Rapid　spectrum　usage　in　wireless　networks　may　reduce　energy　efficiency,　requiring　cognitive　radio　net-works　to　be　more　efficient　than　conventional　ones.　Due　to　increased　data　transmission　demand,　cognitive　radio　networks　arose　from　a　lack　of　spectrum　bandwidth.　Spectrum　sensing　and　handoff　decision　are　two　cognitive　radio　network　strategies　that　help　avoid　interference,　channel　access,　and　cohabitation　between　primary　and　secondary　users.　Current　research　focuses　on　handoff　decision　and　cooperative　spectrum　sensing　to　improve　sensing　efficiency　and　system　throughput　while　neglecting　energy　efficiency　and　handoff　latency.　Spectrum　mobility　and　sensing　are　essential　for　energy-efficient　cognitive　radio　net-works.　This　study　provides　a　second　priority　user　transmission　system　using　cooperative　spectrum　sens-ing　to　sense　available　channels.　An　energy　detection　technique　optimizes　the　sensing　process＇s　energy　usage,　leading　to　energy　efficiency.　A　primary　user　traffic　pattern-based　threshold　approach　is　presented　for　spectrum　mobility　management.　A　threshold　approach　is　utilized　to　calculate　probabilistic　stay-and　-wait　and　QoS　handoff　values.　The　transmission　channel　is　selected　using　a　hybrid　handoff　strategy　based　on　dynamic　spectrum　aggregation.　Moreover,　a　cooperative　spectrum　sensing　algorithm　is　described　and　simulated　to　identify　the　optimum　channel　with　the　greatest　throughput　and　minimum　energy　consump-tion.　The　proposed　approach　increases　energy　efficiency　and　throughput　while　maintaining　handoff　delay　and　avoids　miss-detection　and　false　alarm.　This　technique　improves　energy　efficiency,　sensing　perfor-mance,　throughput,　and　handoff　time.　miss-detection.(c)　2022　THE　AUTHORS.　Published　by　Elsevier　BV　on　behalf　of　Faculty　of　Computers　and　Artificial　Intel-ligence,　Cairo　University.　This　is　an　open　access　article　under　the　CC　BY　license　(http://creativecommons.　org/licenses/by/4.0/).