We present an analytical framework for modeling a priority-based load balancing scheme in cellular networks based on a new algorithm called direct retry with truncated offloading channel resource pool (DRK). The model, developed for a baseline case of two cell network, differs in many respects from previous works on load balancing. Foremost, it incorporates the call admission process, through random access. In specific, the proposed model implements the Physical Random Access Channel used in 3GPP network standards. Furthermore, the proposed model allows the differentiation of users based on their priorities. The quantitative results illustrate that, for example, cellular network operators can control the manner in which traffic is offloaded between neighboring cells by simply adjusting the length of the random access phase. Our analysis also allows for the quantitative determination of the blocking probability individual users will experience given a specific length of random access phase. Furthermore, we observe that the improvement in blocking probability per shared channel for load balanced users using (DRK) is maximized at an intermediate number of shared channels, as opposed to the maximum number of these shared resources. This occurs because a balance is achieved between the number of users requesting connections and those that are already admitted to the network. We also present an extension of our analytical model to a multicell network (by means of an approximation) and an application of the proposed load balancing scheme in the context of opportunistic spectrum access.

In this paper we propose an analytical framework which allows the investigation of the average channel throughput at the medium access control (MAC) layer for opportunistic spectrum access (OSA) networks with channel bonding enabled. We show that channel bonding is beneficial in certain cases only (e.g. low primary user traffic), though the extent of the benefit depend on the features of the OSA network including secondary network size and the total number of channels available for bonding.

Transmission over multiple frequency bands combined into one logical channel speeds up data transfer for wireless networks. On the other hand, the allocation of multiple channels to a single user decreases the probability of finding a free logical channel for new connections, which may result in a network-wide throughput loss. While this relationship has been studied experimentally, especially in the WLAN configuration, little is known on how to analytically model such phenomena. With the advent of Opportunistic Spectrum Access (OSA) networks, it is even more important to understand the circumstances in which it is beneficial to bond channels occupied by primary users with dynamic duty cycle patterns. In this paper we propose an analytical framework which allows the investigation of the average channel throughput at the medium access control layer for OSA networks with channel bonding enabled. We show that channel bonding is generally beneficial, though the extent of the benefits depend on the features of the OSA network, including OSA network size and the total number of channels available for bonding. In addition, we show that performance benefits can be realized by adaptively changing the number of bonded channels depending on network conditions. Finally, we evaluate channel bonding considering physical layer constraints, i.e. throughput reduction compared to the theoretical throughput of a single virtual channel due to a transmission power limit for any bonding size.

We present an analytical framework for modeling a priority-based load balancing scheme in cellular networks. The model differs in many respects from previous work on load balancing, in particular by incorporating the call admission process, through random access; allowing differentiation of users based on their priorities; and by incorporating the received signal properties. The analysis illustrates that, for example, ignoring channel quality has a non- negligible impact on the performance of load balancing. Moreover, the system model allows for the scenario-based determination of whether blocking probability or collision probability (during call admission) is the more dominant factor in the degradation of the performance of UEs affected by load balancing.

Characterizing the number and type of transmitters occupying a given frequency band is a critical aspect of spectrum sensing specifically and cognitive radio generally. We present an analytical framework based on probability to identify the number of frequency hopping transmitters of one specific type in a band of interest, and show that the probability mass functions associated with the different potential number of transmitters quickly becomes Gaussian as the number of channel observations increases. Simulation results confirm that the approach can lead with high probability to a correct decision regarding the number of interferers. Thus, the methods here can serve as a valuable complement to other spectrum sensing approaches.