arXiv subjects

Mohammed Karmoose

Publications and source records attributed to Mohammed Karmoose.

14 recordsLinked to original sources

arXiv2025

Discovering the Unequal Importance of Coded Bits in the Decoding of Polar Codes

Polar codes are widely used in modern communication systems due to their capacity-achieving properties. This paper investigates the importance of coded bits in the decoding process of polar codes and aims to determine which bits contribute most to successful decoding. We investigate the problem via a brute-force search approach and surrogate optimization techniques to identify the most critical coded bits. We also demonstrate how mapping these important bits to the most reliable channels improves system performance with minimal additional cost. We show the performance of our proposed bit mapping in OFDM based systems, and demonstrate up to x7 gain in BER performance.

cs.IT↗

arXiv2025

Detecting What Matters: A Novel Approach for Out-of-Distribution 3D Object Detection in Autonomous Vehicles

Autonomous vehicles (AVs) use object detection models to recognize their surroundings and make driving decisions accordingly. Conventional object detection approaches classify objects into known classes, which limits the AV's ability to detect and appropriately respond to Out-of-Distribution (OOD) objects. This problem is a significant safety concern since the AV may fail to detect objects or misclassify them, which can potentially lead to hazardous situations such as accidents. Consequently, we propose a novel object detection approach that shifts the emphasis from conventional class-based classification to object harmfulness determination. Instead of object detection by their specific class, our method identifies them as either 'harmful' or 'harmless' based on whether they pose a danger to the AV. This is done based on the object position relative to the AV and its trajectory. With this metric, our model can effectively detect previously unseen objects to enable the AV to make safer real-time decisions. Our results demonstrate that the proposed model effectively detects OOD objects, evaluates their harmfulness, and classifies them accordingly, thus enhancing the AV decision-making effectiveness in dynamic environments.

cs.CV↗

arXiv2020

Distortion based Light-weight Security for Cyber-Physical Systems

In Cyber-Physical Systems (CPS), inference based on communicated data is of critical significance as it can be used to manipulate or damage the control operations by adversaries. This calls for efficient mechanisms for secure transmission of data since control systems are becoming increasingly distributed over larger geographical areas. Distortion based security, recently proposed as one candidate for secure transmissions in CPS, is not only more appropriate for these applications but also quite frugal in terms of prior requirements on shared keys. In this paper, we propose distortion-based metrics to protect CPS communication and show that it is possible to confuse adversaries with just a few bits of pre-shared keys. In particular, we will show that a linear dynamical system can communicate its state in a manner that prevents an eavesdropper from accurately learning the state.

cs.IT↗

arXiv2019

Using mm-Waves for Secret Key Establishment

The fact that Millimeter Wave (mmWave) communication needs to be directional is usually perceived as a challenge; in this paper we argue that it enables efficient secret key sharing that are unconditionally secure from passive eavesdroppers, by building on packet erasures. We showcase the potential of our approach in two setups: mmWave-based WiFi networks and vehicle platooning. We show that in the first case, we can establish a few hundred secret bits with minimal changes to standard communication protocol; while in both cases, with the right choice of parameters, we can potentially establish keys in the order of tenths of Mbps. These first results are based on some simplifying assumptions, yet we believe they give incentives to further explore such techniques.

cs.CR↗

arXiv2018

Privacy in Index Coding: $k$-Limited-Access Schemes

In the traditional index coding problem, a server employs coding to send messages to $n$ clients within the same broadcast domain. Each client already has some messages as side information and requests a particular unknown message from the server. All clients learn the coding matrix so that they can decode and retrieve their requested data. Our starting observation is that, learning the coding matrix can pose privacy concerns: it may enable a client to infer information about the requests and side information of other clients. In this paper, we mitigate this privacy concern by allowing each client to have limited access to the coding matrix. In particular, we design coding matrices so that each client needs only to learn some of (and not all) the rows to decode her requested message. By means of two different privacy metrics, we first show that this approach indeed increases the level of privacy. Based on this, we propose the use of $k$-limited-access schemes: given an index coding scheme that employs $T$ transmissions, we create a $k$-limited-access scheme with $T_k\geq T$ transmissions, and with the property that each client needs at most $k$ transmissions to decode her message. We derive upper and lower bounds on $T_k$ for all values of $k$, and develop deterministic designs for these schemes, which are universal, i.e., independent of the coding matrix. We show that our schemes are order-optimal when either $k$ or $n$ is large. Moreover, we propose heuristics that complement the universal schemes for the case when both $n$ and $k$ are small.

