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We have perceived the potentials of spectrum accessing techniques in the cognitive radio networks where the hybrid spectrum access (HSA) is an advanced technique which exploits the interweave and underlay spectrum access strategies simultaneously to enhance the spectral efficiency and throughput. This chapter presents a novel hybrid‐cum‐improved spectrum access technique (HISA) for significant improvement in the throughput, data‐loss rate, and interference at the PU. The spectrum accessing strategies and frame structures are the key elements of the HISA techniques; therefore, the work related to these elements is presented. The proposed frame structures and their combination with HSA are illustrated. The chapter also consists of the mathematical analysis of the throughput and data loss. The throughput and data loss optimization by constraining various metrics is an exigent task which is a potential issue for the future research.” The numerically simulated results of the proposed approach are illustrated and compared with the conventional approach.

The next‐generation communication systems demand huge spectral and energy efficiency, low latency, high scalability, improved connectivity and reliability, as well as advanced security due to massive growth in the wireless connected devices such as internet‐of‐things, wireless sensor networks, wireless body area networks, etc. The prominent and effective approaches to fulfill these demands are the cognitive radio (CR), non‐orthogonal multiple access (NOMA), multi‐antennas or multiple‐input‐multiple‐output, cooperative communication, network function virtualization, millimeter‐wave communication, ultra‐classification, etc. This chapter proposes the potential CR‐NOMA frameworks with the implementation challenges and future research directions. It presents the spectrum accessing strategies in CR. The chapter comprises the fundamentals of NOMA. The chapter also presents the prominent frameworks of NOMA in CR for uplink and downlink scenarios. It also comprises the challenging issues in CR‐NOMA frameworks and their recommended solutions.

After perceiving the idle channels using spectrum sensing, the cognitive user (CU) accesses these channels using suitable medium access control (MAC) protocol where the decision on optimal spectrum sensing, transmission time, and proper coordination with other CUs are the key characteristics of the MAC protocol. In the conventional MAC protocol, the CUs exploit the common control channel for the spectrum sensing information exchange in order to negotiate the channel access. After the spectrum sensing, each CU contends for the access of idle channel using various spectrum access protocols. The system model and proposed hybrid self‐scheduling multichannel‐MAC (HSMC‐MAC) protocol are illustrated. The chapter consists of the performance analysis of proposed protocol for the perfect and imperfect spectrum sensing scenarios. It presents the simulation results for the perfect and imperfect spectrum sensing scenarios. An improved frame structure for the distributed cognitive radio networks is proposed in order to enhance the throughput by exploiting the spectrum efficiently.

Due to the random spectrum sensing of channels in cognitive radio networks, the probability of channel to be sensed active is significantly high, resulting in high data loss due to which the effective throughput of the network decreases significantly. In this chapter, the challenging issues regarding the selection of channel for spectrum sensing after spectrum prediction are exploited to enhance the throughput of cognitive user (CU). First, the chapter illustrates the system model for the proposed approach. The expressions of throughput are then presented. Next, the chapter discusses the simulation results and finally discusses the future scope. A new approach for additional enhancement in the throughput of CU by exploiting the underlay communication in the spectrum sensing and prediction phases is presented and the results are compared with pre‐obtained results of Approach‐1. The results are evidence for the significant improvement in the throughput by using this approach.

The PU channels are highly utilized in the high‐traffic cognitive radio networks (HTCRNs) which results the decrease in the idle probability of channels. In this chapter, the concepts of spectrum prediction and hybrid spectrum access techniques are explored to improve the throughput by alleviating the spectrum sensing errors. Moreover, in the data transmission phase, the cognitive user (CU) transmits data only on the idle sensed channels whereas it needs to wait on the active sensed channels which cause the problem of wait/switch/stop states. To conquer the issue of wait states, a novel approach is proposed in which the hybrid spectrum access technique named as Approach‐1 is exploited. Moreover, the concept of spectrum monitoring during the data transmission period is exploited to lighten the data loss of CU and interference‐at‐PU, and this is named as Approach‐2. The performance analysis of the proposed system models is illustrated. Further, the simulation results and analysis are presented.