You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Survey on coexistence of heterogeneous wireless networks in 2.4 GHz and TV white spaces 
Chapter Title:  Other CR coexistence mechanisms 
1. Abstract of Cited Paper (BIB001):  The ISM spectrum is becoming increasingly populated by emerging wireless networks. Spectrum sharing among the same network of devices can be arbitrated by MAC protocols (e.g., CSMA), but the coexistence between heterogeneous networks remains a challenge. The disparate power levels, asynchronous time slots, and incompatible PHY layers of heterogeneous networks severely degrade the effectiveness of traditional MAC. In this paper, we propose a new mechanism, called the Cooperative Busy Tone (CBT), that enables the reliable coexistence between two such networks, ZigBee and WiFi. CBT allows a separate ZigBee node to schedule a busy tone concurrently with the desired transmission, thereby improving the visibility of ZigBee devices to WiFi. Its core components include a frequency flip scheme that prevents the mutual interference between cooperative ZigBee nodes, and a busy tone scheduler that minimizes the interference to WiFi, for both CSMA and TDMA packets. To optimize CBT, we establish an analytical framework that relates its key design parameters to performance and cost. Both the analytical and detailed simulation results demonstrate CBT's significant throughput improvement over the legacy ZigBee protocol, with negligible performance loss to WiFi. The results are validated further by implementing CBT on sensor motes and software radios. 
2. Abstract of Cited Paper (BIB002):  Spectrum sensing plays a critical role in cognitive radio networks (CRNs). The majority of spectrum sensing algorithms aim to detect the existence of a signal on a channel, i.e., they classify a channel into either busy or idle state, referred to as a two-state sensing model in this paper. While this model works properly when there is only one CRN accessing a channel, it significantly limits the potential and fairness of spectrum access when there are multiple co-existing CRNs. This is because if the secondary users (SUs) from one CRN are accessing a channel, SUs from other CRNs would detect the channel as busy and hence be starved. In this paper, we propose a three-state sensing model that distinguishes the channel into three states: idle, occupied by a primary user, or occupied by a secondary user. This model effectively addresses the fairness concern of the two-state sensing model, and resolves the starvation problem of multiple co-existing CRNs. To accurately detect each state of the three, we develop a two-stage detection procedure. In the first stage, energy detection is employed to identify whether a channel is idle or occupied. If the channel is occupied, the received signal is further analyzed at the second stage to determine whether the signal originates from a primary user or an SU. For the second stage, we design a statistical model and use it for distance estimation. For detection performance, false alarm and miss detection probabilities are theoretically analyzed. Furthermore, we thoroughly analyze the performance of throughput and fairness for the three-state sensing model compared with the two-state sensing model. In terms of fairness, we define a novel performance metric called all-level fairness for all(ALFA) to characterize fairness among CRNs. Extensive simulations are carried out under various scenarios to evaluate the three-state sensing model and verify the aforementioned theoretical analysis. 
3. Abstract of Cited Paper (BIB003):  A number of wireless standards (e.g., IEEE 802.11af and IEEE 802.22) have been developed or are currently being developed for enabling opportunistic access in TV white space (TVWS) using cognitive radio (CR) technology. When heterogeneous CR networks that are based on different wireless standards operate in the same TVWS, coexistence issues can potentially cause major problems. Enabling collaborative coexistence via direct coordination between heterogeneous CR networks is very challenging due to incompatible MAC/PHY designs of coexisting networks. Moreover, the direct coordination would require competing networks or service providers to exchange sensitive control information that may raise conflict of interest issues and customer privacy concerns. In this paper, we present an architecture for enabling collaborative coexistence of heterogeneous CR networks over TVWS, called Symbiotic Heterogeneous coexistence ARchitecturE (SHARE). By mimicking the symbiotic relationships (i.e., the interspecific competition process) between heterogeneous organisms in a stable ecosystem, SHARE establishes an indirect coordination mechanism for spectrum sharing between heterogeneous CR networks via a mediator system, which avoids the drawbacks of direct coordination. Analytical and simulation results show that SHARE allocates spectrum among coexisting networks in a weighted-fair manner without any inter-network direct coordination. 
