On the Combined Effect of Directional Antennas and Imperfect Spectrum Sensing upon Ergodic Capacity of Cognitive Radio Systems

We consider a cognitive radio system, consisting of a primary transmitter (PUtx), a primary receiver (PUrx), a secondary transmitter (SUtx), and a secondary receiver (SUrx). The secondary users (SUs) are equipped with steerable directional antennas. We assume the SUs and primary users (PUs) coexist and the SUtx knows the geometry of network. We find the ergodic capacity of the channel between SUtx and SUrx , and study how spectrum sensing errors affect the capacity. In our system, the SUtx first senses the spectrum and then transmits data at two power levels, according to the result of sensing. The optimal SUtx transmit power levels and the optimal directions of SUtx transmit antenna and SUrx receive antenna are obtained by maximizing the ergodic capacity, subject to average transmit power and average interference power constraints. To study the effect of fading channel, we considered three scenarios: 1) when SUtx knows fading channels between SUtx and PUrx, PUtx and SUrx, SUtx and SUrx, 2) when SUtx knows only the channel between SUtx and SUrx, and statistics of the other two channels, and, 3) when SUtx only knows the statistics of these three fading channels. For each scenario, we explore the optimal SUtx transmit power levels and the optimal directions of SUtx and SUrx antennas, such that the ergodic capacity is maximized, while the power constraints are satisfied

Wideband Spectrum Sensing in Cognitive Radio Networks

Spectrum sensing is an essential enabling functionality for cognitive radio networks to detect spectrum holes and opportunistically use the under-utilized frequency bands without causing harmful interference to legacy networks. This paper introduces a novel wideband spectrum sensing technique, called multiband joint detection, which jointly detects the signal energy levels over multiple frequency bands rather than consider one band at a time. The proposed strategy is efficient in improving the dynamic spectrum utilization and reducing interference to the primary users. The spectrum sensing problem is formulated as a class of optimization problems in interference limited cognitive radio networks. By exploiting the hidden convexity in the seemingly non-convex problem formulations, optimal solutions for multiband joint detection are obtained under practical conditions. Simulation results show that the proposed spectrum sensing schemes can considerably improve the system performance. This paper establishes important principles for the design of wideband spectrum sensing algorithms in cognitive radio networks

Optimising Cooperative Spectrum Sensing in Cognitive Radio Networks Using Interference Alignment and Space-Time Coding

In this thesis, the process of optimizing Cooperative Spectrum Sensing in Cognitive Radio has been investigated in fast-fading environments where simulation results have shown that its performance is limited by the Probability of Reporting Errors. By proposing a transmit diversity scheme using Differential space-time block codes (D-STBC) where channel state information (CSI) is not required and regarding multiple pairs of Cognitive Radios (CR’s) with single antennas as a virtual MIMO antenna arrays in multiple clusters, Differential space-time coding is applied for the purpose of decision reporting over Rayleigh channels. Both Hard and Soft combination schemes were investigated at the fusion center to reveal performance advantages for Hard combination schemes due to their minimal bandwidth requirements and simplistic implementation. The simulations results show that this optimization process achieves full transmit diversity, albeit with slight performance degradation in terms of power with improvements in performance when compared to conventional Cooperative Spectrum Sensing over non-ideal reporting channels. Further research carried out in this thesis shows performance deficits of Cooperative Spectrum Sensing due to interference on sensing channels of Cognitive Radio. Interference Alignment (IA) being a revolutionary wireless transmission strategy that reduces the impact of interference seems well suited as a strategy that can be used to optimize the performance of Cooperative Spectrum Sensing. The idea of IA is to coordinate multiple transmitters so that their mutual interference aligns at their receivers, facilitating simple interference cancellation techniques. Since its inception, research efforts have primarily been focused on verifying IA’s ability to achieve the maximum degrees of freedom (an approximation of sum capacity), developing algorithms for determining alignment solutions and designing transmission strategies that relax the need for perfect alignment but yield better performance. With the increased deployment of wireless services, CR’s ability to opportunistically sense and access the unused licensed frequency spectrum, without causing harmful interference to the licensed users becomes increasingly diminished, making the concept of introducing IA in CR a very attractive proposition. For a multiuser multiple-input–multiple-output (MIMO) overlay CR network, a space-time opportunistic IA (ST-OIA) technique has been proposed that allows spectrum sharing between a single primary user (PU) and multiple secondary users (SU) while ensuring zero interference to the PUs. With local CSI available at both the transmitters and receivers of SUs, the PU employs a space-time WF (STWF) algorithm to optimize its transmission and in the process, frees up unused eigenmodes that can be exploited by the SU. STWF achieves higher performance than other WF algorithms at low to moderate signal-to-noise ratio (SNR) regimes, which makes it ideal for implementation in CR networks. The SUs align their transmitted signals in such a way their interference impairs only the PU’s unused eigenmodes. For the multiple SUs to further exploit the benefits of Cooperative Spectrum Sensing, it was shown in this thesis that IA would only work when a set of conditions were met. The first condition ensures that the SUs satisfy a zero interference constraint at the PU’s receiver by designing their post-processing matrices such that they are orthogonal to the received signal from the PU link. The second condition ensures a zero interference constraint at both the PU and SUs receivers i.e. the constraint ensures that no interference from the SU transmitters is present at the output of the post-processing matrices of its unintended receivers. The third condition caters for the multiple SUs scenario to ensure interference from multiple SUs are aligned along unused eigenmodes. The SU system is assumed to employ a time division multiple access (TDMA) system such that the Principle of Reciprocity is employed towards optimizing the SUs transmission rates. Since aligning multiple SU transmissions at the PU is always limited by availability of spatial dimensions as well as typical user loads, the third condition proposes a user selection algorithm by the fusion centre (FC), where the SUs are grouped into clusters based on their numbers (i.e. two SUs per cluster) and their proximity to the FC, so that they can be aligned at each PU-Rx. This converts the cognitive IA problem into an unconstrained standard IA problem for a general cognitive system. Given the fact that the optimal power allocation algorithms used to optimize the SUs transmission rates turns out to be an optimal beamformer with multiple eigenbeams, this work initially proposes combining the diversity gain property of STBC, the zero-forcing function of IA and beamforming to optimize the SUs transmission rates. However, this solution requires availability of CSI, and to eliminate the need for this, this work then combines the D-STBC scheme with optimal IA precoders (consisting of beamforming and zero-forcing) to maximize the SUs data rates

Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

ActMesh- A Cognitive Resource Management paradigm for dynamic mobile Internet Access with Reliability Guarantees

Wireless Mesh Networks (WMNs) are going increasing attention as a flexible low-cost networking architecture to provide media Internet access over metropolitan areas to mobile clients requiring multimedia services. In WMNs, Mesh Routers (MRs) from the mesh backbone and accomplish the twofold task of traffic forwarding, as well as providing multimedia access to mobile Mesh Clients (MCs). Due to the intensive bandwidth-resource requested for supporting QoS-demanding multimedia services, performance of the current WMNs is mainly limited by spectrum-crowding and traffic-congestion, as only scarce spectrum-resources is currently licensed for the MCs' access. In principle, this problem could be mitigated by exploiting in a media-friendly (e.g., content-aware) way the context-aware capabilities offered by the Cognitive Radio (CR) paradigm. As integrated exploitation of both content and context-aware system's capabilities is at the basis of our proposed Active Mesh (ActMesh) networking paradigm. This last aims at defining a network-wide architecture for realizing media-friendly Cognitive Mesh nets (e.g., context aware Cognitive Mesh nets). Hence, main contribution of this work is four fold: 1. After introducing main functional blocks of our ActMesh architecture, suitable self-adaptive Belief Propagation and Soft Data Fusion algorithms are designed to provide context-awareness. This is done under both cooperative and noncooperative sensing frameworks. 2. The resulting network-wide resource management problem is modelled as a constrained stochastic Network Utility Maximization (NUM) problem, with the dual (contrasting) objective to maximize spectrum efficiency at the network level, while accounting for the perceived quality of the delivered media flows at the client level. 3. A fully distributed, scalable and self-adaptive implementation of the resulting Active Resource Manager (ARM) is deployed, that explicitly accounts for the energy limits of the battery powered MCs and the effects induced by both fading and client mobility. Due to informationally decentralized architecture of the ActMesh net, the complexity of (possibly, optimal) centralized solutions for resource management becomes prohibitive when number of MCs accessing ActMesh net grow. Furthermore, centralized resource management solutions could required large amounts of time to collect and process the required network information, which, in turn, induce delay that can be unacceptable for delay sensitive media applications, e.g., multimedia streaming. Hence, it is important to develop network-wide ARM policies that are both distributed and scalable by exploiting the radio MCs capabilities to sense, adapt and coordinate themselves. We validate our analytical models via simulation based numerical tests, that support actual effectiveness of the overall ActMesh paradigm, both in terms of objective and subjective performance metrics. In particular, the basic tradeoff among backbone traffic-vs-access traffic arising in the ActMesh net from the bandwidth-efficient opportunistic resource allocation policy pursued by the deployed ARM is numerically characterized. The standardization framework we inspire to is the emerging IEEE 802.16h one