle state space explosion and informational constraints, we split the problem into individual CMDPs for the users, coupled through their Lagrange multipliers; and a user selection problem at the base station. To address the issue of unknown channel and arrival statistics, we propose a reinforcement learning algorithm. The users use this learning algorithm to determine the rate at which they wish to transmit in a slot and communicate this to the base station. The base station then schedules the user with the highest rate in a slot. We analyze convergence, stability and optimality properties of the algorithm. We also demonstrate the efficacy of the algorithm through simulations within IEEE 802.16 system.

cs.NI↗

arXiv2008

Some results on communicating the sum of sources over a network

We consider the problem of communicating the sum of $m$ sources to $n$ terminals in a directed acyclic network. Recently, it was shown that for a network of unit capacity links with either $m=2$ or $n=2$, the sum of the sources can be communicated to the terminals if and only if every source-terminal pair is connected in the network. We show in this paper that for any finite set of primes, there exists a network where the sum of the sources can be communicated to the terminals only over finite fields of characteristic belonging to that set. As a corollary, this gives networks where the sum can not be communicated over any finite field even though every source is connected to every terminal.

cs.IT↗

arXiv2007

Link Scheduling in STDMA Wireless Networks: A Line Graph Approach

We consider point to point link scheduling in Spatial Time Division Multiple Access (STDMA) wireless networks under the physical interference model. We propose a novel link scheduling algorithm based on a line graph representation of the network, by embedding the interferences between pairs of nodes into the edge weights of the line graph. Our algorithm achieves lower schedule length and lower run time complexity than existing algorithms.

cs.NI↗

arXiv2007

Power Efficient Scheduling under Delay Constraints over Multi-user Wireless Channels

In this paper, we consider the problem of power efficient uplink scheduling in a Time Division Multiple Access (TDMA) system over a fading wireless channel. The objective is to minimize the power expenditure of each user subject to satisfying individual user delay. We make the practical assumption that the system statistics are unknown, i.e., the probability distributions of the user arrivals and channel states are unknown. The problem has the structure of a Constrained Markov Decision Problem (CMDP). Determining an optimal policy under for the CMDP faces the problems of state space explosion and unknown system statistics. To tackle the problem of state space explosion, we suggest determining the transmission rate of a particular user in each slot based on its channel condition and buffer occupancy only. The rate allocation algorithm for a particular user is a learning algorithm that learns about the buffer occupancy and channel states of that user during system execution and thus addresses the issue of unknown system statistics. Once the rate of each user is determined, the proposed algorithm schedules the user with the best rate. Our simulations within an IEEE 802.16 system demonstrate that the algorithm is indeed able to satisfy the user specified delay constraints. We compare the performance of our algorithm with the well known M-LWDF algorithm. Moreover, we demonstrate that the power expended by the users under our algorithm is quite low.

cs.NI↗

arXiv2007

On High Spatial Reuse Link Scheduling in STDMA Wireless Ad Hoc Networks

Graph-based algorithms for point-to-point link scheduling in Spatial reuse Time Division Multiple Access (STDMA) wireless ad hoc networks often result in a significant number of transmissions having low Signal to Interference and Noise density Ratio (SINR) at intended receivers, leading to low throughput. To overcome this problem, we propose a new algorithm for STDMA link scheduling based on a graph model of the network as well as SINR computations. The performance of our algorithm is evaluated in terms of spatial reuse and computational complexity. Simulation results demonstrate that our algorithm achieves better performance than existing algorithms.

cs.PF↗

arXiv2006

Entropy-optimal Generalized Token Bucket Regulator

We derive the maximum entropy of a flow (information utility) which conforms to traffic constraints imposed by a generalized token bucket regulator, by taking into account the covert information present in the randomness of packet lengths. Under equality constraints of aggregate tokens and aggregate bucket depth, a generalized token bucket regulator can achieve higher information utility than a standard token bucket regulator. The optimal generalized token bucket regulator has a near-uniform bucket depth sequence and a decreasing token increment sequence.

cs.IT↗