Chittabrata Ghosh

Coexistence challenges for heterogeneous cognitive wireless networks in TV white spaces

In order to improve utilization of TV spectrum, regulatory bodies around the world have been developing rules to allow operation by unlicensed users in these bands provided that interference to incumbent broadcasters is avoided. Thus, new services may opportunistically use temporarily unoccupied TV channels, known as television white space. This has motivated several standardization efforts such as IEEE 802.22, 802.11af, 802.19 TG1, and ECMA 392 to further cognitive networking. Specifically, multiple collocated secondary networks are expected to use TVWS, each with distinct requirements (bandwidth, transmission power, different system architectures, and device types) that must all comply with regulatory requirements to protect incumbents. Heterogeneous coexistence in the TVWS is thus expected to be an important research challenge. This article introduces the current regulatory scenario, emerging standards for cognitive wireless networks targeting the TVWS, and discusses possible coexistence scenarios and associated challenges. Furthermore, the article casts an eye on future considerations for these upcoming standards in support of spectrum sharing opportunities as a function of network architecture evolution.

Markov chain existence and Hidden Markov models in spectrum sensing

The primary function of a cognitive radio is to detect idle frequencies or sub-bands, not used by the primary users (PUs), and allocate these frequencies to secondary users. The state of the sub-band at any time point is either free (unoccupied by a PU) or busy (occupied by a PU). The states of a sub-band are monitored over L consecutive time periods, where each period is of a given time interval. Existing research assume the presence of a Markov chain for sub-band utilization by PUs over time, but this assumption has not been validated. Therefore, in this paper we validate existence of a Markov chain for sub-band utilization using real-time measurements collected in the paging band (928–948 MHz). Furthermore, since the detection of idle sub-bands by a cognitive radio is prone to errors, we probabilistically model the errors and then formulate a spectrum sensing paradigm as a Hidden Markov model that predicts the true states of a sub-band. The accuracy of our proposed method in predicting the true states of the sub-band is substantiated using extensive simulations.

A framework for statistical wireless spectrum occupancy modeling

In this paper, we propose a novel spectrum occupancy model designed to generate accurate temporal and frequency behavior of various wireless transmissions. Our proposed work builds upon existing concepts in open literature in order to develop a more accurate time-varying spectrum occupancy model. This model can be employed by wireless researchers for evaluating new wireless communication and networking algorithms and techniques designed to perform dynamic spectrum access (DSA). Using statistical characteristics extracted from actual radio frequency measurements, first- and second-order parameters are employed in a statistical spectrum occupancy model based on a combination of several different probability density functions (PDFs) defining various features of a specific spectrum band with several concurrent transmissions. To assess the accuracy of the model, the output characteristics of the proposed spectrum occupancy model are compared with realtime radio frequency measurements in the television and paging bands.

Modeling and Validation of Channel Idleness and Spectrum Availability for Cognitive Networks

The potential of successful cognitive radio networks operating in TV White Spaces (and other future bands re-allocated for unlicensed operation) has led to significant upsurge of interest in their design optimization - particularly those that are cross-layer in nature, involving both MAC protocols as well as physical layer aspects such as channel sensing. Typically, these seek to optimize a network-level metric (notably, aggregate throughput) of secondary (cognitive) network subject to interference constraints on the primary. In turn, this requires suitable sensing by cognitive users to detect availability of primary channels (currently unused by the protected incumbents) for opportunistic usage. To date, most studies have used largely hypothetical assumptions regarding channel idleness and resulting spectrum availability due to primary user dynamics. For example, idleness of channels over any spectrum are typically assumed to be an independent and identically distributed Bernoulli sequence. In contrast, nearly all real-time measurements suggest that channel idleness is frequency dependent, i.e., the probability that a channel is idle depends on the channel location. Cognitive radio research thus increasingly needs more realistic and validated models for channel idleness as the foundation of credible cross-layer analysis; this is the primary contribution of our work. We use two sets of real-time measurements conducted in disparate geographic locations over four distinct time intervals to show that channel idleness is appropriately modeled as independent but non-identical (i.n.i.d.) Bernoulli variables characterized by p_i, the probability of idleness for the i-th channel. We validate that Beta distribution can be used for modeling the variations in channel idleness probabilities; the Beta distribution parameters are estimated from the data to produce the best model fit. Based on the validated i.n.i.d. model, we build a predictive model by computing the availability probability of k channels, i.e, P{N_{idle} = k}, where N_{idle} denotes the number of idle channels over the spectrum of N channels. However, the combinatorial complexity inherent in the computation of P{N_{idle} = k} suggests the need for efficient approximations. We accomplish this by classifying idleness of channels based on the magnitude of p_i, and propose a novel Poisson-normal approximation for computing P{N_{idle} = k}. For validation, the distribution obtained from our technique is compared with the exact distribution and normal approximation using the approximation error criterion.

