diff --git a/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h
index df3cad6..4be8c17 100644
--- a/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2020 Arm Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -47,8 +47,8 @@
     /** Set the input, weights, biases and output tensors.
      *
      * @param[in,out] input        Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
-     * @param[in]     weights      The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
-     * @param[in]     bias         (Optional) The biases have one dimension. Data type supported: Same as @p input.
+     * @param[in]     weights      The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
+     * @param[in]     bias         (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
      * @param[out]    output       Output tensor. The output has the same number of dimensions as the @p input.
      * @param[in]     deconv_info  Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
      * @param[in]     weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel.
@@ -59,8 +59,8 @@
      *
      * @param[in]     compile_context The compile context to be used.
      * @param[in,out] input           Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
-     * @param[in]     weights         The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
-     * @param[in]     bias            (Optional) The biases have one dimension. Data type supported: Same as @p input.
+     * @param[in]     weights         The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
+     * @param[in]     bias            (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
      * @param[out]    output          Output tensor. The output has the same number of dimensions as the @p input.
      * @param[in]     deconv_info     Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
      * @param[in]     weights_info    (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel.
@@ -71,8 +71,8 @@
     /** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayer
      *
      * @param[in] input        Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
-     * @param[in] weights      The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
-     * @param[in] bias         (Optional) The biases have one dimension. Data type supported: Same as @p input.
+     * @param[in] weights      The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
+     * @param[in] bias         (Optional) The biases have one dimension. Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
      * @param[in] output       Output tensor info. The output has the same number of dimensions as the @p input.
      * @param[in] deconv_info  Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo.
      * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel.
diff --git a/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h
index 232b9f5..a23500e 100644
--- a/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2020 Arm Limited.
+ * Copyright (c) 2019-2021 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -89,7 +89,7 @@
      *
      * @param[in,out] input        Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
      *                             Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
-     * @param[in]     weights      The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
+     * @param[in]     weights      The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
      * @param[in]     bias         (Optional) The biases have one dimension.
      *                             Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
      * @param[out]    output       Output tensor. The output has the same number of dimensions as the @p input.
@@ -103,7 +103,7 @@
      * @param[in]     compile_context The compile context to be used.
      * @param[in,out] input           Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
      *                                Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
-     * @param[in]     weights         The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
+     * @param[in]     weights         The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
      * @param[in]     bias            (Optional) The biases have one dimension.
      *                                Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
      * @param[out]    output          Output tensor. The output has the same number of dimensions as the @p input.
@@ -117,7 +117,7 @@
      *
      * @param[in] input        Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
      *                         Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
-     * @param[in] weights      The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
+     * @param[in] weights      The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input or QSYMM8_PER_CHANNEL if @p input is QASYMM8/QASYMM8_SIGNED.
      * @param[in] bias         (Optional) The biases have one dimension.
      *                         Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
      * @param[in] output       Output tensor info. The output has the same number of dimensions as the @p input.
diff --git a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
index 75f34cc..9188487 100644
--- a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2020 Arm Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -105,6 +105,11 @@
 {
     ARM_COMPUTE_UNUSED(output, bias, weights_info);
 
+    if(is_data_type_quantized_per_channel(weights->data_type()))
+    {
+        return DeconvolutionMethod::DIRECT;
+    }
+
     const DataLayout data_layout = input->data_layout();
 
     const size_t idx_w = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
diff --git a/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp
index d802ef2..00d9a9e 100644
--- a/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLDirectDeconvolutionLayer.cpp
@@ -74,7 +74,12 @@
 
     const TensorShape output_shape = compute_deconvolution_output_shape(out_dims, *input, *weights);
 
-    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights);
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+
+    if(input->data_type() != weights->data_type())
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON(weights->data_type() != DataType::QSYMM8_PER_CHANNEL || !is_data_type_quantized_asymmetric(input->data_type()));
+    }
 
