## 4 Resource Management in Heterogeneous Network (RM HetNet)
### Spectrum Allocation (SA)
#### 4.4.3. Tera Hertz (THz)  
In this section, we provide a summary of the THz frequency bands. We also highlight the exceptional characteristics of the THz frequency region. While the bands above the THz band have been extensively investigated, the THz band remains one of the least studied zones in the SA. In [138], the authors investigated the resource allocation problem in D2D-based underlay 6G HetNets in an uplink scenario. The purpose of this article is to enhance the available spectrum utilization. A decentralized resource allocation strategy based on deep reinforcement learning and federated learning is proposed to increase the network throughput and reduce power consumption while guaranteeing both cellular and D2D users' QoS. For a more realistic simulation of the dynamic network nature, they considered cellular and D2D users equally when allocating transmission resources under a decentralized paradigm and considered users' mobility inside the base station's coverage area. Simulations are performed to evaluate the suggested schemes' effectiveness in the 5G mm-wave and 6G THz scenarios and compared with the baseline methods. Simulation results demonstrate that the proposed approach effectively optimizes network performance in terms of power consumption and throughput. However, realistic mobility models need to be considered. The authors proposed optimum resource allocation methods to optimize the effective capacity in the THz band over energy harvesting-based HetNets in the limited block length scenario for the delay and error-rate constrained QoS provisioning in [139]. They developed models of energy harvesting-based THz-band nano-communication systems within the finite block length range. Afterward, they used the finite block length coding method to analyze the interference, channel dispersion functions, and channel capacity in the THz-band. In order to support massive ultra-reliable low latency communications over finite block length coding energy harvesting based HetNets, they developed and tackled the effective capacity maximization problem. Attenuation is often attributed to the transmission medium's spreading loss and shadow-fading properties. Detailed simulation results are provided to verify and assess their proposed THz band schemes over HetNets. Nevertheless, the network energy consumption needs more consideration and investigation. In [140], the authors investigated the waveform design for ultra-broadband combined radar sensing and communication systems operating in the mmWave and THz bands. For target sensing, they presented a novel Multi-Sub band Quasi-Perfect (MS-QP) sequence comprised of several perfect subsequences on various sub-bands; this allows for precise target range and velocity estimates with just a cost-effectively low rate for sequence detection. In addition, each perfect subsequence's root index is created to minimize the effect of high Doppler shift on radar detection. Lastly, a data-embedded MS-QP (DE-MS-QP) waveform is built by extending the MS-QP sequence in the time domain, which creates null frequency points on each sub-band for data transmission. The suggested DE-MS-QP waveform, which inherits all the benefits from MS-QP sequences, allows for simultaneous interference-free sensing and communication, unlike the co-existence-based joint radar sensing and communication system in the time-domain duplex (TDD) approach. In the simulations, the suggested waveforms were numerically shown to be better than existing methods in terms of communication and sensing performance, implementation cost, and flexibility of spectrum allocation between the functions. Nonetheless, imperfect channel state information needs to be investigated. In [141], they investigated the spectrum allocation for THz band communication systems in HetNets while considering THz channels' frequency and distance dependence. They investigated multi-band-based spectrum allocation with adaptive sub-band bandwidth by dividing the desired spectrum into subbands with uneven bandwidths.