cs.IT↗

arXiv2018

Distorting an Adversary's View in Cyber-Physical Systems

In Cyber-Physical Systems (CPSs), inference based on communicated data is of critical significance as it can be used to manipulate or damage the control operations by adversaries. This calls for efficient mechanisms for secure transmission of data since control systems are becoming increasingly distributed over larger geographical areas. Distortion based security, recently proposed as one candidate for CPSs security, is not only more appropriate for these applications but also quite frugal in terms of prior requirements on shared keys. In this paper, we propose distortion-based metrics to protect CPSs communication and show that it is possible to confuse adversaries with just a few bits of pre-shared keys.

cs.IT↗

arXiv2018

Privacy in Index Coding: Improved Bounds and Coding Schemes

It was recently observed in [1], that in index coding, learning the coding matrix used by the server can pose privacy concerns: curious clients can extract information about the requests and side information of other clients. One approach to mitigate such concerns is the use of $k$-limited-access schemes [1], that restrict each client to learn only part of the index coding matrix, and in particular, at most $k$ rows. These schemes transform a linear index coding matrix of rank $T$ to an alternate one, such that each client needs to learn at most $k$ of the coding matrix rows to decode its requested message. This paper analyzes $k$-limited-access schemes. First, a worst-case scenario, where the total number of clients $n$ is $2^T-1$ is studied. For this case, a novel construction of the coding matrix is provided and shown to be order-optimal in the number of transmissions. Then, the case of a general $n$ is considered and two different schemes are designed and analytically and numerically assessed in their performance. It is shown that these schemes perform better than the one designed for the case $n=2^T-1$.

cs.IT↗

arXiv2017

Communication vs Distributed Computation: an alternative trade-off curve

In this paper, we revisit the communication vs. distributed computing trade-off, studied within the framework of MapReduce in [1]. An implicit assumption in the aforementioned work is that each server performs all possible computations on all the files stored in its memory. Our starting observation is that, if servers can compute only the intermediate values they need, then storage constraints do not directly imply computation constraints. We examine how this affects the communication-computation trade-off and suggest that the trade-off be studied with a predetermined storage constraint. We then proceed to examine the case where servers need to perform computationally intensive tasks, and may not have sufficient time to perform all computations required by the scheme in [1]. Given a threshold that limits the computational load, we derive a lower bound on the associated communication load, and propose a heuristic scheme that achieves in some cases the lower bound.

cs.IT↗

arXiv2017

Preserving Privacy while Broadcasting: $k$-Limited-Access Schemes

Index coding employs coding across clients within the same broadcast domain. This typically assumes that all clients learn the coding matrix so that they can decode and retrieve their requested data. However, learning the coding matrix can pose privacy concerns: it may enable clients to infer information about the requests and side information of other clients [1]. In this paper, we formalize the intuition that the achieved privacy can increase by decreasing the number of rows of the coding matrix that a client learns. Based on this, we propose the use of $k$-limited-access schemes: given an index coding scheme that employs $T$ transmissions, we create a $k$-limited-access scheme with $T_k\geq T$ transmissions, and with the property that each client learns at most $k$ rows of the coding matrix to decode its message. We derive upper and lower bounds on $T_k$ for all values of $k$, and develop deterministic designs for these schemes for which $T_k$ has an order-optimal exponent for some regimes.

cs.IT↗

arXiv2017

Private Broadcasting: an Index Coding Approach

Using a broadcast channel to transmit clients' data requests may impose privacy risks. In this paper, we address such privacy concerns in the index coding framework. We show how a malicious client can infer some information about the requests and side information of other clients by learning the encoding matrix used by the server. We propose an information-theoretic metric to measure the level of privacy and show how encoding matrices can be designed to achieve specific privacy guarantees. We then consider a special scenario for which we design a transmission scheme and derive the achieved levels of privacy in closed-form. We also derive upper bounds and we compare them to the levels of privacy achieved by our scheme, highlighting that an inherent trade-off exists between protecting privacy of the request and of the side information of the clients.

