Insoo Koo

Access Strategy for Hybrid Underlay-Overlay Cognitive Radios With Energy Harvesting

In this paper, we consider a hybrid underlay-overlay cognitive radio with energy harvesting. In the considered system, secondary user can harvest energy from the primary users signal as well as from the other ambient sources, such as solar, wind, vibration and so on. Energy is harvested from the primary users signal when the primary channel is found in busy state. The secondary user either operates in one of the two transmission modes; overlay and underlay in order to maximize the throughput, remains in the sleep mode in order to conserve energy, or harvests energy from the primary channel in order to maximize the remaining energy. To maximize long-term throughput of the system, we propose an access strategy in which the partially observable Markov decision process framework is used to determine action of the secondary user, and energy threshold is used to determine the transmission mode (overlay or underlay) of secondary user. Simulations show that for certain values of the system parameters, the considered system provides 60% improved throughput than overlay-only cognitive radio and 43% enhanced throughput than a hybrid cognitive radio system harvesting energy only from the ambient sources. However, increasing the throughput also increases computational burden on the secondary user, which may increase latency and energy requirements of the system.

Erlang capacity of multiaccess systems with service-based access selection

In this letter, we provide the lower and upper bounds of Erlang capacity of multiaccess systems supporting several different radio access technologies in the multiservice scenario, by considering two extreme operation methods; separate and common operation. In a numerical example with GSM/EDGE-like and WCDMA-like subsystems, it is shown that the common operation method can provide up to 60% Erlang capacity improvement over the separate operation method when using a near optimum so-called service-based user assignment scheme, with the combined effects of the assignment and the trunking gains. Even in the worst-case, the common operation method still can provide about 15% capacity improvement over the separate operation method, which mainly comes from the trunking gain.

Cooperative spectrum sensing with collaborative users using individual sensing credibility for cognitive radio network

Cognitive radio (CR) has been considered as one of the promising next-generation communication systems owning to its ability of sensing and making use of vacant channels that are currently unused by licensed users. Reliable spectrum sensing of licensed users is required for CR network to minimize interference to licensed users. However, an individual CR user may find it difficult to reliably detect the activity status of licensed users due to fading and shadowing effects of the channel. In this paper, we propose a cooperative spectrum sensing scheme for collaborative users in which the sensing credibility of each individual user is utilized to improve local and global sensing performance, and reduce the number of reports transmitted through the control channel between CR users and the fusion center (FC). Using this method, few CR users who satisfy the credibility thresholds will transmit their local decisions to the FC one by one according to the states order of their credibility. That is, the CR user with higher reliability will transmit local decision sooner and others with less reliability can use this sensing information to update their local decisions. Finally, all local decisions received at the FC are combined into a global decision using the Chair - Varshney data fusion rule.

Evidence-Theory-Based Cooperative Spectrum Sensing With Efficient Quantization Method in Cognitive Radio

Sensing spectra in a reliable and efficient manner is fundamental to cognitive radio (CR). Ensuring cooperation among spectrum sensing devices is an appropriate method when a CR system is under deep shadowing and in a fading environment. In this paper, an enhanced scheme for cooperative spectrum sensing (CSS) based on efficient quantization and the Dempster-Shafer (D-S) theory of evidence is proposed. The proposed scheme includes an effective quantizer for the sensing data by utilizing special properties of the hypothesis distribution under different signal-to-noise ratios (SNRs) of the primary signal. As a result, the required bandwidth for the reporting channel is reduced while the advantage for combinations of the D-S theory is maintained. Simulation results revealed that significant improvements in the CSS gain, as well as a reduction in the system overhead, were achieved.

Log-likelihood Ratio Optimal Quantizer for Cooperative Spectrum Sensing in Cognitive Radio

In order to reduce the bandwidth requirement for reporting channel, the quantization of sensing datas log-likelihood ratio (LLR) in cooperative spectrum sensing is considered. A well-preserved quantizer which minimizes mean square error of the sensing datas LLR at quantizer output is achieved by applying the well-known Lloyd-Max quantization algorithm. The probability density function of the LLR of the sensing information is also formulated for designing the quantizer. Simulation results reveal that the proposed quantizer provides the same sensing performance of the original LLR test with only few quantization bits.

