In this study, a contextual multi-armed bandit (CMAB)-based decentralized channel exploration framework disentangling a channel utility function (i.e., reward) with respect to contending neighboring access points (APs) is proposed. The proposed framework enables APs to evaluate observed rewards compositionally for contending APs, allowing both robustness against reward fluctuation due to neighboring APs' varying channels and assessment of even unexplored channels. To realize this framework, we propose contention-driven feature extraction (CDFE), which extracts the adjacency relation among APs under contention and forms the basis for expressing reward functions in disentangled form, that is, a linear combination of parameters associated with neighboring APs under contention). This allows the CMAB to be leveraged with a joint linear upper confidence bound (JLinUCB) exploration and to delve into the effectiveness of the proposed framework. Moreover, we address the problem of non-convergence — the channel exploration cycle — by proposing a penalized JLinUCB (P-JLinUCB) based on the key idea of introducing a discount parameter to the reward for exploiting a different channel before and after the learning round. Numerical evaluations confirm that the proposed method allows APs to assess the channel quality robustly against reward fluctuations by CDFE and achieves better convergence properties by P-JLinUCB.

With the widespread diffusion of Internet of Things (IoT), the number of applications using wireless sensor devices are increasing, and Quality of Service (QoS) required for these applications is diversifying. Thus, it becomes difficult to satisfy a variety of QoS with a single wireless system, and many kinds of wireless systems are working in the same domains; time, frequency, and place. This paper considers coexistence environments of ZigBee and Wi-Fi networks, which use the same frequency band channels, in the same place. In such coexistence environments,ZigBee devices suffer radio interference from Wi-Fi networks, which results in severe ZigBee packet losses because the transmission power of Wi-Fi is much higher than that of ZigBee. Many existing methods to avoid interference from Wi-Fi networks focus on only one of time, frequency, or space domain. However, such avoidance in one domain is insufficient particularly in near future IoT environments where more ZigBee devices and Wi-Fi stations transfer more amount of data. Therefore, in this paper, we propose joint channel allocation and routing in both frequency and space domains. Finally, we show the effectiveness of the proposed method by computer simulation.

A spectrum suppressed transmission that increases the frequency utilization efficiency, defined as throughput/bandwidth, by suppressing the required bandwidth has been proposed. This is one of the most effective schemes to solve the exhaustion problem of frequency bandwidths. However, in spectrum suppressed transmission, its transmission quality potentially degrades due to the ISI making the bandwidth narrower than the Nyquist bandwidth. In this paper, in order to improve the transmission quality degradation, we propose the spectrum suppressed transmission applying both FEC (forward error correction) and LE (linear equalization). Moreover, we also propose a new channel allocation scheme for the spectrum suppressed transmission, in multi-channel environments over a satellite transponder. From our computer simulation results, we clarify that the proposed schemes are more effective at increasing the system throughput than the scheme without spectrum suppression.

In this work, we address a joint energy efficiency (EE) and throughput optimization problem in interweave cognitive radio networks (CRNs) subject to scheduling, power, and stability constraints, which could be solved through traffic admission control, channel allocation, and power allocation. Specifically, the joint objective is to concurrently optimize the system EE and the throughput of secondary user (SU), while satisfying the minimum throughput requirement of primary user (PU), the throughput constraint of SU, and the scheduling and power control constraints that must be considered. To achieve these goals, our algorithm independently and simultaneously makes control decisions on admission and transmission to maximize a joint utility of EE and throughput under time-varying conditions of channel and traffic without a priori knowledge. Specially, the proposed scheduling algorithm has polynomial time efficiency, and the power control algorithms as well as the admission control algorithm involved are simply threshold-based and thus very computationally efficient. Finally, numerical analyses show that our proposals achieve both system stability and optimal utility.

This paper proposes a dynamic spectrum controlled (DSTC) channel allocation algorithm to increase the total throughput of satellite communication (SATCOM) systems. To effectively use satellite resources such as the satellite's maximum transponder bandwidth and maximum transmission power and to handle the propagation gain variation at all earth stations, the DSTC algorithm uses two new transmission techniques: spectrum compression and spectrum division. The algorithm controls various transmission parameters, such as the spectrum compression ratio, number of spectrum divisions, combination of modulation method and FEC coding rate (MODCOD), transmission power, and spectrum bandwidth to ensure a constant transmission bit rate under variable propagation conditions. Simulation results show that the DSTC algorithm achieves up to 1.6 times higher throughput than a simple MODCOD-based algorithm.