     if(bias != nullptr)
     {
@@ -227,7 +232,6 @@
         {
             _weights_flipped.allocator()->free();
         }
-
         _is_prepared = true;
     }
 }
diff --git a/tests/validation/CL/DeconvolutionLayer.cpp b/tests/validation/CL/DeconvolutionLayer.cpp
index c284cdc..15962b5 100644
--- a/tests/validation/CL/DeconvolutionLayer.cpp
+++ b/tests/validation/CL/DeconvolutionLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2020 Arm Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -87,34 +87,34 @@
 // *INDENT-OFF*
 // clang-format off
 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(
-    framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),   // Mismatching data type
-                                            TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),   // Invalid weights shape
-                                            TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),   // Non supported data type
-                                            TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),  // Invalid bias shape
-                                            TensorInfo(TensorShape(13U, 11U, 4U, 3U), 1, DataType::F32), // Window shrink
-                                            TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32),
-                                          }),
+    framework::dataset::make("InputInfo",   { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),   // Mismatching data type
+                                              TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),   // Invalid weights shape
+                                              TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),   // Non supported data type
+                                              TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),  // Invalid bias shape
+                                              TensorInfo(TensorShape(13U, 11U, 4U, 3U), 1, DataType::F32), // Window shrink
+                                              TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32),
+                                            }),
     framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16),
-                                            TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16),
-                                            TensorInfo(TensorShape(3U, 2U, 2U, 2U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(3U, 3U, 4U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16),
+                                              TensorInfo(TensorShape(3U, 2U, 2U, 2U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(3U, 3U, 4U), 1, DataType::F32),
                                               TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32),
-                                          })),
-    framework::dataset::make("BiasInfo",  { TensorInfo(TensorShape(1U), 1, DataType::F16),
-                                            TensorInfo(TensorShape(1U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(1U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(25U, 11U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(1U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(4U), 1, DataType::F32),
-                                          })),
-    framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16),
-                                            TensorInfo(TensorShape(25U, 10U, 2U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(13U, 13U, 2U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(11U, 9U, 1U, 3U), 1, DataType::F32),
-                                            TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32),
-                                          })),
+                                            })),
+    framework::dataset::make("BiasInfo",    { TensorInfo(TensorShape(1U), 1, DataType::F16),
+                                              TensorInfo(TensorShape(1U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(1U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(25U, 11U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(1U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(4U), 1, DataType::F32),
+                                            })),
+    framework::dataset::make("OutputInfo",  { TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16),
+                                              TensorInfo(TensorShape(25U, 10U, 2U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(13U, 13U, 2U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(11U, 9U, 1U, 3U), 1, DataType::F32),
+                                              TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32),
+                                            })),
     framework::dataset::make("PadStrideInfo", { PadStrideInfo(1, 1, 0, 0),
                                                 PadStrideInfo(1, 1, 0, 0),
                                                 PadStrideInfo(1, 1, 0, 0),
@@ -286,6 +286,18 @@
 template <typename T>
 using CLDeconvolutionLayerQuantizedFixture1x1 = DeconvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, 1, 1>;
 
+template <typename T>
+using CLDeconvolutionLayerQuantizedPerChannelFixture4x4 = DeconvolutionValidationQuantizedPerChannelFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, int8_t, 4, 4>;
+
+template <typename T>
+using CLDeconvolutionLayerQuantizedPerChannelFixture3x3 = DeconvolutionValidationQuantizedPerChannelFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, int8_t, 3, 3>;
+
+template <typename T>
+using CLDeconvolutionLayerQuantizedPerChannelFixture2x2 = DeconvolutionValidationQuantizedPerChannelFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, int8_t, 2, 2>;
+
+template <typename T>
+using CLDeconvolutionLayerQuantizedPerChannelFixture1x1 = DeconvolutionValidationQuantizedPerChannelFixture<CLTensor, CLAccessor, CLDeconvolutionLayer, T, int8_t, 1, 1>;
+
 TEST_SUITE(Quantized)
 TEST_SUITE(QASYMM8)
 
@@ -414,8 +426,8 @@
 TEST_SUITE_END() // W2x2
 
 TEST_SUITE(W1x1) // DirectDeconvolution and GEMMDeconvolution
-FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerQuantizedFixture1x1<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(data1x1, framework::dataset::make("DataType",
-                                                                                                                      DataType::QASYMM8_SIGNED)),
+FIXTURE_DATA_TEST_CASE(Run, CLDeconvolutionLayerQuantizedFixture1x1<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(data1x1,
+                                                                                                                      framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
                                                                                                                       data_layouts_dataset),
                                                                                                                       framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 0), QuantizationInfo(2.f / 255.f, 0) })),
                                                                                                                       framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 0), QuantizationInfo(4.f / 255.f, 0) })),
@@ -428,6 +440,115 @@
 