4. Abstract of Cited Paper (BIB004):  Cognitive radio is viewed as a disruptive technology innovation to improve spectrum efficiency. The deployment of coexisting cognitive radio networks, however, raises a great challenge to the medium access control (MAC) protocol design. While there have been many MAC protocols developed for cognitive radio networks, most of them have not considered the coexistence of cognitive radio networks, and thus do not provide a mechanism to ensure fair and efficient coexistence of cognitive radio networks. In this paper, we introduce a novel MAC protocol, termed fairness-oriented media access control (FMAC), to address the dynamic availability of channels and achieve fair and efficient coexistence of cognitive radio networks. Different from the existing MACs, FMAC utilizes a three-state spectrum sensing model to distinguish whether a busy channel is being used by a primary user or a secondary user from an adjacent cognitive radio network. As a result, secondary users from coexisting cognitive radio networks are able to share the channel together, and hence to achieve fair and efficient coexistence. We develop an analytical model using two-level Markov chain to analyze the performance of FMAC including throughput and fairness. Numerical results verify that FMAC is able to significantly improve the fairness of coexisting cognitive radio networks while maintaining a high throughput. 
5. Abstract of Cited Paper (BIB005):  Cognitive radio (CR) technologies have led to several wireless standards (e.g., IEEE 802.11af and IEEE 802.22) that enable secondary networks to access the TV white-space (TVWS) spectrum. Different unlicensed wireless technologies with different PHY/MAC designs are expected to coexist in the same TVWS spectrum-we refer to such a situation as heterogeneous coexistence. The heterogeneity of the PHY/MAC designs of coexisting CR networks can potentially exacerbate the hidden terminal problem. This problem cannot be addressed by the conventional handshaking/coordination mechanism between two homogeneous networks employing the same radio access technology. In this paper, we present a coexistence protocol, called Spectrum Sharing for Heterogeneous Coexistence (SHARE), that mitigates the hidden terminal problem for the coexistence between two types of networks: one that employs a time-division-multiplexing-based MAC protocol and one that employs a carrier-sense-multiple-access-based MAC protocol. Specifically, SHARE utilizes beacon transmissions and dynamic quiet periods to avoid packet collisions caused by the hidden terminals. Our analytical and simulation results show that SHARE reduces the number of packet collisions and guarantees weighted fairness in partitioning the spectrum among the coexisting secondary networks. 
6. Abstract of Cited Paper (BIB006):  Compared to the homogeneous coexistence problems studied in previous chapters, the coexistence of heterogeneous wireless systems in TV “white space” (TVWS) is a more challenging issue to address. 
7. Abstract of Cited Paper (BIB007):  Coexistence protocols enable collocated cognitive radio networks (CRNs) to share the spectrum in an opportunistic manner. These protocols work under the assumption that all spectrum bands provide the same level of throughput. This assumption is however limited in scope because channel conditions as well as the licensee's usage of allocated channels can vary significantly with time and space. Under these circumstances, CRNs are expected to have a preference over the choice of available channels which can lead to an imbalance in contention for disparate channels, degraded quality of service, and an overall inefficient utilization of spectrum resource. In this paper, we analyze this situation from a game theoretic perspective and model the coexistence of CRNs with heterogeneous spectrum as a non-cooperative, repeated spectrum sharing game. We derive three solutions for the game; (1) pure and (2) mixed strategy Nash Equilibria as well as (3) centralized and distributed correlated equilibria which are derived using linear programming and a channel selection learning algorithms, respectively. We also analyze each of these solutions from the perspective of fairness and efficiency. To that end, we utilize the concept of price of anarchy to measure the efficiency of these solutions under selfish behavior from CRNs.

