Our research effort bridges several areas such as coding theory and its applications, modern wireless networking (sensor/ad-hoc networks, cognitive radio networks), and signal processing. Our research has so far been supported by the following agencies/programs:

  • National Science Foundation (NSF)
  • Department of Defense (DoD), Defense University Research Instrumentation Program   


Here is some of our recent research efforts:

Compressive Sensing: Design and Applications

The emerging field of compressive sensing (CS) has overturned the traditional concept of sensing and sampling, established by Nyquist sampling theorem, for signals that have a sparse representation over some proper basis. We are studying new CS sampling and recovery schemes with low complexity and improved performance. We are also exploring new exciting applications for CS.


Spectrum Sensing in Cognitive Radio Networks

Efficient spectrum sensing is one of the key steps for implementing the cognitive radio-based systems. We are investigating several novel spectrum sensing techniques for different network scenarios. Here is the list of some of our ongoing projects:

·         Cooperative-Parallel Spectrum Sensing in Cognitive Radio Networks Using Bipartite Matching

·         Joint Wideband Spectrum Sensing in Frequency Overlapping Cognitive Radio Networks Using Distributed Compressive Sensing

·         Eigenvalue-based Cooperative Spectrum Sensing with Finite Samples/Sensors



Spectrum Sharing in Cognitive Radio Networks

Cognitive radio (CR) is a promising solution to alleviate today's spectrum deficiency. In this research, we analyze and compare the performance of cooperative relaying in CRNs with two different error control scenarios namely, selective automatic repeat request (SR-ARQ) and rateless coding. Our goal is to maximize the secondary (unlicensed) user's throughput, while preserving the stable throughput and end-to-end delay requirements of primary (licensed) user.




UEP Rateless Codes for Efficient Video Transmission

Rateless codes with unequal error protection (UEP) property can be employed to increase the video transmission efficiency.

First, we employed the UEP rateless codes in video-on-demand (VOD) systems. In VOD systems, required bandwidth is decreased to a great extend by sharing a single video stream among several users watching the same video. We proposed to employ unequal error protection (UEP) rateless codes in VOD systems and have show this scheme decreases the initial waiting time considerably compared to the case where equal error protection (EEP) codes are employed.

Second, we studied the application of UEP rateless codes for efficient MPEG video transmission. MPEG movie has different frame types namely, I, P, and B, which have different levels of importance. UEP rateless codes can be efficiently used to increased the MPEG video transmission efficiency.







DU-rateless Codes: Distributed Rateless Codes with UEP Property

When multiple sources of data need to transmit their rateless coded symbols through a single relay to a common destination, a distributed rateless code can be employed to encode the source symbols instead of several separated conventional rateless codes to increase the transmission efficiency and flexibility.

In this research, we have proposed DU-rateless codes, which are distributed rateless codes that can provide UEP for sources with different data lengths (see right figure). We have designed degree distributions for DU-rateless codes using genetic-algorithms. The degree distributions are available HERE for ρ={0.3,0.5,1}.

Provide desired 1<η and ρ={0.3,0.5,1} to the Matlab function enclosed to find the appropriate optimum DU-rateless code.

>> [dd1 dd2 p1 p2 p3] = best_DUrateless_finder( [desired η], [desired ρ] )

Example in Matlab environment for ρ=1 and η=10:

>> [dd1 dd2 p1 p2 p3] = best_DUrateless_finder(10,1)


Rateless Codes with Optimum Intermediate Performance

We have designed several rateless codes similar to LT codes with optimum intermediate recovery rate. You can download the databases for optimum degree distribution of 4 different lengths (Asymptotic, k=10,000, k=1000, k=100) in Matlab MAT file format. The first three columns are the packet error rate of each degree distribution at received overheads of 50%, 75% and 100%, respectively. The rest of each column shows the respective degree distribution from degree one and up. All files are available in one compressed file that you can download HERE. The Matlab function which returns the best solution out of many optimum degree distributions according to three weights assigned to each objective function is also included in the compressed file.