 TEST_SUITE_END() // QASYMM8_SIGNED
 
+const auto input_qinfo_dataset         = framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 10) });
+const auto output_qinfo_dataset        = framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 0) });
+const auto input_signed_qinfo_dataset  = framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, -10) });
+const auto output_signed_qinfo_dataset = framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 10) });
+
+TEST_SUITE(QSYMM8_PER_CHANNEL)
+
+TEST_SUITE(W4x4)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedPerChannelFixture4x4<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data4x4,
+                       framework::dataset::make("DataType", DataType::QASYMM8)),
+                       data_layouts_dataset),
+                       input_qinfo_dataset),
+                       output_qinfo_dataset),
+                       add_bias_dataset),
+                       framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunSmallSigned, CLDeconvolutionLayerQuantizedPerChannelFixture4x4<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data4x4,
+                       framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+                       data_layouts_dataset),
+                       input_signed_qinfo_dataset),
+                       output_signed_qinfo_dataset),
+                       add_bias_dataset),
+                       framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+TEST_SUITE_END() // W4x4
+
+TEST_SUITE(W3x3)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedPerChannelFixture3x3<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data3x3,
+                       framework::dataset::make("DataType", DataType::QASYMM8)),
+                       data_layouts_dataset),
+                       input_qinfo_dataset),
+                       output_qinfo_dataset),
+                       add_bias_dataset),
+                       framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunSmallSigned, CLDeconvolutionLayerQuantizedPerChannelFixture3x3<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data3x3,
+                       framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+                       data_layouts_dataset),
+                       input_signed_qinfo_dataset),
+                       output_signed_qinfo_dataset),
+                       add_bias_dataset),
+                       framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+TEST_SUITE_END() // W3x3
+
+TEST_SUITE(W2x2)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedPerChannelFixture2x2<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data2x2_precommit,
+                       framework::dataset::make("DataType", DataType::QASYMM8)),
+                       data_layouts_dataset),
+                       input_qinfo_dataset),
+                       output_qinfo_dataset),
+                       add_bias_dataset),
+                       framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunSmallSigned, CLDeconvolutionLayerQuantizedPerChannelFixture2x2<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data2x2_precommit,
+                       framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+                       data_layouts_dataset),
+                       input_signed_qinfo_dataset),
+                       output_signed_qinfo_dataset),
+                       add_bias_dataset),
+                       framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+TEST_SUITE_END() // W2x2
+
+TEST_SUITE(W1x1)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDeconvolutionLayerQuantizedPerChannelFixture1x1<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data1x1,
+                       framework::dataset::make("DataType", DataType::QASYMM8)),
+                       data_layouts_dataset),
+                       input_qinfo_dataset),
+                       output_qinfo_dataset),
+                       add_bias_dataset),
+                       framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunSmallSigned, CLDeconvolutionLayerQuantizedPerChannelFixture1x1<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data1x1,
+                       framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+                       data_layouts_dataset),
+                       input_signed_qinfo_dataset),
+                       output_signed_qinfo_dataset),
+                       add_bias_dataset),
+                       framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance_qasymm8, tolerance_num);
+}
+TEST_SUITE_END() // W1x1
+
+TEST_SUITE_END() // QSYMM8_PER_CHANNEL
+
 TEST_SUITE_END() // Quantized
 
 TEST_SUITE_END() // DeconvolutionLayer
diff --git a/tests/validation/NEON/DeconvolutionLayer.cpp b/tests/validation/NEON/DeconvolutionLayer.cpp
index 4c6ee26..19bd742 100644
--- a/tests/validation/NEON/DeconvolutionLayer.cpp
+++ b/tests/validation/NEON/DeconvolutionLayer.cpp
@@ -395,14 +395,19 @@
 
 TEST_SUITE_END() // QASYMM8_SIGNED
 
+const auto input_qinfo_per_channel_dataset         = framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, 10) });
+const auto output_qinfo_per_channel_dataset        = framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 0) });
+const auto input_signed_qinfo_per_channel_dataset  = framework::dataset::make("InputQuantizationInfo", { QuantizationInfo(1.f / 255.f, -10) });
+const auto output_signed_qinfo_per_channel_dataset = framework::dataset::make("OutputQuantizationInfo", { QuantizationInfo(3.f / 255.f, 10) });
+
 TEST_SUITE(QSYMM8_PER_CHANNEL)
 