Radio over Fiber (RoF) is a promising solution for providing wireless access services. Heterogeneous radio signals are transferred via an optical fiber link using an analog transmission technique. When the RoF and the radio frequency (RF) devices have a nonlinear characteristic, these will create the intermodulation products (IMPs) in the system and generate the intermodulation distortion (IMD). In this paper, the IMD interference in the uplink RF signals from the coupling effect between the downlink and the uplink antennas has been addressed. We propose a method using the dynamic channel allocation (DCA) algorithm with the predistortion (PD) technique to improve the throughput performance of the multi-channel RoF system. The carrier to distortion plus noise power ratio (CDNR) is evaluated for all channel allocation combinations; then the best channel combination is assigned as a set of active channels to minimize the effect of IMD. The results show that the DCA with PD has the lowest IMD and obtains a better throughput performance.

Cognitive radio has been developed recently as a promising solution to tackle the spectrum related issues such as spectrum scarcity and spectrum underutilization. Cognitive spectrum assignment is necessary for allocating spectrum bands to secondary users in order to avoid conflicts among secondary users and maximize the total network performance under a given set of conditions. In most spectrum assignment schemes, throughput is considered as the main criterion for spectrum selection or spectrum assignment. In this paper, we propose a distortion-aware channel allocation scheme for multiple secondary users who compete for primary channels to transmit multimedia data. In the proposed scheme, idle spectrum bands are assigned to the multimedia secondary users that attain the highest video distortion reduction. The scheme is expected to mitigate the selfish behaviors of users in competing channels. The performance effectiveness of our proposed channel allocation scheme is demonstrated through simulation by comparing with a benchmark of two reference spectrum assignment schemes.

This paper proposes a new channel allocation algorithm for satellite communication systems. The algorithm is based on a spectrum division transmission technique as well as a spectrum compression transmission technique that we have developed in separate pieces of work. Using these techniques, the algorithm optimizes the spectrum bandwidth and a MODCOD (modulation and FEC error coding rate) scheme to balance the usable amount of satellite transponder bandwidth and satellite transmission power. Moreover, it determines the center frequency and bandwidth of each divided subspectra depending on the unused bandwidth of the satellite transponder bandwidth. As a result, the proposed algorithm enables flexible and effective usage of satellite resources (bandwidth and power) in channel allocations and thus enhances satellite communication (SATCOM) system capacity.

This paper proposes a novel satellite channel allocation algorithm for a demand assigned multiple access (DAMA) controller. In satellite communication systems, the channels' total bandwidth and total power are limited by the satellite's transponder bandwidth and transmission power (satellite resources). Our algorithm is based on multi-carrier transmission and adaptive modulation methods. It optimizes channel elements such as the number of sub-carriers, modulation level, and forward error correction (FEC) coding rate. As a result, the satellite's transponder bandwidth and transmission power can be simultaneously used to the maximum and the overall system capacity, i.e., total transmission bit rate, will increase. Simulation results show that our algorithm increases the overall system capacity by 1.3 times compared with the conventional fixed modulation algorithm.

This paper proposed three channel aggregation schemes for cognitive radio networks, a constant channel aggregation scheme, a probability distribution-based variable channel aggregation scheme, and a residual channel-based variable channel aggregation scheme. A cognitive radio network can have a wide bandwidth if unused channels in the primary networks are aggregated. Channel aggregation schemes involve either constant channel aggregation or variable channel aggregation. In this paper, a Markov chain is used to develop an analytical model of channel aggregation schemes; and the performance of the model is evaluated in terms of the average sojourn time, the average throughput, the forced termination probability, and the blocking probability. Simulation results show that channel aggregation schemes can reduce the average sojourn time of cognitive users by increasing the channel occupation rate of unused channels in a primary network.

Efficient resource allocation for delay-sensitive traffic, such as telephony and video streaming, in Orthogonal Frequency Division Multiple Access (OFDMA) networks is needed to increase system performance. In our system, users try to achieve a low queuing delay and buffer space usage by competing for transmission over the subchannels. We formulate this problem as a bargaining game and use the Nash Bargaining Solution (NBS) to realize a fair and efficient subchannel allocation for the users. Simulation results show performance improvements, with regard to packet dropping and delay distribution, over other algorithms.

This paper proposes a new Ad-Hoc network system which comprises the multiple relay access points (APs) with multi channels. Ad-Hoc network systems are recently proposed and incorporated for the communication infrastructure, which relays wireless transmission among access points (APs) in wireless LAN (WLAN) system. System throughput is decreased due to hidden terminal problem when only a single channel is used for the Ad-Hoc network. In order to solve this problem, a new system with multi channels is proposed. However, even if the multi channels are employed, the co- and/or adjacent-channel interference occurs due to hidden terminal problem and multiple APs in a limited space, when considering a simultaneous transmit and reception at the relay AP. In this paper, we develop an Ad-Hoc network testbed which can reduce and avoid co- and/or adjacent-channel interference by using vertically arranged antenna configuration and distributed channel allocation scheme. Moreover, the effectiveness of our testbed is clarified by applying actual WLAN signals.