Performance Analysis of Group-Synchronized DCF for Dense IEEE 802.11 Networks

In dense IEEE 802.11 networks, improving the efficiency of contention-based media access control is an important and challenging issue. Recently, the IEEE802.11ah Task Group has discussed a group-synchronized distributed coordination function (GS-DCF) for densely deployed wireless networks with a large number of stations. By using the restricted access window (RAW) and RAW slots, the GS-DCF is anticipated to improve the throughput substantially, primarily due to relieving the channel contention. However, optimizing the MAC configurations for the RAW, i.e., the number and duration of RAW slots, is still an open issue. In this paper, we first build an analytical model to track the performance of the GS-DCF in saturated 802.11 networks. Then, we study and compare the GS-DCF throughput using both centralized and decentralized grouping schemes. The accuracy of our model has been validated with simulation results. It is observed that the GS-DCF obtains a throughput gain of seven times or more over DCF in a network of 512 or more stations. Moreover, it is demonstrated that the decentralized grouping scheme can be implemented with a small throughput loss when compared with the centralized grouping scheme.

Spectrum occupancy validation and modeling using real-time measurements

Existing research have considered Beta distribution in modeling channel occupancy of primary users in a licensed spectrum. This paper is the first initiative in validating this basic assumption in the cognitive radio paradigm using real-time measurements performed in Aachen, Germany on the 1500 MHz spectrum centered at 770 MHz. The Kolmogorov-Smirnov test is applied as a validation approach. The result of this test conforms to the validity of the Beta distribution modeling of spectrum occupancy. With this channel occupancy model, we have extended our research in modeling spectrum availability by proposing a new Poisson-normal approximation method. Further, we characterize available channels in a spectrum into five different types based on occupancy of its two adjacent channels. The probabilistic modeling of each of these types is determined using recurrence relations. Simulation results show that channel type classification and their modeling facilitate preferable selection of one section compared to another section over an operating spectrum.

Throughput Analysis for a Multi-User, Multi-Channel ALOHA Cognitive Radio System

In this paper, we investigate a novel slotted ALOHA-based distributed access cognitive network in which a secondary user (SU) selects a random subset of channels for sensing, detects an idle (unused by licensed users) subset therein, and transmits in any one of those detected idle channels. First, we derive a range for the number of channels to be sensed per SU access. Then, the analytical average system throughput is attained for cases where the number of idle channels is a random variable. Based on that, a relationship between the average system throughput and the number of sensing channels is attained. Subsequently, a joint optimization problem is formulated in order to maximize average system throughput. The analytical results are validated by substantial simulations.

On-demand reliable medium access in sensor networks

A wireless sensor network typically consists of a dense deployment of sensor nodes to achieve higher resolution and better network coverage. Having a dense network increases the fault-tolerance and robustness of the system. However, if not properly handled, it can lead to more collisions during transmission and also network congestion. Furthermore, wireless communication is inherently unpredictable and error-prone. Hence, it is imperative to design an efficient medium access control (MAC) protocol that facilitates guaranteed delivery of data over unreliable wireless links. In this paper, we have designed an on-demand reliable MAC (RMAC) protocol that enables timely delivery of data. We have demonstrated its superior performance over existing reliability-enforcing approaches in terms of reliability, latency, scalability and energy-efficiency

Priority-based spectrum allocation for cognitive radio networks employing NC-OFDM transmission

In this paper, we present three novel priority-based spectrum allocation techniques for enabling dynamic spectrum access (DSA) networking for non-contiguous orthogonal frequency division multiplexing (NC-OFDM) transmission. With each communication link in the network possessing a specified pair of bit error rate (BER) and throughput requirements for supporting a specific application, the proposed technique assigns one or more blocks of wireless spectrum to these applications in an attempt to simultaneously satisfy these requirements. Specifically, the proposed techniques assigns blocks of spectrum possessing aggregate bandwidth that is sufficient for supporting the intended wireless data service over the communication link. Moreover, since several portions of the wireless spectrum may be heavily attenuated due to frequency-selective fading resulting from multipath propagation, communication links requiring high error robustness are assigned frequency bands located further away from these attenuated regions of spectrum. Thus, the proposed spectrum allocation techniques aims at accommodating communication links supporting several wireless services possessing different performance requirements.

Channel Assignment with Route Discovery (CARD) using Cognitive Radio in Multi-channel Multi-radio Wireless Mesh Networks

For better spectrum utilization, efficient channel allocation in multi-radio wireless mesh networks has become an active research area. Our proposed CARD algorithm deals with the application of cognitive mesh routers for fixed channel assignments to mesh clients under each routers domain. The farthest channel assignment by the cognitive radio in mesh routers ensures minimum inter-router and intra-router interference. Initial fixed assignment of channels to clients supporting k-connectivity (k = 3 and 5 sub-channels) shows substantial increase with 15 concurrent transmissions when compared to 4 in case of the CCA scheme with k=3 and 3 channels to choose, i.e., a factor of almost 4. The improvement in communication delay is about a factor of 80 when compared to SC and a factor of 35 compared to CCA.