Haythem Bany Salameh

Cooperative adaptive spectrum sharing in cognitive radio networks

The cognitive radio (CR) paradigm calls for open spectrum access according to a predetermined etiquette. Under this paradigm, CR nodes access the spectrum opportunistically by continuously monitoring the operating channels. A key challenge in this domain is how the nodes in a CR network (CRN) cooperate to access the medium in order to maximize the CRN throughput. Typical multichannel MAC protocols assume that frequency channels are adjacent and that there are no constraints on the transmission power. However, a CRN may operate over a wide range of frequencies, and a power mask is often enforced on the transmission of a CR user to avoid corrupting the transmissions of spectrum-licensed primary-radio (PR) users. To avoid unnecessary blocking of CR transmissions, we propose a novel distance-dependent MAC protocol for CRNs. Our protocol, called DDMAC, attempts to maximize the CRN throughput. It uses a novel probabilistic channel assignment mechanism that exploits the dependence between the signals attenuation model and the transmission distance while considering the traffic profile. DDMAC allows a pair of CR users to communicate on a channel that may not be optimal from one users perspective, but that allows more concurrent transmissions to take place, especially under moderate and high traffic loads. Simulation results indicate that, compared to typical multichannel CSMA-based protocols, DDMAC reduces the blocking rate of CR requests by up to 30%, which consequently improves the network throughput.

Spectrum Bonding and Aggregation with Guard-Band Awareness in Cognitive Radio Networks

Spectrum access/sharing algorithms for dynamic spectrum access (DSA) networks are often designed without accounting for adjacent-channel interference. In practice, guard bands are needed to prevent such interference. Introducing guard bands naturally constrains the effective use of the spectrum. In this work, we investigate the problem of assigning channels/powers to opportunistic transmissions, while accounting for such a constraint. Specifically, we propose a novel guard-band-aware channel assignment scheme for DSA systems. Our scheme reduces the number of required guard channels for a given transmission by exploiting the benefit of utilizing adjacent channels and considering already reserved guard channels. We analytically formulate the channel access problem as a joint power control and channel assignment optimization problem, with the objective of minimizing the required spectrum resource for a given CR transmission. We show that the optimization problem is a binary linear program (BLP), which is, in general, NP-hard. Accordingly, we present a near-optimal solution based on sequential fixing, where the binary variables are determined iteratively by solving a sequence of linear programs. Based on the proposed channel assignment algorithm, we develop an operational MAC protocol that enables DSA users to dynamically utilize the spectrum. The proposed protocol realizes our channel assignment algorithm in a distributed manner while relying only on information provided by the two communicating users. Simulation results are provided, which verify the effectiveness of our protocol and demonstrate the significant gain achieved through guard-band-aware channel assignment.

Distance- and Traffic-Aware Channel Assignment in Cognitive Radio Networks

The scarcity of unlicensed spectrum has triggered great interest in cognitive radio (CR) technology as a means to improve spectrum utilization. An important challenge in this domain is how to enable nodes in a CR network (CRN) to access the medium opportunistically. Multi-channel MAC protocols for typical ad hoc networks assume that frequency channels are adjacent and that there are no strict constraints on the transmission power. However, a CRN may occupy a wide range of frequencies. In addition, a power mask is often enforced on the transmission power of a CR user to avoid corrupting the transmissions of spectrum-licensed primary-radio (PR) users. Obviously, CR users operating in different licensed bands will be subject to different PR-to-CR interference conditions. To avoid unnecessary blocking of CR transmissions under these constraints, we propose a novel distance-dependent MAC protocol for CRNs (DDMAC) that attempts to maximize the CRN throughput. DDMAC introduces a novel suboptimal probabilistic channel assignment algorithm that exploits the dependence between the signals attenuation model and the transmission distance while considering the traffic profile. The protocol allows a pair of CR users to communicate on a channel that may not be optimal from one users perspective, but that allows more transmissions to take place simultaneously, especially under moderate to high traffic loads. Simulation results indicate that compared to typical multi-channel CSMA-based protocols, DDMAC decreases the connection blocking rate of CR transmission requests by up to 30%, which improves the network throughput at no additional cost in energy consumption. On the whole, our protocol is simple yet effective. It can be incorporated into existing multi-channel systems with little extra processing overhead.

