Matlab垂直切换仿真实例代码解析

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资源摘要信息: "extended_vertical_handover.zip是一个包含MATLAB例程的压缩文件,专门用于研究和实现垂直切换的概念。垂直切换是指在移动通信系统中,移动设备在不同接入技术之间进行切换的过程,如从蜂窝网络切换到Wi-Fi,或者从Wi-Fi切换到蓝牙等。这种切换策略在异构网络环境中尤为重要,旨在改善用户的服务质量,平衡网络负载,以及优化资源使用。MATLAB作为一种高级数学计算和仿真软件,经常被用于通信系统的建模和分析中,通过提供强大的算法开发和数据可视化工具,使得研究人员能够更有效地设计和测试通信系统中的切换机制。该文件中的'extended_vertical_handover'脚本或函数可能是为了实现特定的垂直切换算法或场景模拟而设计的,而'license.txt'则可能包含了软件使用许可的相关信息。" 从标题和描述中我们可以提取出以下知识点: 1. 垂直切换(Vertical Handover)的概念及其在移动通信系统中的应用。 2. 异构网络环境(Heterogeneous Network Environment)中垂直切换的重要性。 3. MATLAB软件在通信系统建模和分析中的应用。 4. 通信系统中的算法开发和数据可视化。 5. MATLAB例程在垂直切换场景模拟中的具体应用。 6. 研究垂直切换可能涉及的关键技术,如服务质量(Quality of Service, QoS)的改善、网络负载的平衡以及资源使用的优化。 垂直切换是无线通信网络中的关键技术之一,其主要目的是确保用户在不同类型的网络间切换时,能够无缝地、不间断地继续进行通信,并且在切换的过程中提供尽可能优质的通信体验。为了实现这一目标,垂直切换需要考虑的因素包括但不限于信号强度、网络拥塞程度、用户的移动速度、服务质量要求、成本、用户的偏好设置等。 异构网络环境通常由多种接入技术组成,例如2G/3G/4G/5G蜂窝网络、Wi-Fi、蓝牙、WiMAX等。在这样的环境下,为了选择最佳的接入技术,垂直切换机制会执行一系列的操作,包括监测、测量、决策、执行等。监测是指系统对当前可用网络资源的状态进行实时跟踪;测量是指对这些资源进行性能评估;决策是指根据测量结果和一定的切换策略来选择最佳的接入技术;执行是指完成从一个网络到另一个网络的切换动作。 MATLAB提供了丰富的工具箱(Toolboxes),用于通信系统的模拟和分析,例如通信系统工具箱(Communications System Toolbox)、信号处理工具箱(Signal Processing Toolbox)等。通过这些工具箱,研究人员能够快速地构建复杂的通信系统模型,设计信号处理算法,进行性能评估和优化,并将结果以图形化的方式展现出来。这对于验证垂直切换策略和算法的性能至关重要。 "extended_vertical_handover"作为压缩包中的核心文件,可能包含实现某种特定垂直切换算法的MATLAB脚本或函数。考虑到文件标题中的"extended"一词,我们可以推断该例程可能是对现有垂直切换技术的扩展或改进,可能包括更为复杂的决策算法,更加精细的网络状态监测机制,或者对切换过程的优化处理等。 最后,"license.txt"文件通常包含了软件的授权使用条款和条件。由于MATLAB是商业软件,使用时需要遵守相应的许可协议。这可能涉及到软件的安装、分发、修改和转售等权利的界定,确保用户合法合规地使用MATLAB软件及其工具箱。 总结来说,该压缩文件"extended_vertical_handover.zip"可能包含了实现垂直切换机制的MATLAB例程,以及相关授权信息。通过分析这些文件,研究人员和工程师可以进一步学习和改进垂直切换策略,为异构网络环境下的通信质量优化提供支持。

