diff --git a/ivy/functional/backends/paddle/experimental/layers.py b/ivy/functional/backends/paddle/experimental/layers.py
index 1369a98b8d6b3..f41f61af07ecf 100644
--- a/ivy/functional/backends/paddle/experimental/layers.py
+++ b/ivy/functional/backends/paddle/experimental/layers.py
@@ -477,6 +477,27 @@ def rfftn(
     return result.astype("complex128")
 
 
+@with_supported_dtypes(
+    {
+        "2.5.1 and below": (
+            "complex64",
+            "complex128",
+        )
+    },
+    backend_version,
+)
+def hfftn(
+    x: paddle.Tensor,
+    s: Optional[Union[int, Tuple[int]]] = None,
+    axes: Optional[Union[int, Tuple[int]]] = None,
+    *,
+    norm: Optional[str] = "backward",
+    out: Optional[paddle.Tensor] = None,
+) -> paddle.Tensor:
+    result = paddle.fft.hfftn(x, s, axes, norm)
+    return result
+
+
 @with_supported_dtypes(
     {
         "2.5.1 and below": (
diff --git a/ivy/functional/frontends/paddle/fft.py b/ivy/functional/frontends/paddle/fft.py
index 4355c8d954eef..c172d819b93f5 100644
--- a/ivy/functional/frontends/paddle/fft.py
+++ b/ivy/functional/frontends/paddle/fft.py
@@ -131,3 +131,18 @@ def rfftfreq(n, d=1.0, dtype=None, name=None):
     pos_max = n // 2 + 1
     indices = ivy.arange(0, pos_max, dtype=dtype)
     return indices * val
+
+
+@with_supported_dtypes(
+    {
+        "2.5.1 and below": (
+            "complex64",
+            "complex128",
+        )
+    },
+    "paddle",
+)
+@to_ivy_arrays_and_back
+def hfftn(x, n=None, axis=None, norm="backward", name=None):
+    result = ivy.hfftn(x, axis, n=n, norm=norm)
+    return ivy.real(result)
\ No newline at end of file
diff --git a/ivy/functional/ivy/experimental/layers.py b/ivy/functional/ivy/experimental/layers.py
index 8b8db56bd375c..587179b01693a 100644
--- a/ivy/functional/ivy/experimental/layers.py
+++ b/ivy/functional/ivy/experimental/layers.py
@@ -1193,6 +1193,51 @@ def ifft(
     return ivy.current_backend(x).ifft(x, dim, norm=norm, n=n, out=out)
 
 
+@handle_exceptions
+@handle_backend_invalid
+@handle_nestable
+@handle_array_like_without_promotion
+@handle_out_argument
+@to_native_arrays_and_back
+@handle_device_shifting
+def hfftn(
+    x: Union[ivy.Array, ivy.NativeArray],
+    dim: int,
+    /,
+    *,
+    s: Optional[Union[int, Tuple[int, ...]]] = None,
+    norm: str = "backward",
+    n: Optional[Union[int, Tuple[int]]] = None,
+    out: Optional[ivy.Array] = None,
+) -> ivy.Array:
+    r"""
+    Compute the FFT of a signal that has Hermitian symmetry, a real spectrum.
+
+    Parameters
+    ----------
+        x
+            The input data. It's a Tensor type. It's a complex.
+        n
+            The length of the output transform axis. 
+        axis
+            Axis used to calculate FFT. If not specified, the last axis
+            is used by default.
+        norm
+            Indicates which direction to scale the `forward` or `backward` transform
+            pair and what normalization factor to use. The parameter value must be one
+            of "forward" or "backward" or "ortho". Default is "backward".
+        name
+            The default value is None.  Normally there is no need for user to set
+            this property. For more information, please refer to :ref:`api_guide_Name` .
+
+    Returns
+    -------
+    ret
+        The result of HFFTN operation.
+    """
+    return ivy.current_backend(x).hfftn(x, s, dim, norm=norm, n=n, out=out)
+
+
 @handle_exceptions
 @handle_backend_invalid
 @handle_nestable