Hyoung-Jin Lim

Deployment and coverage of cognitive radio networks in TV white space

This article presents experimental and simulation results for the use of TV band devices (TVBDs) in TV white space, considering the presence of interference by incumbent services. Digital TV (DTV) services are major incumbent services currently operating in the TV bands. With DTV service, co-channel and adjacent channel deployment scenarios of TVBD networks are introduced. To safely protect the incumbent service, a minimum separation distance from the DTV protected contour, which is called the keep-out distance, is required. We estimate the keep-out distance for different ranges of TVBD transmit antenna height by using several propagation models and measurements of ultra-high-frequency signals in Korea. We also investigate the hidden node problem for the spectrum sensing operation mode of TVBDs. According to the results of these measurements, the hidden node margin should be at least 38 dB in order to protect DTV service. Finally, the service coverage reduction of TVBD networks caused by neighboring DTV service is discussed. It is shown that the service coverage of a wireless local area network system decreases about 50 percent by co-channel interference from neighboring DTV service when the field strength of the DTV received signal is 41 dBu.

Joint Sensing Adaptation and Resource Allocation for Cognitive Radio with Imperfect Sensing

In cognitive radio networks, imperfect spectrum sensing causes harmful interferences or low utilization of unused bands, depending on an access policy of the secondary system. Since these losses have a trade-off relationship, it is hard to decide proper sensing and access policies for the licensed bands. To deal with this problem, we propose a joint algorithm for sensing adaptation and opportunistic resource allocation. The joint optimization problem minimizes the total expected cost of the losses and utilities which are likely generated for the secondary system. To protect the primary system and ensure the secondary systems utility, we employ an average interference threshold constraint and a QoS constraint for the secondary system. Two types of average secondary utilities are considered for the QoS constraint; one is averaged over only transmitted frames and the other is averaged over total frames. Based on energy detection, we derive feasible ranges of sensing threshold to satisfy the constraints. Simulation results show that the proposed scheme dynamically adapts sensing threshold depending on the network environment and minimizes the total cost of the secondary system. In addition, we investigate the performance of the proposed scheme with the two types of the secondary utility.

QoS-constrained opportunistic scheduling for sc-fdma with iterative multiuser detection

This letter proposes a quality-of-service (QoS) constrained opportunistic scheduling for a single-carrier frequency division multiple access (SC-FDMA) scheme. The SC-FDMA scheme considered in this letter employs an iterative multiuser detection using frequency-domain equalization (IMDFDE), which allows several users to share a common set of subcarriers. In order to improve spectral efficiency and guarantee QoS of assigned users, the proposed method chooses users by iteratively performing user selection. At each user selection for a set of subcarriers, the scheduler takes into account multiuser interference from previously assigned users of corresponding subcarriers and QoS constraint. Simulation results show that the proposed method provides higher spectral efficiency compared with round-robin and max-SNR.

Cooperation-Based Dynamic Spectrum Leasing via Multi-Winner Auction of Multiple Bands

In this paper, we study a cooperation-based dynamic spectrum leasing mechanism via multi-winner auction of multiple bands. Based on a second-price auction mechanism, the primary users independently conduct auctions to determine winners who are then granted access to leased bands and prices for those bands. Before auctions, each secondary user jointly chooses bands which they want to lease and generates bids for those bands with a limited transmit power budget. To this end, we determine the feasibility conditions for band selection and for power and time allocation. Further, we propose a low complexity bidding algorithm that iteratively selects a band and calculates the bid for that band. For the paying price among winners after auctions, a multi-objective optimization problem is considered. We derive Pareto optimal solutions and propose paying schemes that prioritize the objectives with pre-defined weighting rules. In addition, the payment and secondary utility are investigated with regard to the number of winners. Simulation results show that secondary users achieve significantly increased utility as more winners are chosen, while primary users are guaranteed a non-negative benefit from spectrum leasing. The power consumed by the secondary users for cooperative transmission is compared for the proposed paying schemes.

Cooperative Spectrum Sensing with Dynamic Threshold Adaptation

Spectrum sensing is a key enabling technology of cognitive radio. Reliable detection increases access opportunity to temporarily unused bands and prevents harmful interference to the licensed users. Due to the receiver noise, signal attenuation, and multi-path fading effect, however, it is usually not possible to determine the existence of primary signal with absolute certainty. By extracting a global decision from shared local sensing results, cooperative sensing achieves high reliability over fading channels. In this paper, we assume that the traffic statistic of primary system is logged into the radio environment map (REM) and can be accessed by the secondary systems. The threshold of each energy detector is dynamically adapted according to the utility values and a priori information from REM. Then, decision results and corresponding operating points are collected by a fusion center, which makes a global decision with high confidence.