def draw_stats(self, vals, vals1, vals2, vals3, vals4, vals5, vals6): self.ax1 = plt.subplot(self.gs[0, 0]) self.ax1.plot(vals) self.ax1.set_xlim(self.xlim) locs = self.ax1.get_xticks() locs[0] = self.xlim[0] locs[-1] = self.xlim[1] self.ax1.set_xticks(locs) self.ax1.use_sticky_edges = False self.ax1.set_title(f'Connected Clients Ratio') self.ax2 = plt.subplot(self.gs[1, 0]) self.ax2.plot(vals1) self.ax2.set_xlim(self.xlim) self.ax2.set_xticks(locs) self.ax2.yaxis.set_major_formatter(FuncFormatter(format_bps)) self.ax2.use_sticky_edges = False self.ax2.set_title('Total Bandwidth Usage') self.ax3 = plt.subplot(self.gs[2, 0]) self.ax3.plot(vals2) self.ax3.set_xlim(self.xlim) self.ax3.set_xticks(locs) self.ax3.use_sticky_edges = False self.ax3.set_title('Bandwidth Usage Ratio in Slices (Averaged)') self.ax4 = plt.subplot(self.gs[3, 0]) self.ax4.plot(vals3) self.ax4.set_xlim(self.xlim) self.ax4.set_xticks(locs) self.ax4.use_sticky_edges = False self.ax4.set_title('Client Count Ratio per Slice') self.ax5 = plt.subplot(self.gs[0, 1]) self.ax5.plot(vals4) self.ax5.set_xlim(self.xlim) self.ax5.set_xticks(locs) self.ax5.use_sticky_edges = False self.ax5.set_title('Coverage Ratio') self.ax6 = plt.subplot(self.gs[1, 1]) self.ax6.plot(vals5) self.ax6.set_xlim(self.xlim) self.ax6.set_xticks(locs) self.ax6.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax6.use_sticky_edges = False self.ax6.set_title('Block ratio') self.ax7 = plt.subplot(self.gs[2, 1]) self.ax7.plot(vals6) self.ax7.set_xlim(self.xlim) self.ax7.set_xticks(locs) self.ax7.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax7.use_sticky_edges = False self.ax7.set_title('Handover ratio')修改为一张张输出图片

2023-06-02 上传

def connect(self): s = self.get_slice() if self.connected: return # increment connect attempt self.stat_collector.incr_connect_attempt(self) if s.is_avaliable(): s.connected_users += 1 self.connected = True print(f'[{int(self.env.now)}] Client_{self.pk} [{self.x}, {self.y}] connected to slice={self.get_slice()} @ {self.base_station}') return True else: self.assign_closest_base_station(exclude=[self.base_station.pk]) if self.base_station is not None and self.get_slice().is_avaliable(): # handover self.stat_collector.incr_handover_count(self) elif self.base_station is not None: # block self.stat_collector.incr_block_count(self) else: pass # uncovered print(f'[{int(self.env.now)}] Client_{self.pk} [{self.x}, {self.y}] connection refused to slice={self.get_slice()} @ {self.base_station}') return False def disconnect(self): if self.connected == False: print(f'[{int(self.env.now)}] Client_{self.pk} [{self.x}, {self.y}] is already disconnected from slice={self.get_slice()} @ {self.base_station}') else: slice = self.get_slice() slice.connected_users -= 1 self.connected = False print(f'[{int(self.env.now)}] Client_{self.pk} [{self.x}, {self.y}] disconnected from slice={self.get_slice()} @ {self.base_station}') return not self.connected def start_consume(self): s = self.get_slice() amount = min(s.get_consumable_share(), self.usage_remaining) # Allocate resource and consume ongoing usage with given bandwidth s.capacity.get(amount) print(f'[{int(self.env.now)}] Client_{self.pk} [{self.x}, {self.y}] gets {amount} usage.') self.last_usage = amount def release_consume(self): s = self.get_slice() # Put the resource back if self.last_usage > 0: # note: s.capacity.put cannot take 0 s.capacity.put(self.last_usage) print(f'[{int(self.env.now)}] Client_{self.pk} [{self.x}, {self.y}] puts back {self.last_usage} usage.') self.total_consume_time += 1 self.total_usage += self.last_usage self.usage_remaining -= self.last_usage self.last_usage = 0中的资源分配