cs.IT↗

arXiv2016

Cooperation-based Routing in Cognitive Radio Networks

Primary user activity is a major bottleneck for existing routing protocols in cognitive radio networks. Typical routing protocols avoid areas that are highly congested with primary users, leaving only a small fragment of available links for secondary route construction. In addition, wireless links are prone to channel impairments such as multipath fading; which renders the quality of the available links highly fluctuating. In this paper, we investigate using cooperative communication mechanisms to reveal new routing opportunities, enhance route qualities, and enable true coexistence of primary and secondary networks. As a result, we propose Undercover: a cooperative routing protocol that utilizes the available location information to assist in the routing process. Specifically, our protocol revisits a fundamental assumption taken by the state of the art routing protocols designed for cognitive radio networks. Using Undercover, secondary users can transmit in the regions of primary users activity through utilizing cooperative communication techniques to null out transmission at primary receivers via beamforming. In addition, the secondary links qualities are enhanced using cooperative diversity. To account for the excessive levels of interference typically incurred due to cooperative transmissions, we allow our protocol to be interference-aware. Thus, cooperative transmissions are penalized in accordance to the amount of negatively affected secondary flows. We evaluate the performance of our proposed protocol via NS2 simulations which show that our protocol can enhance the network goodput by a ratio reaches up to 250% compared to other popular cognitive routing protocols with minimal added overhead.

cs.NI↗

arXiv2016

Simplifying Wireless Social Caching

Social groups give the opportunity for a new form of caching. In this paper, we investigate how a social group of users can jointly optimize bandwidth usage, by each caching parts of the data demand, and then opportunistically share these parts among themselves upon meeting. We formulate this problem as a Linear Program (LP) with exponential complexity. Based on the optimal solution, we propose a simple heuristic inspired by the bipartite set-cover problem that operates in polynomial time. Furthermore, we prove a worst case gap between the heuristic and the LP solutions. Finally, we assess the performance of our algorithm using real-world mobility traces from the MIT Reality Mining project dataset and two mobility traces that were synthesized using the SWIM model. Our heuristic performs closely to the optimal in most cases, showing a better performance with respect to alternative solutions.

cs.IT↗

arXiv2015

Censoring for Improved Sensing Performance in Infrastructure-less Cognitive Radio Networks

Censoring has been proposed to be utilized in wireless distributed detection networks with a fusion center to enhance network performance in terms of error probability in addition to the well-established energy saving gains. In this paper, we further examine the employment of censoring in infrastructure-less cognitive radio networks, where nodes employ binary consensus algorithms to take global decisions regarding a binary hypothesis test without a fusion center to coordinate such a process. We show analytically - and verify by simulations - that censoring enhances the performance of such networks in terms of error probability and convergence times. Our protocol shows performance gains up to 46.6% in terms of average error probability over its conventional counterpart, in addition to performance gains of about 48.7% in terms of average energy expenditure and savings up to 50% in incurred transmission overhead.

cs.NI↗

arXiv2013

Dead Zone Penetration Protocol for Cognitive Radio Networks

Current routing protocols for cognitive radio networks are severely affected by the frequent activity of primary users. Nodes that are in the interference range of an appearing primary user are not allowed to transmit, and therefore existing routes which utilize such nodes are obliged to undergo a route maintenance phase. This naturally provides other routes to the destination that may incur extra delay or increase packet queuing overhead. In this work, a novel route maintenance protocol is proposed that allows existing routes to endure the event of primary user presence by forming cooperative links between neighboring nodes and nulling out transmission at the primary receiver using cooperative beamforming. Our proposed protocol can be used in conjunction with any of the existing routing protocols, thus achieving modularity. Extensive simulations are done which prove that our proposed protocol outperforms existing route maintenance techniques in terms of end-to-end delay and loss ratio, with minimal incurred overhead.

cs.NI↗