Please load the MAT files before running the function with command "load x.mat". Replace "x" with desired results database file name. Then provide desired weights to the function for find optimum degree distribution.

Example in matlab environment: we want to find the best degree distribution for rateless codes of length 10k in intermediate range with equal weights of one. The input weights are for packet error rates at 50%, 75% and 100%, respectively

>> load costs_final_k10000

>> degree_distr = best_degree_finder(1,1,1,costs_final)


Minimum-Energy Broadcast in Wireless Sensor Networks Using Rateless Coding

Efficient network-wide broadcasting is an important issue in wireless networks that attracted a lot of attention.

In this research, we considered the case that a large amount of packets have to be broadcasted in a multihop wireless network with our main concerns being reliability and energy-efficiency. We proposed a two-phase broadcasting scheme referred as Collaborative Rateless Broadcast (CRBcast). Our two-phase protocol is based on Probabilistic Broadcasting (PBcast) and an application layer rateless coding. At the first phase, the rateless-encoded packets are broadcasted based on PBcast, in which each node probabilistically relays every new received packet. The second recovery phase, which is based on simple collaborations of nodes, ensures that all nodes can recover original data. We showed that CRBcast can provide both reliability and energy efficiency. Simulation results indicate that CRBcast saves at least 72% and 60% energy in comparison with flooding and PBcast, respectively. We implemented CRBcast protocol in a testbed including MICAz motes with TinyOS distributed software operating system. The result showed similar improvement in the energy efficiency while providing reliability. We are currently working on another scheme for reliable and energy-efficient one-to-all broadcasting in multihop wireless networks, where each link is modeled as a packet erasure channel. In this scheme, referred to as Fractional Transmission Scheme (FTS), rateless coding enables each node to send a fraction of the total encoded packets.


Bounds on Maximum-Likelihood Decoding of Finite-Length Rateless Codes

In this research, we derived upper and lower bounds on maximum-likelihood (ML) decoding bit error probabilities of finite-length rateless codes over the binary erasure channel. The bounds on ML decoding is of interest, as it provides an ultimate indication on the system performance. Simulation results depict that the bounds are tight. These bounds specifically can be used for optimizing the degree distribution of rateless codes when the decoding scheme performs like or close to ML decoding. Maxwell decoder and guess-based decoder are examples of such decoding schemes.

Unequal Error Protection LDPC Codes

We proposed two schemes to construct LDPC codes that are suitable for unequal error protection (UEP). The first scheme is based on partially-regular LDPC codes. The proposed ensemble for the second scheme is a combination of two conventional bipartite graphs. We derived density evolution formulas for both the proposed UEP-LDPC ensembles. Using the density evolution formulas, high performance UEP codes were found. The proposed codes were also shown to have linear encoding complexity, which is very desirable for practical applications.






Unequal Error Protection Rateless Codes

Rateless codes are a new class of codes that have been invented recently. Rateless codes on lossy channels do not assume any knowledge about the channel, unlike the traditional codes. This feature makes them very interesting in the applications that the channel loss is unknown, time-varying, or nonuniform. In the original work on rateless codes, equal error protection (EEP) of all data was considered. EEP would be sufficient in the applications such as multicasting bulk data. However, in several applications, a portion of data may need more protection than the rest of data. For example, in an MPEG stream, I-frames need more protection that P-frames.

In some other applications, a portion of data may need to be recovered prior to the other parts. An example would be on-demand media streaming, in which the stream should be reconstructed in sequence. Such applications raise a need for having codes with unequal error protection (UEP) or unequal recovery time (URT) property. We developed , for the first time, rateless codes that can provide UEP and URT. We analyzed the proposed codes under both iterative decoding and maximum-likelihood decoding. Results are very promising and show the applicability of UEP-rateless codes in many important applications, such as transferring data frames or video/audio-on-demand streaming.