 TEST_SUITE(W4x4)
 FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerQuantizedPerChannelFixture4x4<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data4x4,
                        framework::dataset::make("DataType", DataType::QASYMM8)),
                        data_layouts_dataset),
-                       input_qinfo_dataset),
-                       output_qinfo_dataset),
+                       input_qinfo_per_channel_dataset),
+                       output_qinfo_per_channel_dataset),
                        add_bias_dataset),
                        framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
 {
@@ -412,8 +417,8 @@
 FIXTURE_DATA_TEST_CASE(RunSigned, NEDeconvolutionLayerQuantizedPerChannelFixture4x4<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data4x4,
                        framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
                        data_layouts_dataset),
-                       input_qinfo_dataset),
-                       output_qinfo_dataset),
+                       input_signed_qinfo_per_channel_dataset),
+                       output_signed_qinfo_per_channel_dataset),
                        add_bias_dataset),
                        framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
 {
@@ -426,8 +431,8 @@
 FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerQuantizedPerChannelFixture3x3<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data3x3,
                        framework::dataset::make("DataType", DataType::QASYMM8)),
                        data_layouts_dataset),
-                       input_qinfo_dataset),
-                       output_qinfo_dataset),
+                       input_qinfo_per_channel_dataset),
+                       output_qinfo_per_channel_dataset),
                        add_bias_dataset),
                        framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
 {
@@ -437,8 +442,8 @@
 FIXTURE_DATA_TEST_CASE(RunSigned, NEDeconvolutionLayerQuantizedPerChannelFixture3x3<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data3x3,
                        framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
                        data_layouts_dataset),
-                       input_qinfo_dataset),
-                       output_qinfo_dataset),
+                       input_signed_qinfo_per_channel_dataset),
+                       output_signed_qinfo_per_channel_dataset),
                        add_bias_dataset),
                        framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
 {
@@ -451,8 +456,8 @@
 FIXTURE_DATA_TEST_CASE(Run, NEDeconvolutionLayerQuantizedPerChannelFixture1x1<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data1x1,
                        framework::dataset::make("DataType", DataType::QASYMM8)),
                        data_layouts_dataset),
-                       input_qinfo_dataset),
-                       output_qinfo_dataset),
+                       input_qinfo_per_channel_dataset),
+                       output_qinfo_per_channel_dataset),
                        add_bias_dataset),
                        framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
 {
@@ -462,8 +467,8 @@
 FIXTURE_DATA_TEST_CASE(RunSigned, NEDeconvolutionLayerQuantizedPerChannelFixture1x1<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(data1x1,
                        framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
                        data_layouts_dataset),
-                       input_qinfo_dataset),
-                       output_qinfo_dataset),
+                       input_signed_qinfo_per_channel_dataset),
+                       output_signed_qinfo_per_channel_dataset),
                        add_bias_dataset),
                        framework::dataset::make("WeightsDataType", { DataType::QSYMM8_PER_CHANNEL })))
 {
diff --git a/tests/validation/fixtures/DeconvolutionLayerFixture.h b/tests/validation/fixtures/DeconvolutionLayerFixture.h
index 4bc1d3b..7c06635 100644
--- a/tests/validation/fixtures/DeconvolutionLayerFixture.h
+++ b/tests/validation/fixtures/DeconvolutionLayerFixture.h
@@ -136,8 +136,7 @@
         {
             case DataType::S32:
             {
-                const int32_t value = static_cast<int32_t>(tensor.quantization_info().uniform().offset);
-                library->fill_tensor_value(tensor, value);
+                library->fill_tensor_value(tensor, 0);
                 break;
             }
             case DataType::F16:
diff --git a/tests/validation/reference/DeconvolutionLayer.cpp b/tests/validation/reference/DeconvolutionLayer.cpp
index afbf063..eeb25fc 100644
--- a/tests/validation/reference/DeconvolutionLayer.cpp
+++ b/tests/validation/reference/DeconvolutionLayer.cpp
@@ -24,6 +24,7 @@
 #include "ConvolutionLayer.h"
 
 #include "tests/validation/Helpers.h"
+
 namespace arm_compute
 {
 namespace test