Throughput-oriented channel assignment for opportunistic spectrum access networks

Cognitive radio (CR) is a revolutionary technology in wireless communications that enhances spectrum utilization by allowing opportunistic and dynamic spectrum access. One of the key challenges in this domain is how CR users cooperate to dynamically access the available spectrum opportunities in order to maximize the overall perceived throughput. In this paper, we consider the coordinated spectrum access problem in a multi-user single-transceiver CR network (CRN), where each CR user is equipped with only one half-duplex transceiver. We first formulate the dynamic spectrum access as a rate/power control and channel assignment optimization problem. Our objective is to maximize the sum-rate achieved by all contending CR users over all available spectrum opportunities under interference and hardware constraints. We first show that this problem can be formulated as a mixed integer nonlinear programming (MINLP) problem that is NP-hard, in general. By exploiting the fact that actual communication systems have a finite number of available channels, each with a given maximum transmission power, we transfer this MINLP into a binary linear programming problem (BLP). Due to its integrality nature, this BLP is expected to be NP-hard. However, we show that its constraint matrix satisfies the total unimodularity property, and hence our problem can be optimally solved in polynomial time using linear programming (LP). To execute the optimal assignment in a distributed manner, we then present a distributed CSMA/CA-based random access mechanism for CRNs. We compare the performance of our proposed mechanism with reference CSMA/CA channel access mechanisms designed for CRNs. Simulation results show that our proposed mechanism significantly improves the overall network throughput and preserves fairness.

Rate-Maximization Channel Assignment Scheme for Cognitive Radio Networks

In this paper, we consider the coordinated spectrum access problem in a multiuser single-transceiver cognitive radio network (CRN). Our objective is to maximize the sum-rate achieved by all contending cognitive radio users with respect to both spectrum assignment and transmission rate. The problem is posed as a rate-maximization problem subject to hardware and interference constraints. Specifically, we show that this problem can be formulated as an integer linear programming problem (ILP) with unimodular constraint matrix, which can be optimally solved in polynomial time using linear programming. Unlike previous research, our formulation is not restricted to the information-theoretic capacity, and can be applied to any arbitrarily given rate-SINR function. We also develop a distributed CSMA/CA-based MAC protocol for CRNs to realize the optimal assignment in a distributed manner. Simulation results indicate that compared to a reference CSMA/CA CRN MAC protocol, the proposed protocol significantly improves network throughput and preserves fairness.

Opportunistic medium access control for maximizing packet delivery rate in dynamic access networks

One of the key challenges to enabling efficient cognitive radio (CR) communications is how to perform opportunistic medium access control (MAC) that maximizes spectrum efficiency. Several CRN MAC protocols have been designed assuming relatively static primary radio (PR) channels with average idle durations largely exceed CR transmission times. For such CR environment, typical multichannel MAC protocols, which select the best quality channel, perform reasonably well. However, when such mechanism is employed in a CRN that coexists with highly dynamic licensed PR networks (PRNs), where PR channel idle durations are comparable to CR transmission times, the forced-termination rate for CR transmission can significantly increase, leading to a reduction in network throughput. To reduce the forced-termination rate, many MAC protocols have been proposed to account for the dynamic time-varying nature of PR channels by requiring communicating CR users to consistently perform channel switching according to PR activities. However, such channel-switching strategy introduces significant overhead and latency, which negatively affect network throughput. Hence, in this paper, we propose a probabilistic channel quality- and availability-aware CRN MAC. Our protocol uses a novel channel assignment mechanism that attempts at maximizing the packet success probability of each transmission and hence avoids the significant overhead and latency of channel switching. Simulation results show that by being quality- and availability-aware, our protocol provides better spectrum utilization by decreasing the forced-termination rate and improving network throughput.