2023-06-01 上传

def draw_stats(self, vals, vals1, vals2, vals3, vals4, vals5, vals6): self.ax1 = plt.subplot(self.gs[0, 0]) self.ax1.plot(vals) self.ax1.set_xlim(self.xlim) locs = self.ax1.get_xticks() locs[0] = self.xlim[0] locs[-1] = self.xlim[1] self.ax1.set_xticks(locs) self.ax1.use_sticky_edges = False self.ax1.set_title(f'Connected Clients Ratio') self.ax2 = plt.subplot(self.gs[1, 0]) self.ax2.plot(vals1) self.ax2.set_xlim(self.xlim) self.ax2.set_xticks(locs) self.ax2.yaxis.set_major_formatter(FuncFormatter(format_bps)) self.ax2.use_sticky_edges = False self.ax2.set_title('Total Bandwidth Usage') self.ax3 = plt.subplot(self.gs[2, 0]) self.ax3.plot(vals2) self.ax3.set_xlim(self.xlim) self.ax3.set_xticks(locs) self.ax3.use_sticky_edges = False self.ax3.set_title('Bandwidth Usage Ratio in Slices (Averaged)') self.ax4 = plt.subplot(self.gs[3, 0]) self.ax4.plot(vals3) self.ax4.set_xlim(self.xlim) self.ax4.set_xticks(locs) self.ax4.use_sticky_edges = False self.ax4.set_title('Client Count Ratio per Slice') self.ax5 = plt.subplot(self.gs[0, 1]) self.ax5.plot(vals4) self.ax5.set_xlim(self.xlim) self.ax5.set_xticks(locs) self.ax5.use_sticky_edges = False self.ax5.set_title('Coverage Ratio') self.ax6 = plt.subplot(self.gs[1, 1]) self.ax6.plot(vals5) self.ax6.set_xlim(self.xlim) self.ax6.set_xticks(locs) self.ax6.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax6.use_sticky_edges = False self.ax6.set_title('Block ratio') self.ax7 = plt.subplot(self.gs[2, 1]) self.ax7.plot(vals6) self.ax7.set_xlim(self.xlim) self.ax7.set_xticks(locs) self.ax7.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax7.use_sticky_edges = False self.ax7.set_title('Handover ratio') self.ax8 = plt.subplot(self.gs[3, 1]) row_labels = [ 'Initial number of clients', 'Average connected clients', 'Average bandwidth usage', 'Average load factor of slices', 'Average coverage ratio', 'Average block ratio', 'Average handover ratio', ] l, r = self.xlim cell_text = [ [f'{len(self.clients)}'], [f'{mean(vals[l:r]):.2f}'], [f'{format_bps(mean(vals1[l:r]), return_float=True)}'], [f'{mean(vals2[l:r]):.2f}'], [f'{mean(vals4[l:r]):.2f}'], [f'{mean(vals5[l:r]):.4f}'], [f'{mean(vals6[l:r]):.4f}'], ] self.ax8.axis('off') self.ax8.axis('tight') self.ax8.tick_params(axis='x', which='major', pad=15) self.ax8.table(cellText=cell_text, rowLabels=row_labels, colWidths=[0.35, 0.2], loc='center right') plt.tight_layout() 更改为只输出其中的第一行第一列的图片

2023-06-02 上传

def draw_stats(self, vals, vals1, vals2, vals3, vals4, vals5, vals6): self.ax1 = plt.subplot(self.gs[0, 0]) self.ax1.plot(vals) self.ax1.set_xlim(self.xlim) locs = self.ax1.get_xticks() locs[0] = self.xlim[0] locs[-1] = self.xlim[1] self.ax1.set_xticks(locs) self.ax1.use_sticky_edges = False self.ax1.set_title(f'Connected Clients Ratio') self.ax2 = plt.subplot(self.gs[1, 0]) self.ax2.plot(vals1) self.ax2.set_xlim(self.xlim) self.ax2.set_xticks(locs) self.ax2.yaxis.set_major_formatter(FuncFormatter(format_bps)) self.ax2.use_sticky_edges = False self.ax2.set_title('Total Bandwidth Usage') self.ax3 = plt.subplot(self.gs[2, 0]) self.ax3.plot(vals2) self.ax3.set_xlim(self.xlim) self.ax3.set_xticks(locs) self.ax3.use_sticky_edges = False self.ax3.set_title('Bandwidth Usage Ratio in Slices (Averaged)') self.ax4 = plt.subplot(self.gs[3, 0]) self.ax4.plot(vals3) self.ax4.set_xlim(self.xlim) self.ax4.set_xticks(locs) self.ax4.use_sticky_edges = False self.ax4.set_title('Client Count Ratio per Slice') self.ax5 = plt.subplot(self.gs[0, 1]) self.ax5.plot(vals4) self.ax5.set_xlim(self.xlim) self.ax5.set_xticks(locs) self.ax5.use_sticky_edges = False self.ax5.set_title('Coverage Ratio') self.ax6 = plt.subplot(self.gs[1, 1]) self.ax6.plot(vals5) self.ax6.set_xlim(self.xlim) self.ax6.set_xticks(locs) self.ax6.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax6.use_sticky_edges = False self.ax6.set_title('Block ratio') self.ax7 = plt.subplot(self.gs[2, 1]) self.ax7.plot(vals6) self.ax7.set_xlim(self.xlim) self.ax7.set_xticks(locs) self.ax7.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax7.use_sticky_edges = False self.ax7.set_title('Handover ratio') 能否改为一张张图片输出

2023-06-02 上传