Spectral Efficient Multiuser Technique with Channel-Dependent Resource Allocation Schemes

This paper proposes a spectral efficient multiuser scheme for single-carrier transmission. In the proposed scheme, a combination (hybrid) of localized and distributed subcarrier mapping types is employed, where the signals of users with different subcarrier mapping types are superimposed on a common set of subcarriers. We first present mathematical formulations of multiuser detection and derive the equalization coefficients for the hybrid type. In fading environments, the proposed scheme allows users to employ any subcarrier mapping types (localized, distributed, hybrid types), which can support low and high speed users. To estimate the performance of the proposed scheme, we develop a density evolution technique and show that the predicted performances are consistent with simulated performances. Further, based on the performance estimation of the proposed scheme, we discuss channel-dependent resource allocation algorithms: opportunistic scheduling and adaptive modulation and coding (AMC) schemes. These resource allocation algorithms increase the spectral efficiency of the proposed scheme with guaranteed quality-of-service (QoS). Simulation results show that the proposed multiuser scheme achieves both multiuser and frequency diversity gains in fading environments.

Resource Allocation for Mitigating the Effect of Sensing Errors in Cognitive Radio Networks

This letter proposes a resource allocation scheme to mitigate the effect of sensing errors in cognitive radio networks. When a spectrum sensor misses primary signals, the secondary transmission can be interfered with by the primary transmission, whereas the interference to the primary system can be limited to a tolerable level. To deal with this problem, we consider the utility for inaccurate sensing in the proposed resource allocation scheme. Simulation results show that a higher outage performance is achieved by the proposed scheme than the resource allocation scheme that does not consider the utility for inaccurate sensing.

Optimal threshold adaptation with radio environment map for cognitive radio networks

Spectrum sensing is a key enabling technology of cognitive radio. Reliable detection increases access opportunity to temporarily unused bands and prevents harmful interference to the licensed users. Due to the receiver noise, signal attenuation, and multi-path fading effect, however, it is usually not possible to determine the existence of primary signal with absolute certainty. Without the information of primary user activity, Neyman-Pearson criterion has been commonly used to minimize the missed detection probability for a given false alarm rate. In this paper, we assume that the traffic statistic of primary system is logged into the radio environment map (REM) and can be accessed by the secondary system. Considering sensing errors, Bayes criterion is adopted for total utility maximization of primary and secondary systems. The threshold of energy detector is adapted according to the utility values and a priori information from REM, i.e., both false alarm and detection probabilities are dynamically adjusted.

Power Efficient Transceiver Designs for Multi-Cell Coordination in MIMO Cognitive Radio Networks

In cognitive radio networks, multiple secondary systems can access a licensed spectrum when none of the secondary transmitters cause harmful interference to the Primary Users (PUs). For spectrum sharing with coordination among co-located secondary systems, we propose both centralized and distributed beamforming algorithms. The proposed algorithms minimize the total transmit power of secondary systems, while maintaining the interference to PUs below a certain threshold and satisfying the Quality-of-Service (QoS) constraint for each secondary system. The centralized algorithm achieves the optimal transmit power by exploiting the virtual uplink-downlink duality using the knowledge of the channel state information for all the secondary links. However, the assumption of global channel knowledge at each secondary system may not be allowed in practical applications for multi-cell coordination. To address this problem, we design a distributed transceiver beamformer that satisfies the interference constraint to protect PUs. On the basis of this distributed beamformer, we also propose power allocation algorithms that guarantee the QoS for secondary systems. Distributed beamforming and power allocations operate iteratively to minimize the total transmit power. Simulation results show that the distributed algorithms achieve a near-optimal transmit power while satisfying both the QoS and interference constraints.

Power Budget Allocations for Auctions with Multi-Bands in Cooperation-Based Spectrum Leasing

In this paper, we propose power budget allocation algorithms for bidding of auctions in cooperation-based spectrum leasing. The cooperation-based spectrum leasing allows secondary users to dynamically access licensed bands while providing the benefit of cooperative diversity to primary users as a reward. For efficient allocation of the licensed bands to the secondary users, a second-price based multiple auction mechanism is considered. In this mechanism, the secondary users select bands which they want to use and calculate bids for those bands, under a limited transmit power. For the optimal solution of the bidding problem, however, computational complexity increases exponentially with the number of bands. To overcome this problem, we find feasibility conditions for band selection and propose a suboptimal algorithm. The suboptimal algorithm makes bids consisting of the maximum achievable rates for cooperative transmissions. Simulation results show that the primary and secondary users achieve significantly increased achievable rates through spectrum leasing with the proposed algorithms. It is also shown that the performance of the suboptimal algorithm approaches that of the optimal solution as the invested power budget increases.