This paper presents a novel dynamic subchannel allocation scheme that can improve the cell capacity by coordinating the intercell interference (ICI) in a cellular orthogonal frequency division multiple access (OFDMA) system. The proposed scheme mitigates the ICI by adopting the virtual cell concept and improves the frequency reuse factor through subchannel reuse among different virtual cells. In particular, each virtual cell is assigned a primary and a secondary subchannel group, and each sector base station (BSs) allocates the subchannel resulting in the least ICI in probability out of the candidate subchannels to the mobile stations, dynamically searching from its primary group and then secondary group. In addition, an optional use of pico-cell overlay at the intersection of the virtual cells is also proposed to enhance the fairness of the proposed scheme with the BS-MS distance. Through computer simulation, it is shown that the proposed scheme has the advantages of improved cell capacity and fairness compared to the conventional schemes.

Based on game theory, a distributed power control algorithm with sequential subchannel nulling is proposed for ad-hoc networks. It is shown that the proposed method, by sharing subchannels appropriately according to the interference profiles, can reduce the power consumption of the network while satisfying the target rate of each link.

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

OFDMA femtocells in the macrocellular network of which frequency reuse factor is 1 cause serious interference to macrocell users, while the femtocells improve the performance of indoor users. In this letter, a novel downlink resource allocation algorithm for OFDMA femtocell networks is proposed to reduce interference between the macrocells and the femtocells. This algorithm allocates femtocell subchannels to avoid interference to macrocell users in the femtocell coverage, and minimizes the total transmission power of the femtocell to reduce the negative effect on the performance of the macrocell. Simulation results are provided to present the performance of the proposed algorithm.

This paper describes a novel channel allocation scheme that enables data to be collected from observation points throughout the ultra-wide area covered by a satellite communication system. Most of the earth stations in the system acquire pre-scheduled type data such as that pertaining to rainfall and temperature measurements, but a few of them acquire event-driven type data such as that pertaining to earthquakes. Therefore, the main issue pertaining to this scheme is how to effectively accommodate demand for the channels by a huge number of earth stations with limited satellite frequency bandwidth regardless of their acquired data types. To tackle this issue, we propose a channel allocation scheme built on a pre-assigned scheme to gather pre-scheduled type data but that also includes an additional procedure to gather event-driven type data reliably. Performance evaluations show that the proposed scheme achieves higher throughput and lower packet loss rate than conventional schemes.

Cooperation can increase the system performance by obtaining the spatial diversity. While most of the present works concentrate on the analysis of the cooperation based on the inter-user channel response and developing a scheme for higher cooperative diversity, in this paper, we focus on practical resource allocation in OFDMA systems. Since the user who uses the same center frequency can not receive the signal when transmitting, this constraint should be considered to apply the cooperation to OFDMA systems. In this paper, we propose the pair-based OFDMA frame structure that overcomes this constraint. Also in this frame structure to achieve the minimum outage probability of system, we select the best partner among the candidate neighbors and allocate the suitable subchannels to bandwidth requested users through a cooperative subchannel allocation (CSA) algorithm. In order to evaluate the proposed resource allocation scheme, we carry out simulations based on IEEE 802.16e. The simulation results show that our proposed algorithm offers smaller outage probability than one based on non-cooperative communications and we get the minimum outage probability when a threshold for selection of candidate neighbors is 10 dB. We analyze that these results can be achieved by helping users located around the edge of the cell.

Wireless Mesh Network (WMN) is a promising model with benefits in coverage extension and throughput improvement. In WMN, multiple channels are available for improving system performance through concurrent transmission. For maximum utilization, per-node channel quality and inter-channel interference should be considered in multi-channel assignment. We propose a new multi-channel assignment method. First, we model the mesh network connectivity after a multi-graph which has multiple edges between two nodes. From this connectivity graph, we generate a multi-channel conflict graph, then we allocate multiple channels so that they do not overlap, using list coloring algorithm. We also propose a new sub-graph list coloring algorithm to enhance channel allocation performance. From computer simulations, we verify the performance of the algorithm.

In this letter, we propose an efficient scheme for combining scheduling and channel allocation functions in multi-channel systems such as an orthogonal frequency division multiple access (OFDMA). In our approach, the scheduling function is embedded in the channel allocation function in an implicit manner, and the implicit scheduler only translates quality-of-service (QoS) requirements into a set of constraints on channel allocation. The channel allocation problem is then formulated as a linear programming (LP) problem, and the optimal solution can be easily obtained through various LP algorithms. Through extensive numerical experiments, it is demonstrated that the proposed scheme can maximize the cell throughput under the given QoS requirements.