A sequential cooperative spectrum sensing scheme based on cognitive user reputation

The spectrum sensing plays an essential role in Cognitive Radio (CR), which enables opportunistic access to underutilized licensed spectrums. Cooperative spectrum sensing can help improve sensing performance. However, when the number of cognitive users is large, the latency and network traffic for reporting sensing results to the Fusion Center (FC) become extremely large, which may result in an extended sensing time and collision in the control channel between Cognitive Users (CUs) and the FC. In this paper, we propose an extended Sequential Cooperative Spectrum Sensing (SCSS) scheme in which the reputation of individual CU is used to ensure that the FC efficiently collects local sensing data from CUs. The proposed scheme reduces the number of sensing reports required while improving sensing performance in comparison with the conventional SCSS scheme even when few malicious users exist in the network.

Resource reservation in call admission control schemes for CDMA systems with non-uniform traffic distribution among cells

In this paper, we propose the reservation type call admission control (CAC) scheme for CDMA systems with non-uniform traffic distribution among cells to resolve the intercell unbalanced traffic problem. Differently from a conventional CAC scheme where the system resource is fully allocated to the local users in home cell, the proposed CAC scheme reserves small portion of the system resource for new calls occurring in the neighboring cells instead of fully allowing the local users in home cell to occupy the system resource. As a result, the proposed CAC scheme improves the overall call blocking probability when traffics are non-uniformly distributed among cells. More specifically, the proposed CAC scheme improves the overall call blocking probability by 15% when one cell has 67% more traffic than its surrounding cells.

A cluster-based selective cooperative spectrum sensing scheme in cognitive radio

Developing an effective cooperative spectrum sensing (CSS) scheme in cognitive radio (CR), which is considered as promising system for enhancing spectrum utilization, is necessary. In this paper, a cluster-based optimal selective CSS scheme is proposed for reducing reporting time and bandwidth while maintaining a certain level of sensing performance. Clusters are organized based on the identification of primary signal signal-to-noise ratio value, and the cluster head in each cluster is dynamically chosen according to the sensing data qualities of CR users. The cluster sensing decision is made based on an optimal threshold for selective CSS which minimizes the probability of sensing error. A parallel reporting mechanism based on frequency division is proposed to considerably reduce the time for reporting decision to fusion center of clusters. In the fusion center, the optimal Chair-Vashney rule is utilized to obtain a high sensing performance based on the available cluster’s information.

Multiple QoS support using M-LWDF in OFDMA adaptive resource allocation

In this paper, we consider multiple quality of service (QoS) support by using modified largest weighted delay first (M-LWDF) discipline in the adaptive resource allocation of the orthogonal frequency division multiplexing (OFDM) multiple access (OFDMA) systems. We propose a M-LWDF (M Andrews et al., Feb. 2001) based on subchannel assignment, which can satisfy different QoS requirements of services including delay-sensitive and data rate-sensitive traffics in OFDMA systems. The simulation shows that the proposed M-LWDF based subchannel assignment provides controlled QoS provisions while maintaining both the stability of scheduling discipline and the flexibility of the multiple QoS support.

Performance Analysis of ILEACH and LEACH Protocols for Wireless Sensor Networks

In this paper, we examine the problems of the low energy adaptive clustering hierarchy (LEACH) protocol and present ideas for improvement by selecting the cluster head node. The main problem with LEACH lies in the random selection of cluster heads. There exists a probability that the formed cluster heads are unbalanced and may remain in one part of the network, which makes some part of the network unreachable. In this paper, we present a new version of the LEACH protocol called the improved LEACH (ILEACH) protocol, which a cluster head is selected based on its ratio between the current energy level and an initial energy level, and multiplies by the root square of its number of neighbor nodes. The simulation results show that the proposed ILEACH increases the energy efficiency and network lifetime.