Cooperative OFDM-Based Virtual Clustering Scheme for Distributed Coordination in Cognitive Radio Networks

Cognitive radio (CR) networks are expected to offer a huge bandwidth to wireless users through dynamic spectrum access techniques. To realize this new network paradigm, effective distributed coordination schemes to exchange control information without assuming the availability of a prespecified common control channel (CCC) are needed. In this paper, we propose a distributed group-based spectrum-aware coordination scheme for carrier-sense multiple access with collision avoidance (CSMA/CA)-based CR networks, which is called virtual clustering distributed coordination (VCDC). By using a CSMA/CA access mechanism, VCDC allows neighboring CR users with a similar view to spectrum opportunities to asynchronously organize themselves into virtual clusters and coordinate their communications using locally available CCCs. VCDC differs from previous cluster-based schemes in that it exploits the discrete orthogonal frequency-division multiplexing (D-OFDM) technology to reduce neighbor-discovery time and facilitate intercluster communication and broadcasting. Three variants of the VCDC scheme are proposed, which are one-hop, two-hop, and constrained VCDC. These variants provide different cluster size based on the number of adopted local CCCs. We compare the performance of the VCDC scheme with existing clustering schemes. Simulation results show that VCDC constructs fewer larger size clusters with an appropriate number of common idle channels and introduces a lower percentage of clusters with no shared idle channels. Thus, VCDC performs better without imposing synchronization.

Adaptive cross-layer MAC design for improved energy-efficiency in multi-channel wireless sensor networks

We present a novel cross-layer design for improving energy efficiency in a wireless sensor network that utilizes a multi-channel non-persistent CSMA MAC protocol with adaptive MQAM modulation at the physical layer. Cross-layer interactions are achieved through joint, traffic-dependent adaptation of the backoff probability at the MAC layer and the modulation order at the physical layer. The joint optimization of the backoff probability and the modulation order is conducted subject to a constraint on the packet retransmission delay. Such an optimization is shown to produce a significant improvement in the per-bit energy requirement for successful packet delivery. Our analytical findings are verified through numerical results and computer simulations.

Probabilistic quality-aware routing in cognitive radio networks under dynamically varying spectrum opportunities

In this paper, we introduce a probabilistic routing metric that considers the peculiar characteristics of the operating environment of cognitive radio networks (CRNs). This metric captures the dynamic changes in channel availabilities due to the randomness of primary users activity and the rich channel diversity due to the fact that a CRN is expected to operate over highly separated frequency channels with different propagation characteristics. Our metric, Probability of Success (PoS), statistically quantifies the chances of a successful cognitive radio (CR) packet transmission over a given channel. Based on the PoS metric, we propose a joint probabilistic routing and channel assignment protocol for multi-hop CRNs that attempts at selecting the path with the maximum probability of success among all possible paths for a given CR source-destination pair. Selecting such a path results in minimizing the number of disruptions to CR packet transmissions, which consequently improves network throughput. Simulation results verify the significant throughput improvement achieved by our protocol compared to reference CRN routing protocols.

Efficient Resource Allocation for Multicell Heterogeneous Cognitive Networks With Varying Spectrum Availability

This paper investigates the problem of designing an efficient spectrum-allocation mechanism in heterogeneous multicell coordinated cognitive radio networks (CRNs) under time-varying channel availabilities and traffic demands across the different cells. The problem is modeled as a utility proportional fair maximization problem subject to traffic demand, spectrum heterogeneity, and exclusive spectrum sharing constraints. Specifically, the optimization problem is formulated as a binary linear programming (BLP) problem. Due to its integrality properties, the BLP is anticipated to be NP-hard. However, this paper proves that the optimal solution of the formulated BLP can be found in polynomial time using linear programming (LP) because of its total unimodular constraint matrix. The proposed solution is a spectrum-aware allocation design that ensures a fair spectrum sharing among cells based on their current traffic loads while considering the unique characteristics of their radio-frequency (RF) environment. Simulation results reveal that the proposed spectrum-aware proportional weighted fair allocation leads to improved system performance while effectively dealing with spectrum heterogeneity and time-varying traffic demands. The results also indicate that the proposed spectrum-allocation design is quite robust to traffic estimation and spectrum sensing errors.