Literature Review:
In this subsection, we survey other novel coexistence solutions proposed by the research community. These solutions are mainly concentrated on the coordination among secondary networks and the coexistence with primary networks, which are surveyed as follows. As pointed out in section 'Introduction', one of the design challenges of heterogeneous network coexistence mechanism is the asymmetry in transmission power, which may cause the hidden terminal problem. The hidden terminal problem is particularly challenging if the nodes involved belong to two heterogeneous networks in terms of network protocols. In this regard, Bian et al. BIB006 developed a novel protocol to solve the hidden terminal problem between a Time-division multiplexing (TDM)-based CR network and a CSMA-based CR network in TVWSs, a typical coexistence scenario. The coexistence scenario is illustrated in Figure 11 . The TDM-based network has long-duration superframes and quite period (QP). The CSMA-based network has short time slots and CSMA frames have short sensing operation time, so that they can fit in the QP of the TDM superframes. In the work by Bian et al., BIB006 a coexistence protocol Spectrum sHARing for heterogeneous coexistencE (SHARE) is proposed to address the hidden terminal problem in the following two cases: Avoiding collision at CSMA receivers: By approximating the packet arrival time of CSMA-based networks using Poisson distribution, BIB002 BIB001 Bian et al. BIB006 develop the collision avoidance algorithm to avoid collision at CSMA receivers. Specifically, each TDM transmitter estimates the CSMA packet transmission frame length and then configures the QP termination time to keep silence for one more CSMA packet transmission or terminate QP for TDM packets transmission. To ensure the fairness in terms of channel access time between the TDM-based network and the CSMA network, a weight-fairness maintenance mechanism is designed in SHARE to adjust the channel access time of the two networks by adding or removing additional time slots in future QPs. Avoiding collision at TDM receivers: A beacon transmission mechanism is provided in SHARE to avoid collisions at TDM receivers. Specifically, SHARE lets TDM receivers broadcast short beacon signals at the beginning of each time slot to inform CSMA nodes to suspend data transmission. Since the TDM frame duration is fixed, the estimation of transmitting duration for CSMA nodes is feasible. The configuration of BPs in SHARE also takes into account the channel conditions via estimation. Bian and colleagues BIB004 BIB007 presented an ecologyinspired framework, Symbiotic Heterogeneous coexistence ARchitecturE (SHARE), to coordinate heterogeneous network coexistence. The core idea comes from the similarity of the interaction between heterogeneous networks and that between ecology species in ecosystems (symbiotic relation). Specifically, two types of biological algorithms are developed under the symbiotic framework to address the coexistence problem: First, an ecology-inspired spectrum share allocation algorithm is proposed in which by analogizing classical Lotka-Volterra (L-V) predator-prey model where N i represents the population size of predator, and K i is the maximized population size of species i. While a i,j indicates mutual impacts between species i and j, r i indexes intrinsic rate of increase. The spectrum bandwidths which are needed by CR networks could be transformed as predators' population, and total spectrum shared by heterogeneous networks is similar to prey's amount. Hence, a fair spectrum competition mechanism is constructed. Second, a foraging-based channel selection algorithm is introduced to coordinate coexistence. Based on the analogies between animals' foraging behaviours and channel selection process, the algorithm enables CR network agents to select appropriate channels to reach an equilibrium point of the whole system. However, Amjad et al. BIB008 provided a novel coexistence protocol for heterogeneous CR WSNs with game theory on frequency and time dimensions. As shown in Figure 12 , suppose three heterogeneous CR networks (CRN 1, CRN 2 and CRN 3) coexistence with three channels for communication. Then, coexistence scenarios could become Because the quality of channel 1 is the best, selfish channel selection mechanism in these networks would cause congestion as shown in Figure 12 (a). Even heterogeneous CR networks employ ordinary fair spectrum resources allocation mechanism, and results are also hard to avoid data transmission collisions perfectly as shown in Figure 12 (b). In this case, Amjad et al. BIB008 split different CR network frames into unified time slots and introduce the pure and mixed strategy Nash equilibria game solution which is called correlated equilibrium on the evaluation of relationship between unified data frames and channels selection, so that fair and efficient communication resources distribution could be realized as shown in Figure 12 . A particularity that makes the coexistence of CR networks challenging is the presence of PUs. In this regard, Zhao and colleagues BIB005 BIB003 developed a suite of solutions to address the coexistence problem between CR networks under the presence of PUs. More specifically, a fairness-oriented media access control (FMAC) protocol is proposed that mainly contains two components: A cooperative spectrum sensing mechanism is proposed to estimate the location of the PU under the assumption that the location of PUs is fixed and already known by cognitive nodes. In such context, the distance between the primary transmitter and an SU can be estimated through signal strength received by the SU receiver. Mathematically, it is well known that if three CR users measure the distance between them and the PU, the location of the PU can be calculated as shown in Figure 13 . Then, the primary Figure 12 . Channel access pattern of CR Networks: (a) selfish behaviour from CR networks for best quality channel (channel 1) will always result in a collision, (b) fair distribution of spectrum resource when CR networks mix their choice of channels and (c) fair and efficient resource distribution with correlated equilibrium. signal can be distinguished from a secondary signal. Once the primary signal is distinguished, a threestate sensing model is proposed to classify the sensed channel occupation states, as shown in equation   where x s is the emitted signal strength of an SU, x p is the emitted signal strength of a PU and n i is zeromean additive white Gaussian noise (AWGN). The three-state model classifies the channel states into H 0 (idle), H 1 (occupied by a PU) and H 2 (occupied by a SU). If a PU is present, the SU transmission should be refrained. Otherwise, the secondary network can compete for the occupation of channel with other secondary networks. The solutions proposed by Zhao and colleagues BIB005 BIB003 consist of MAC protocols for coexisting CR networks. The major drawbacks are the assumption that the PUs' locations are fixed and the prior knowledge on the PU locations, which limit their application.